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Rsi_divergence

Volume Weighted RSI PRO | AnonycryptousVolume Weighted RSI Pro | Anonycryptous Description & user manual Why this indicator is different Standard RSI treats every bar equally. A bar where 100 lots traded and a bar where 100,000 lots traded produce the same RSI value if the price change was the same. That is a fundamental problem. Price moves on low volume are noise. Price moves on high volume are institutional participation. RSI cannot tell the difference. Volume Weighted RSI Pro fixes this at the calculation level. Instead of averaging raw price changes, every gain and loss is multiplied by its relative volume before entering the RSI calculation. A strong move on elevated volume pushes the oscillator harder than the same move on thin participation. A drift in price on below-average volume barely registers. The result is an RSI that reflects who was actually behind the move — not just that a move happened. But volume-weighted RSI alone is one perspective. The indicator adds a second independent layer through the Money Flow Index — a separate oscillator that weights typical price by volume rather than price change. When both VW RSI and MFI agree on an extreme reading, the confluence is structurally different from either line alone. One can be driven by a single large candle. Two separate calculation methods arriving at the same conclusion is harder to dismiss. And then there are the liquidity levels. Most RSI-based indicators live in isolation from price structure. They show you when the oscillator is extended, but not where on the price chart that extension corresponds to meaningful levels. Volume Weighted RSI Pro draws the nearest swing highs and lows directly on the price chart — the levels where stops cluster, where institutions defend positions, and where reversals tend to form. Each level shows the volume ratio at the moment it was created. Each level disappears automatically when price closes through it, and the indicator immediately identifies the next relevant level below or above. The divergence engine connects oscillator behavior with price structure by drawing lines, endpoint markers, and a highlighted box on the price chart that spans the exact bars involved. Not just a signal — a spatial map of what happened and where. This is an RSI indicator that knows where it is on the chart. Important notice Volume Weighted RSI Pro generates signals based on oscillator behavior, volume analysis, and price structure detection. These signals are not financial advice. They do not predict future price movement. They do not guarantee profitability. All trading decisions are made entirely by the user. Always manage your own risk. Always apply your own judgment. 1. Overview Volume Weighted RSI Pro is a multi-layer oscillator built around a volume-weighted RSI calculation. It combines momentum analysis, divergence detection, volume flow confirmation, and liquidity level mapping in a single indicator across both the oscillator pane and the price chart. What it includes: - Volume weighted RSI using relative volume to scale price change contributions - Money Flow Index as a second independent momentum layer - EMA signal line with configurable length and crossover markers - Divergence detection with RSI pane lines and mainchart box visualization - Liquidity level lines on the price chart from confirmed swing highs and lows - Volume ratio label per liquidity level showing institutional activity at formation - Automatic level mitigation: levels disappear when price closes through them - OB/OS zone boxes with per-zone volume intensity tracking - Gradient glow fill between the RSI line and midline - OB/OS exit signals and signal line crossover markers - Bar coloring and mainchart background based on RSI position - Live dashboard with RSI value, volume ratio, zone, divergence, signal, and liquidity levels - Seven alerts covering divergence, exits, and signal line crossovers 2. Core calculation 2.1 Volume weighted RSI Standard RSI sums gains and losses over a lookback period using Wilder's smoothing (RMA). Volume Weighted RSI Pro applies the same structure but multiplies each bar's price change by its relative volume — the ratio of bar volume to the smoothed volume average — before the RMA smoothing step. A bar with twice the average volume contributes twice as much to the gain or loss accumulation. A bar with half the average volume contributes half as much. This means the oscillator level reflects participation quality, not just price displacement. In practical terms: trending moves on rising volume push the oscillator to extremes faster. Pullbacks on thin volume barely move it. This creates a cleaner, more institutionally-aware reading than standard RSI. The volume weighted mode can be toggled off to revert to standard RSI behavior for direct comparison. 2.2 Standard RSI reference line A standard RSI line is plotted as a secondary reference in the same pane. Its color and width are configurable. Divergence between the volume weighted and standard lines reveals moments where volume is distorting the picture — a large move on thin participation that standard RSI registers but the VW version largely ignores, or vice versa. 2.3 Signal line An EMA of the volume weighted RSI value acts as a signal line, similar in concept to the signal line in a MACD. The default length is 9. When the VW RSI crosses above the signal line, momentum is accelerating to the upside. When it crosses below, momentum is decelerating. Crossover markers appear at the exact cross point and can be toggled on or off. The signal line is most useful as a filter — only take a setup if the RSI and signal line agree on direction. 2.4 Money Flow Index The MFI is calculated using typical price ((high + low + close) / 3) multiplied by volume, producing separate positive and negative money flow sums that are then converted to an index between 0 and 100. It shares the same scale as the VW RSI, making direct visual comparison possible. The MFI responds differently from VW RSI because it weights price level rather than price change. Elevated MFI without elevated VW RSI suggests buying pressure at current levels without strong directional momentum. Both indicators in overbought territory simultaneously is a stronger condition than either alone. 3. Divergence detection Divergence is detected by comparing pivots in the volume weighted RSI against pivots in price over a configurable lookback window Bearish divergence: price makes a higher high while VW RSI makes a lower high. Momentum is weakening as price extends — a structural warning. Bullish divergence: price makes a lower low while VW RSI makes a higher low. Selling pressure is exhausting even as price continues lower — a structural opportunity. Sensitivity controls the pivot lookback window: - High: 3-bar pivots. More signals, more false positives. - Medium: 5-bar pivots. Balanced default. - Low: 10-bar pivots. Fewer signals, higher quality. When a divergence confirms, two things are drawn simultaneously. In the RSI pane: a solid line connecting the two pivot RSI values. On the price chart: a box spanning the full price range of the bars involved in the divergence. This makes the spatial relationship between the oscillator event and the price structure immediately visible. The divergence box does not confirm a trade. It confirms that a structural disagreement between price and momentum occurred, and where on the chart it happened. 4. Liquidity levels Liquidity levels are drawn on the price chart at confirmed swing highs and lows using a pivot detection engine. They represent the price levels where stop orders are likely to cluster — below swing lows for buy stops and above swing highs for sell stops. These are the levels that institutional participants use as targets when running liquidity. Each level is a horizontal line that starts at the pivot bar and extends to the right in real time. The nearest level is fully opaque. Additional levels fade with distance from current price. Each level displays a volume ratio label at its origin — the bar's volume at the time of pivot formation relative to the recent average. A level formed on 2.1x average volume is more institutionally significant than one formed on 0.7x volume. This context is part of reading the level. When price closes through a level, it is removed immediately. The indicator repopulates from the remaining valid pivots. There is no manual cleanup and no visual clutter from levels that have already been swept. The detail level setting controls how aggressively levels are detected: - Minimal: wide pivot lookback, only the most significant structural highs and lows qualify. - Standard: balanced detection, practical default across most timeframes. - Full: tighter pivot lookback, more levels are identified. The dashboard shows the nearest bull side level (BSL) and bear side level (SSL) by price, updated in real time. 5. OB/OS zone tracking When the VW RSI enters overbought or oversold territory, the indicator begins accumulating the total volume transacted during that period. When price exits the zone, a filled box is drawn over the duration of the zone on the RSI pane. The box includes a volume intensity label showing how the average volume inside the zone compared to the baseline average. A zone with 1.8x average volume indicates elevated institutional activity during the extreme reading — the extension was not just price drift but active participation. A zone below 1.0x is thin and less meaningful. OB/OS zones are off by default. 6. Visual guide RSI pane elements: - Bright green/red RSI line — volume weighted RSI, color intensity increases toward OB/OS extremes - Grey reference line — standard RSI, configurable color and width - Gold line — signal line (EMA of VW RSI) - Purple line — MFI - Gradient glow fill — color intensity increases from midline toward the RSI line, creating a visual depth effect that reflects how extended the oscillator is - OB/OS background — deepens in red or green when RSI is in extreme territory - ▲ marker — RSI exiting oversold territory - ▼ marker — RSI exiting overbought territory - ✕ marker — RSI/signal line crossover (when enabled) - Divergence line — solid colored line between the two pivot RSI values Mainchart elements: - Horizontal lines — liquidity levels, color and opacity by distance from current price - Volume label at origin — volume ratio at pivot formation bar - Divergence box — spans the full price range of the divergence bars - Background color — subtle green above RSI 50, subtle red below - Bar coloring — gradient intensity based on RSI position 7. Dashboard reference The dashboard is positioned bottom right by default and updates on every bar close. VW RSI — current VW RSI value, colored by position. Vol ratio — current bar volume relative to the smoothed average. Values above 1.5x are highlighted in gold. Zone — current RSI zone: overbought, oversold, or neutral. Divergence — active divergence state if detected on the most recent pivot. Signal — most recent signal condition. — Liquidity — Near BSL — nearest bull side liquidity level below current price. Near SSL — nearest sell side liquidity level above current price. Liq levels — count of active levels on each side. Mode — VW (volume weighted) or STD (standard RSI mode). Anonycryptous — indicator brand and version. 8. Alerts Seven alert conditions are available: - Bullish divergence: price lower low with VW RSI higher low confirmed. - Bearish divergence: price higher high with VW RSI lower high confirmed. - OS exit signal: RSI crosses back above the oversold level. - OB exit signal: RSI crosses back below the overbought level. - Any divergence: fires on either divergence type. - Signal cross up: VW RSI crosses above the signal line. - Signal cross down: VW RSI crosses below the signal line. 9. Settings reference 9.1 RSI settings - RSI length: lookback period for the VW RSI calculation. Default 14. - Volume smoothing: lookback for the volume moving average. Default 14. - Volume weighted mode: toggle between volume weighted and standard RSI. - Show signal line: toggle the EMA signal line. - Signal line length: EMA period for the signal line. Default 9. - Show signal crossovers: toggle ✕ markers at signal line crossovers. Default off. - Show MFI line: toggle the Money Flow Index line. - MFI length: lookback for MFI calculation. Default 14. - MFI color: default brand purple. - MFI line width: 1 to 4. Default 2. - Overbought level: threshold for OB signals and zone tracking. Default 70. - Oversold level: threshold for OS signals and zone tracking. Default 30. 9.2 Divergence - Sensitivity: pivot lookback window — high (3), medium (5), low (10). - Show bullish divergence. - Show bearish divergence. - Divergence box on mainchart: draws the price range box on the price chart. - Div line width: stroke weight of divergence lines. 1 to 4. Default 2. 9.3 Liquidity levels - Show liquidity levels: toggle all liquidity lines on the price chart. - Detail level: minimal, standard, or full pivot sensitivity. - Pivot lookback: swing detection window. Default 10. - Max levels each side: maximum lines shown above and below current price. Default 2. 9.4 OB/OS zones - Show OB/OS zones: toggle zone boxes in the RSI pane. Default off. - Volume intensity label: show per-zone volume ratio label. - Zone transparency: fill opacity for OB/OS zone boxes. 9.5 Visuals - Bull color: primary bull color across all elements. - Bear color: primary bear color across all elements. - Bull div color: color for bullish divergence lines and box. - Bear div color: color for bearish divergence lines and box. - Std RSI color: color of the standard RSI reference line. - Std RSI width: stroke weight of the reference line. - Bar coloring: gradient bar color based on RSI position. - Signal size: size of OB/OS exit markers — tiny, small, or normal. - Show background color: subtle mainchart background based on RSI direction. - Background transparency: opacity of the mainchart background. 9.6 Dashboard - Show dashboard. - Position: top left, top right, bottom left, or bottom right. - Size: tiny, small, or normal. 10. How to use 10.1 Reading divergence Divergence is not a signal to enter immediately. It is a warning that the relationship between momentum and price is breaking down. The most effective approach is to wait for the divergence box to appear on the price chart and then look for a second confirmation — a signal line crossover, an OB/OS exit marker, or a price reaction at a nearby liquidity level — before treating the setup as actionable. Divergence on its own can persist for many bars before price reacts. Use it as directional context, not as a trigger. 10.2 Using liquidity levels The liquidity lines show where the market has unfinished business — swing levels that formed on meaningful volume and have not yet been revisited. When the VW RSI is approaching overbought or showing bearish divergence and price is simultaneously approaching a sell-side liquidity level above, those two conditions are pointing at the same structural event from different angles. The volume ratio label at each level is particularly useful. A level formed on 0.6x average volume is a weak level that may not generate a meaningful reaction. A level formed on 2.5x average volume suggests a move was initiated or defended with institutional size. Treat these differently. 10.3 Using VW RSI and MFI together When both lines are in overbought territory simultaneously, the condition is stronger than either alone. VW RSI is extended on momentum. MFI confirms that money flow at current price levels is also elevated. The two calculations are independent — their agreement is not trivial. When they diverge — VW RSI overbought while MFI is not — one of the components is not confirming the other. This does not mean the move is wrong, but the confluence is weaker. 10.4 OB/OS zone volume When the zone volume label shows above 1.5x, the extreme RSI reading occurred during elevated participation. That tells you the extension was not just mechanical drift — there was active buying or selling pressure behind it. An exit from that zone after a high-volume OB/OS period carries more weight than an exit from a thin zone. 10.5 Illustrative bull scenario Educational example only. Not a trading recommendation. VW RSI drops into oversold on above-average volume. A bull-side liquidity level sits 0.8% below current price, formed three sessions ago on 2.1x volume. VW RSI begins making a higher low while price makes a lower low — bullish divergence is confirmed. A divergence box appears on the price chart. The RSI crosses back above the oversold level, firing a ▲ marker. The signal line crossover fires shortly after. Three separate conditions align: oversold exit, bullish divergence, and signal line confirmation. 10.6 Illustrative bear scenario Educational example only. Not a trading recommendation. Price rallies into a sell-side liquidity level visible on the chart at 2.2x formation volume. VW RSI is in overbought territory while MFI is also elevated. Price makes a higher high but VW RSI makes a lower high — bearish divergence is drawn on the RSI pane and a box appears on the price chart covering the divergence range. RSI crosses back below overbought. A ▼ marker fires. The setup has divergence, OB exit, and a liquidity level all at the same location. 11. Tips The volume ratio in the dashboard is one of the most underused readings. A vol ratio below 0.7 means current price action is thin — institutions are not participating. Signals that fire on low volume ratio are less reliable than those that fire on 1.5x or above. Signal line crossovers are most useful as filters. Toggle them on during active sessions to see where momentum flips are occurring relative to the rest of the setup. Too many crossovers on a given session usually means the market is ranging — reduce position size or wait for the RSI to expand toward an extreme before taking the cross seriously. The standard RSI reference line reveals when volume weighting is changing the picture. If the VW RSI is significantly above the standard line, it means recent price movement was driven by above-average volume. If the VW RSI is below the standard line, price moved on thin participation — the market did not commit to the direction. Liquidity level count in the dashboard tells you how many valid structural references remain. When the count drops — because levels are being swept — it means the market is clearing stops. That is meaningful context for the direction of the current move. 12. Disclaimer This indicator is provided for educational and informational purposes only. Nothing in this document or in the indicator output constitutes financial advice or any form of recommendation. Trading financial instruments involves substantial risk of loss. Past performance is not indicative of future results. You may lose all of your invested capital. Anonycryptous accepts no responsibility or liability for any losses incurred as a result of using this indicator.
Penunjuk Pine Script®
oleh Anonycryptous
Cadence Reversion Cartography [JOAT]Cadence Reversion Cartography Introduction Cadence Reversion Cartography is an open-source mean-reversion and exhaustion overlay designed to locate stretched conditions around an EMA envelope and anchored VWAP framework. It focuses on mapping where price has moved too far from local balance, then grades whether a return toward value has enough supporting evidence to matter. The problem this script solves is selective reversal timing. Price can stay overextended for longer than expected, so simple band-touch logic is not enough. Cadence Reversion Cartography combines envelope stretch, VWAP stretch, RSI exhaustion, volume impulse, rejection-candle behavior, reclaim logic, and projected response boxes so the user can distinguish weak touches from stronger reversion candidates. Core Concepts 1. Dual Stretch Model Price is compared to both an EMA deviation envelope and an anchored VWAP deviation layer. A long-side exhaustion condition requires price to stretch below both lower references. A short-side exhaustion condition requires price to stretch above both upper references. 2. Exhaustion Quality Filters RSI can require oversold or overbought context, volume can require impulse relative to average participation, and candle structure can require a visible rejection profile. 3. Reclaim And Signal Grading A setup becomes actionable only after price closes back inside the envelope on a confirmed bar. The script then scores the setup by counting how many filters aligned and promotes stronger signals to a prime grade. 4. Projection Mapping When a setup forms, the script can draw a forward projection with a risk box, reward box, signal zone, and reclaim line. This is meant to show the structure of the reversion idea rather than acting as a promise of outcome. Features EMA reversion envelope: Basis plus statistical deviation bands Anchored VWAP stretch layer: Secondary value reference around VWAP RSI exhaustion filter: Optional momentum exhaustion gate Volume impulse filter: Optional participation confirmation Rejection-candle filter: Optional candle-structure confirmation Signal grading: Standard and prime long or short responses Signal zones and reclaim lines: On-chart response structure around the active setup Risk and reward projection boxes: Optional forward mapping of stop and target structure Context candle coloring: Candles can tint with stretch state Dashboard: Displays stretch, setup bias, and active context Input Parameters Reversion Envelope: Channel Length Deviation Multiplier VWAP Stretch Multiplier Filters And Display: RSI settings Volume average and impulse multiplier Rejection-candle requirement Projection-box toggle, stop percent, reward multiple, projection length, and signal cooldown Dashboard, background, candle-color, and signal-zone toggles How to Use This Indicator Step 1: Wait for price to stretch beyond both the EMA envelope and the VWAP stretch layer. Step 2: Check whether RSI, volume, and rejection filters support the move. Step 3: Wait for confirmed re-entry back inside the envelope instead of fading the first touch. Step 4: Use the signal grade and projection structure to judge whether the setup is marginal or stronger. Step 5: Use the basis and reclaim line as the first balance reference after entry. Indicator Limitations Strong directional trends can keep price stretched for extended periods and delay reversion Volume-based confirmation is less meaningful on symbols with irregular volume reporting Projection boxes are planning tools, not guaranteed outcomes This script is designed for reversion analysis and is not intended to replace broader trend context Originality Statement Cadence Reversion Cartography is original in how it coordinates envelope stretch, VWAP stretch, filter-based exhaustion grading, and forward projection structure inside one reversion workflow. The components are combined to answer one analytical problem: not just whether price is stretched, but whether the stretch is mature enough to support a structured return toward value. Disclaimer This indicator is provided for educational and informational purposes only. It is not financial advice. Reversion setups can fail during strong trends or regime expansion, so all signals should be used with independent confirmation and risk management. -Made with passion by jackofalltrades
Penunjuk Pine Script®
oleh officialjackofalltrades
Momentum Covenant Bias [JOAT]Momentum Covenant Bias Introduction Momentum Covenant Bias is an open-source momentum pane designed to classify whether the market is in a constructive, defensive, balanced, or compressed state. It blends WaveTrend timing, RSI displacement, normalized trend distance, compression logic, layered state bands, pane boxes, and an optional force-overlay TP/SL scaffold when fresh confirmed momentum shifts occur. This indicator is meant to solve timing. Trend and auction context can describe where the market is, but they do not always tell you whether momentum is actually participating in the current move. Momentum Covenant Bias translates several independent momentum dimensions into one composite state engine and presents them in a clean, institutional-style pane. Core Concepts 1. WaveTrend Timing WaveTrend serves as the primary turning-point rhythm engine. The script uses the relationship between the main line and signal line to measure timing pressure. 2. RSI Displacement RSI is evaluated not only relative to 50, but also relative to its own smoothed mean. This helps distinguish raw strength from persistent displacement. 3. Normalized Trend Distance Price distance from the slower trend baseline is normalized by ATR so the output remains portable across markets with different price scales. 4. Compression State Compression logic compares recent range behavior to a slower baseline. This helps identify lower-energy conditions before expansion. 5. State Boxes and Overlay Scaffold The pane includes positive, negative, and compression zones, and can project a force-overlay TP/SL scaffold on the chart when a fresh momentum shift is confirmed. Features Composite momentum score: Combines WaveTrend, RSI, trend distance, and compression context Signal line: Smoothed line for momentum transitions Layered state bands: Positive, negative, and extension zones rendered as gradients Compression boxes: Visual isolation of low-energy conditions Top-right dashboard: Displays composite score, signal, wave state, RSI, compression, trend distance, and scaffold status Force-overlay TP/SL scaffold: Optional informational rails on fresh positive or negative momentum shifts Confirmed-bar state promotion: Uses confirmed bars for event states instead of unstable intrabar triggers How to Use This Indicator Step 1: Read the composite state first. Balanced states should be interpreted differently from impulse states. Step 2: Compare the composite score to the signal line. Fresh separation often matters more than absolute level alone. Step 3: Watch compression zones. These can help explain why a market is not yet extending despite directional context elsewhere. Step 4: If using the optional scaffold, treat it as a planning aid that reflects momentum state, not as a standalone trade system. Indicator Limitations Momentum state can reverse quickly in whipsaw markets Compression logic can remain active for extended periods in slow markets WaveTrend and RSI are still derivatives of price and can lag during violent reversals The overlay scaffold is informational and does not execute orders Originality Statement Momentum Covenant Bias is original in the way it combines multi-source momentum confirmation, pane state boxes, gradient regime presentation, and force-overlay planning rails in one open-source script. The indicator is intended as a timing layer that complements structure and auction context instead of replacing them. Disclaimer This indicator is provided for educational and informational purposes only. It is not financial advice. Momentum conditions are derived from historical price behavior and may fail or reverse without warning. Use proper risk management and independent validation. -Made with passion by jackofalltrades
Penunjuk Pine Script®
oleh officialjackofalltrades
Adaptive Swing Matrix | MouryaThis indicator provides a Multi-Timeframe (MTF) table matrix designed to display the real-time states of several standard momentum and trend indicators across 11 user-defined timeframes simultaneously. The primary purpose of this script is to consolidate chart real estate. By organizing MTF data into a single table, it allows users to monitor higher-timeframe trends and oscillator states without needing to continuously switch chart intervals or clutter their screen with multiple lower panes. Indicator Logic & Components: This matrix tracks the following standard indicators across the user's chosen timeframes: Trend (EMA Crossover): Evaluates a fast EMA crossing a medium or slow EMA, filtered by a macro 200-period baseline EMA. RSI (Relative Strength Index): Displays the current RSI value, color-coded based on user-defined breakout/breakdown thresholds. MFI (Money Flow Index): Displays volume-weighted momentum. ADX (Average Directional Index): Evaluates trend strength to filter out sideways consolidation periods. MACD (Moving Average Convergence Divergence): Evaluates the relationship between the MACD line and the Signal line relative to the zero-line. The matrix uses the following acronyms to display the exact MACD state: AZPCO: Above Zero, Positive Crossover (MACD is > 0 and MACD > Signal) AZNCO: Above Zero, Negative Crossover (MACD is > 0 and MACD < Signal) BZPCO: Below Zero, Positive Crossover (MACD is < 0 and MACD > Signal) BZNCO: Below Zero, Negative Crossover (MACD is < 0 and MACD < Signal) VWAP (Volume Weighted Average Price): Displays the current VWAP value and highlights if the closing price is currently holding above or below the baseline. NASDAQ:INTC Matrix Features: Customizable Timeframes: Users are not restricted to default intervals. You can input custom minute, hour, day, week, or month intervals for all 11 rows via the settings menu. Overall Consensus Score: The bottom row of the table evaluates a 7-timeframe core grouping. If a strict majority of these selected timeframes share the same trend direction, it outputs a unified directional signal. Visual Chart Overlays: Users can optionally enable the EMA lines and VWAP bands on their main chart. These visual elements have been strictly segregated in the indicator's Style tab for easy toggling. All backend settings—including lengths, source data, and trigger thresholds for the RSI, MFI, and ADX—are fully unlocked in the inputs menu for personal customisation.
Penunjuk Pine Script®
oleh RajMouryaReddy
Sigma Channel [JOAT]JOAT Sigma Channel Introduction JOAT Sigma Channel is an open-source regression-based channel overlay built to identify the best-fit directional corridor across a search range of candidate windows. It is designed to show whether price is traveling normally inside a fitted corridor, stretching away from it, reclaiming it, or moving into stress territory. The problem it solves is model selection. A fixed-length regression channel can look excellent in one regime and poor in the next. If the market accelerates, slows down, or shifts its dominant drift horizon, a static window becomes less useful. Sigma Channel solves that by searching a range of possible windows and selecting the strongest available fit. That fit becomes the active corridor. Around it the script builds multiple sigma tiers. These tiers create a richer price-state map than a single upper and lower band. The result is a more useful framework for reading acceptance, stretch, reclaim, and exhaustion. Core Concepts 1. Multi-Window OLS Search The script evaluates multiple candidate regression windows and scores them by fit quality. for len = minWindow to maxWindow by stepWindow = f_model(len) 2. Sigma-Tier Envelope Stack The fitted centerline is surrounded by inner, core, outer, and stress layers. 3. Slope and Quality Diagnostics The chosen model exposes both slope and fit quality. 4. Reclaim and Acceptance States The script identifies when price reclaims or accepts back inside the corridor after extension. 5. Stress-State Shading The most extreme statistical layer is visually emphasized. 6. Forward Projection The active model projects forward to keep the corridor useful at the right edge. 7. Residual Awareness Residual behavior helps judge whether the active model remains representative. 8. Gradient Candle Context Bar coloring transitions with the current statistical state. Features Adaptive regression search: scans multiple windows instead of using one fixed length Inner, core, outer, and stress bands: multiple sigma tiers for normal and abnormal travel Slope-aware corridor logic: distinguishes positive and negative drift Reclaim and acceptance events: return-to-channel behavior is identified Stress shading: abnormal statistical extension is highlighted Forward projection: the active corridor extends to the chart edge Gradient candle tinting: bar color reflects the current z-state Dashboard: slope, quality, window, and deviation state are summarized Input Parameters Model Search: Minimum Window Maximum Window Window Step Minimum R-Squared Projection Bars Deviation Envelope: Inner Sigma Core Sigma Outer Sigma Stress Sigma Filter Stack / Visual System: Bias EMA ATR Length Momentum RSI Use EMA Bias Gate Use RSI Gate Use Volume Gate Tint Bars Show Projection Show Dashboard How to Use This Indicator Step 1: Check the active slope and whether the corridor is upward, downward, or balanced. Step 2: Check fit quality before trusting the active statistical path. Step 3: Read whether price is inside the core corridor, at the outer layer, or in stress territory. Step 4: Watch reclaims back into the channel after extension. Step 5: Use the projection to organize the near-future chart space. Indicator Limitations The selected best-fit window can change as the market evolves Linear regression becomes less representative in strongly nonlinear markets Statistical extension does not guarantee immediate reversal The indicator measures deviation from a model, not directional certainty Originality Statement This script is original in the way it combines adaptive regression selection, multi-tier sigma structure, reclaim logic, stress-state shading, and forward projection into one corridor framework. The goal is not just to draw a regression channel. The goal is to keep the active model responsive while preserving statistical context. Disclaimer This indicator is provided for educational and informational purposes only. It is not financial advice. Regression fit and statistical deviation do not predict future price with certainty. Markets can remain extended or break away from the active fit entirely. Best Use Cases Reading whether price is behaving normally inside a fitted directional corridor Identifying statistical stretch and stress states Watching for reclaim behavior after extension Combining statistical deviation with separate structure or liquidity analysis Interpretation Notes The channel should be trusted more when fit quality is stronger and the slope is clear. Core travel is generally more normal than outer-band travel. Stress states are especially useful when they coincide with separate structural or participation warnings. The projection should be read as a continuation of the current best-fit model, not as a forecast guarantee. Publication Notes This script is intended to be published with a clean chart where the corridor, the active slope, and at least one reclaim or extension state are obvious. The example chart should help the viewer understand how the band hierarchy works. Avoid combining it with unrelated overlays in the publication image. -Made with passion by jackofalltrades
Penunjuk Pine Script®
oleh officialjackofalltrades
Liquidity Cartography [JOAT]JOAT Liquidity Cartography Introduction JOAT Liquidity Cartography is an open-source liquidity mapping overlay built to organize where price has swept obvious pools, where imbalance still exists, and where repricing blocks remain active. It combines prior-day and prior-week references, equal-high and equal-low clustering, sweep-state persistence, displacement logic, imbalance arrays, repricing block arrays, and confluence scoring. The problem it solves is fragmented liquidity analysis. Many traders watch prior highs and lows separately from fair value gaps, separately from equal highs and lows, and separately from displacement. This script turns those references into one coordinated chart map. That makes it easier to judge whether the market is merely tapping a level, actually sweeping it, or accepting away from it with structure and participation. The script is useful because it tracks the sequence, not just the level. A prior-day low by itself is only a reference. A sweep below it is more informative. A sweep followed by displacement and structure recovery is a different condition again. Liquidity Cartography is built around those transitions. The box system is managed over time. Zones are extended, aged, and deleted when invalidated or expired. That keeps the chart focused on currently relevant liquidity rather than permanent drawings. Core Concepts 1. Daily and Weekly Reference Liquidity The script tracks PDH, PDL, PWH, and PWL. These are the major reference pools used to judge whether price is probing obvious liquidity. = request.security(syminfo.tickerid, "D", [high , low ], lookahead = barmerge.lookahead_on) = request.security(syminfo.tickerid, "W", [high , low ], lookahead = barmerge.lookahead_on) 2. Equal-High and Equal-Low Tracking Confirmed pivots are compared in ATR terms to identify clustered highs and lows. 3. Sweep-State Persistence Sweeps remain active for a configurable confirmation window. That allows follow-through logic to validate the narrative. 4. Displacement Validation The script checks whether the reaction away from a pool is meaningful through body expansion and gap behavior. 5. Imbalance Management Imbalance zones are stored and extended as long as they remain active. 6. Repricing Block Management Order-block style repricing areas are created after structural breaks and managed over time. 7. Filter Stack Trend, RVOL, RSI, and session filters can refine signal quality. 8. Confluence Scoring The indicator counts alignment across the active liquidity narrative. Features Prior-day and prior-week levels: major reference pools are tracked Equilibrium levels: daily and weekly range centers are shown Equal-high / equal-low detection: clustered pools are identified Sweep persistence: active sweep context remains available for confirmation Displacement checks: strong rejection is separated from weak noise Imbalance boxes: active FVG-style zones extend until mitigation or expiry Repricing blocks: revisit zones are stored and managed Filter stack: trend, RVOL, RSI, and session alignment are available Confluence scoring: current liquidity alignment is summarized Dashboard: active pool, trend, confluence, and signal state are displayed Input Parameters Reference Levels: Show Prior Day Levels Show Prior Week Levels Show Equilibrium Track Weekly Sweeps Sweep / Zone Logic: Structure Length Sweep Reset Bars Zone Extension Equal Pool Tolerance ATR Zone Max Age History Limits Validation: Require Displacement Displacement Multiplier Use Trend Filter Use RVOL Filter Use RSI Filter Use Session Filter How to Use This Indicator Step 1: Identify the active daily or weekly liquidity pool. Step 2: Check whether price only touched the pool or actually swept it. Step 3: Look for displacement and structure response after the sweep. Step 4: Watch active imbalances and repricing blocks for later revisits. Step 5: Use the confluence count to separate weak narratives from stronger ones. Indicator Limitations Obvious liquidity pools can be tapped or swept multiple times before direction resolves Object-heavy overlays may appear dense on low timeframes if many zones remain active Pivot-based pool detection confirms after the swing completes, which is intentional non-repainting behavior Zones are analytical references, not guarantees of reversal or continuation Originality Statement This script is original in how it combines sweep persistence, equal-pool detection, imbalance inventory, repricing blocks, and confluence scoring into one coordinated liquidity framework. The components are integrated because they all describe the same process: price probing liquidity, taking it, and either failing or accepting beyond it. Disclaimer This indicator is provided for educational and informational purposes only. It is not financial advice. Liquidity reactions can fail. Sweeps can repeat. No level or zone guarantees a directional outcome. Always use independent judgment and risk management. Best Use Cases Mapping where obvious daily and weekly liquidity is likely resting Studying how price behaves after a confirmed sweep Tracking whether displacement and imbalance support the sweep narrative Marking revisit zones after structural repricing Interpretation Notes A sweep by itself is only the beginning of the story. The more useful sequence is sweep, displacement, structural response, and active zone support. Equal-high and equal-low references are helpful because they often identify where liquidity may accumulate before the sweep occurs. The confluence score should be interpreted as a narrative-strength read, not a promise of reversal. Publication Notes This script is intended to be published with a clean chart that clearly shows the active liquidity pool, the current sweep state, and one or two relevant active zones. Do not overload the publication chart with unrelated drawings. The value of the visual example should come from clarity rather than chart decoration. -Made with passion by jackofalltrades Chart Reading Framework 1. Start with the active daily or weekly pool. 2. Determine whether price only touched or truly swept the pool. 3. Check displacement, break state, and confluence. 4. Review active imbalances and repricing blocks for the next revisit path. 5. Use the dashboard to verify whether the liquidity narrative is strengthening or fading. Why This Matters Liquidity logic becomes much more useful when it is organized as a process instead of a list of disconnected levels. This indicator is meant to help the user see that process clearly. Open-Source Notes This script is published open source so users can inspect how sweep persistence, imbalance management, and zone aging are handled. Who This Is For This indicator is for traders who want a structured liquidity map rather than isolated levels. It is especially useful for users who think in terms of sweeps, repricing, and revisit zones. Summary JOAT Liquidity Cartography turns scattered liquidity references into one organized live framework. Its main value is clarity. Additional Notes The strongest use of this script comes from following the sequence of events rather than reacting to a single box or line in isolation. Clean publication images should make that sequence obvious.
Penunjuk Pine Script®
oleh officialjackofalltrades
Liquidity Matrix | AnonycryptousLiquidity Matrix | Anonycryptous Description & user manual **Credits** The sweep detection engine in Liquidity Matrix draws conceptual inspiration from the Liquidity Sweep Filter by AlgoAlpha. The approach to identifying swing-based stop hunts, classifying sweeps by volume significance, and filtering by trend direction is based on ideas first demonstrated in their open-source script, author: AlgoAlpha (tradingview.com/u/AlgoAlpha) --- Why this indicator is different; Most liquidity indicators show you one thing. A zone. A sweep marker. A supply box. A trendline. Each tool tries to solve one problem, and if you want to understand the full picture, you stack five or six indicators on the same chart until it becomes unreadable. Liquidity Matrix works differently. It is not a signal indicator. It does not tell you when to buy or sell. It does not score your trades or track your win rate. What it does is something more fundamental: it maps the full landscape of liquidity around price, across ten independent engines, all configurable, all in one overlay. The core idea is that liquidity drives price. Retail traders place stops at predictable locations — below swing lows, above swing highs, at equal highs and lows, at structural pivots, inside fair value gaps. Institutional participants know this. They move price to those locations, collect that liquidity, and then move in the direction they were always going. If you understand where the liquidity is, where it has already been taken, and what levels are still sitting unmitigated, you understand the context before you place a trade. Liquidity Matrix gives you that map. What makes it different from other multi-engine indicators is that every engine is genuinely independent. You can run just the liquidity zones. Or just the voids and HTF levels. Or every engine at once and build your own confluence system. There is no forced reading. There is no house view on what the market is doing. You bring your methodology. The indicator gives you the context to apply it. It also does something no single-purpose tool does: it shows you the volume behind every level. Not just where the stop clusters are — but how much liquidity was there when they formed. A zone created on 2.4M volume is not the same as a zone created on 58K. The indicator makes that difference visible. Important notice Liquidity Matrix does not generate trading signals. It does not tell you when to buy or sell. It does not predict market direction. It does not guarantee any outcome. All trading decisions remain entirely with the user. Always apply your own judgment and manage your own risk. 1. Overview Liquidity Matrix is a multi-engine liquidity context indicator built around one idea: before you place a trade, understand where the liquidity is. What it includes: - Liquidity zones: probability-scored pivot clusters with volume intensity rendering - Equal highs and equal lows: zones where retail stops stack at matching price levels - Trend engine: directional band with accumulated sweep volume tracking - Sweep detection: swing-level stop hunt identification with safe stop placement - HTF liquidity levels: higher timeframe high/low levels as horizontal reference lines - Dynamic trendlines: automatically detected diagonal support and resistance with touch volume - Supply and demand zones: SMC-based structural zones with BOS conversion - Weekend gap: Friday close reference with gap fill tracking - Liquidity voids: fair value gaps with gradient layer fill tracking - RSI divergence: price chart divergence detection with candle coloring and optional trailing stop - Dashboard: live market context across all active engines 2. Liquidity zones 2.1 How they form Liquidity zones are identified at confirmed pivot highs and lows. A pivot forms when a price extreme holds for a configurable number of bars on both sides. Each zone is scored using a probability model that weighs four factors: distance from current price, age of the zone, whether it is still fresh (untested), and the volume present at formation. The result is a probability score from 0 to 100 displayed on the chart. A score above 70 appears in green. Between 40 and 70 it appears in gold. Below 40 it appears in red. The fill intensity of each zone box scales automatically with the normalized volume at formation. Higher volume at creation means a fuller, more opaque box. This makes the visual weight of each zone reflect its actual significance without requiring manual evaluation. Zones above price are BSL — buy side liquidity. These are where long stops and breakout orders sit. Zones below price are SSL — sell side liquidity. These are where short stops and breakdown orders sit. 2.2 Sweep markers When price breaks through the bottom of a demand zone or the top of a supply zone, a circle marker appears on the chart — above the candle for a supply zone break (bearish), below the candle for a demand zone break (bullish). The zone fades to indicate the liquidity has been consumed. This is distinct from the swing sweep detection engine, which operates independently. 2.3 Settings Pivot left and right bars control detection sensitivity. Fewer bars on the right produces faster confirmation but reduces accuracy. The volume filter removes zones that formed on below-average activity. Fresh zones only hides tested zones to keep the chart clean. Max zones controls how many active zones are held at once. The swept zone transparency and show swept toggle control what remains visible after a zone is consumed. 2.4 In practice Look for price approaching an unmitigated zone with a high probability score on high-volume context. The higher the score and the more opaque the box, the more likely institutional interest was present at formation. When multiple zones stack closely — visible as a cluster — that price area has concentrated stop density. When a zone is swept and the circle marker appears, the liquidity at that level has been cleared. Stops are gone. The level loses its significance as a target. Volume note: all volume values in Liquidity Matrix are expressed in the base currency of the trading pair. On BTC/USDT, the value shown is in BTC. On SOL/USDT, it is in SOL. To convert to USD equivalent, multiply by the current price. This applies to every volume label across all engines. 3. Equal highs and equal lows 3.1 How they form Equal highs and equal lows (EQH/EQL) are zones where price has tested the same level on two or more separate occasions without closing through it. These represent areas where retail stop orders have accumulated in a predictable way. Matching swing highs create a resistance cluster with long stops resting above. Matching swing lows create a support cluster with short stops resting below. The zones are rendered as filled boxes using a linefill between two lines. The box spans from the lower of the two matching pivots to the higher, creating a clearly visible area of concentrated liquidity. 3.2 Settings Tolerance (ATR×) controls how precisely two pivots must match to qualify as equal. A lower tolerance requires a near-exact match. A higher tolerance allows approximate levels to be grouped. The minimum age prevents recent, unconfirmed pivots from forming zones too early. The removal mode determines whether a zone is removed when price touches the wick, the body, or the body at twice ATR distance. 3.3 In practice An EQH/EQL zone directly above or below price is a high-probability target for a liquidity sweep. When price approaches such a level, consider whether the move has the characteristics of a stop hunt: a spike through the level, a strong close back inside, and a reversal. The volume label on each zone shows the total volume from both matching pivots combined — giving you a sense of how much liquidity is sitting there. 4. Trend engine 4.1 How it works The trend engine calculates a rolling volatility band using ATR. When price is above the upper band, the trend direction is bullish. When price is below the lower band, it is bearish. The band tracks the dominant directional bias and changes color accordingly. As the trend unfolds, peak and valley levels form at local turning points within the band. The engine accumulates the volume from sweep events at each of these turning points and displays it as a label on the band. The label shows the total volume cleared at that inflection point — a direct measure of how much liquidity was consumed as the trend moved through that level. 4.2 In practice The trend direction is shown in the dashboard as bull or bear. Use this as your macro bias filter. Look for setups in the direction of the trend. The volume labels along the band show where the significant sweeps occurred — these points represent former liquidity levels that have already been consumed and are unlikely to act as targets again. The current edge of the band is where the next sweep may occur. 5. Sweep detection 5.1 How it works The sweep detection engine monitors rolling swing highs and lows using a configurable lookback. When price spikes through a swing level on the wick and closes back inside, a sweep event is recorded. The wick must penetrate the level by at least a minimum ATR multiple. The close must reject with a minimum strength relative to the candle range. An optional EMA filter and cooldown period reduce false triggers. Sweeps are classified as major or minor based on normalized volume. A sweep on above-average volume is marked with a solid triangle. A below-average sweep is marked with a hollow triangle. When a sweep fires, a safe stop line is drawn at the sweep extreme — the wick tip. This is the correct location for a stop loss after a sweep, because the liquidity that was resting there has already been consumed. Placing a stop beyond a consumed sweep is placing it where no further stop hunt is likely to occur. 5.2 Settings The wick minimum ATR multiple and minimum rejection percentage filter out weak sweeps. The EMA filter aligns sweeps with the broader trend. The cooldown prevents repeated triggers from the same level. Major sweep threshold (normalized volume) separates significant events from minor ones. 5.3 In practice A major sweep on a significant EQH or liquidity zone is one of the cleanest setups in the indicator. Price took the liquidity, volume confirms the institutional event, and the safe stop line gives you a clear invalidation level. The smaller the distance between current price and the safe stop line, the more attractive the risk structure. 6. HTF liquidity levels 6.1 How they form Higher timeframe high and low levels represent the largest clusters of resting liquidity on the chart. Monthly, weekly, daily, previous day, 4-hour, and 1-hour levels are supported. Each level is drawn as a horizontal line starting at the bar time of the HTF candle that created it and extending a configurable number of bars to the right. The volume of the HTF candle is shown as a label at the right edge of the line. Higher volume on the HTF candle means more institutional activity was present when that level formed. Monthly levels have the highest opacity. Opacity decreases progressively as timeframe decreases, so the relative significance is immediately visible. 6.2 Settings Each timeframe is individually toggleable. Line style (solid, dashed, dotted), width, and color are configurable. Extend bars controls how far the line projects to the right. The liquidity label can be hidden if a cleaner chart is preferred. 6.3 In practice HTF levels are major liquidity magnets. Price tends to move toward unmitigated monthly and weekly highs and lows before reversing. When a HTF level aligns with a liquidity zone or EQH/EQL cluster, the confluence strengthens the case for a sweep at that level. The dashboard shows the nearest HTF level above and below current price so you can read the closest target without examining every line on the chart. 7. Dynamic trendlines 7.1 How they form The trendline engine scans historical pivot highs and lows and finds the best-fit diagonal line across multiple touch points. A valid trendline requires at least two confirmed touches with minimal deviation, a score that weighs touch count, recency, tightness of touches, and span. The highest-scoring line for both support and resistance is drawn automatically every bar. Volume accumulates at each confirmed touch point. The label at the end of the line shows the total accumulated volume across all touches — the more volume that has interacted with the trendline, the more significant it is as a structural level. A channel fill renders between the support and resistance lines and changes color based on whether price is in the upper or lower half of the channel. 7.2 Settings Pivot length controls detection sensitivity. Lookback bars limits how far back the engine searches. ATR length controls the volatility smoothing used for touch tolerance. Max violations allows lines to remain valid after a small number of wick pierces. Touch tolerance and max distance filter noise. Extend bars projects the lines forward. 7.3 In practice A trendline with high accumulated volume and multiple tight touches is a strong structural level. When price approaches it from inside the channel, it is approaching a level where multiple institutional interactions have occurred. The volume label tells you how much. A break and retest of such a line — particularly with a sweep marker — is a high-quality location for a trade idea. 8. Supply and demand zones 8.1 How they form Supply and demand zones are identified using structural pivot points. When a new swing high forms, a supply zone is created at that level. When a new swing low forms, a demand zone is created. Zones are sized using an ATR-based width multiplier. An overlap filter prevents duplicate zones from stacking in the same price area. When price breaks through a zone boundary, the zone converts to a BOS line — a thin horizontal marker showing where market structure was broken. This mirrors the SMC (smart money concepts) approach where a broken supply zone confirms bullish structure, and a broken demand zone confirms bearish structure. 8.2 Settings Swing length controls how many bars are required on each side of a pivot for zone formation. Zone width scales the height of each box relative to ATR. The midline (POI) can be toggled to show the point of interest at the center of each zone. History to keep limits the total number of visible zones. HH/LH/HL/LL labels mark each swing point with its structural context. BOS color is configurable separately from zone colors. 8.3 In practice Supply and demand zones show you where price left an imbalance after a structural break. When a demand zone holds and price bounces from it, the zone remains valid. When price breaks through it, the BOS line marks where that structure was invalidated. These zones work best in combination with the liquidity zone engine — when both a liquidity zone and a demand zone overlap in the same price area, the confluence raises the probability of a significant reaction. Note on terminology: liquidity zones and supply/demand zones are different concepts. Liquidity zones mark where stop orders are likely to be resting based on pivot volume and probability scoring. Supply and demand zones mark structural imbalances where price left quickly. Both can occur at the same level, but they represent different phenomena. 9. Weekend gap 9.1 How it works The weekend gap engine records the last confirmed Friday close price and tracks whether price returns to fill that level during the following weekend and early week. On assets that trade continuously (crypto, 24/7 markets), the gap fill tracks whether price has revisited the Friday close since the weekend began. The Friday close is drawn as a horizontal reference line extending forward into the week. The gap fill zone renders between the Friday close and price during the relevant window. A bullish gap (price above Friday close) renders in green. A bearish gap (price below Friday close) renders in red. When the gap is filled, it clears automatically. 9.2 Settings Line style, width, and color are configurable. Extend days controls how far the Friday close line remains visible. Bull and bear gap colors are independently adjustable. 9.3 In practice The Friday close acts as a liquidity magnet for early week price action. Markets frequently return to fill the weekend gap before continuing in the dominant direction. The dashboard shows the gap status (open, percentage, or filled) so you can monitor it without keeping the line visible on all timeframes. On CME futures charts, the gap window is literal — the market was closed and the gap in data is visible. On crypto charts, the market was open but institutional behavior around the weekly close creates the same magnetic effect. 10. Liquidity voids 10.1 How they form A liquidity void (also called a fair value gap or imbalance) forms when price moves quickly in one direction across three consecutive candles, leaving a gap between the wick of the first candle and the wick of the third candle. No trading occurred in that gap area. Price tends to return to fill these zones as the market seeks balance. The void is rendered as a gradient of 13 layers. Each layer fills individually as price touches it, changing to the filled color. This gives a precise view of how much of the void has been mitigated and how much remains unvisited. A volume label shows the total volume from the bars that created the void. 10.2 Settings Mode controls whether all historical voids are shown or only the most recent N bars. Threshold (ATR×) sets the minimum gap size relative to ATR(144) — smaller values detect more voids, larger values filter to only significant imbalances. Bullish and bearish colors are independently configurable. The filled void color can be adjusted or filled voids can be removed entirely by toggling the show filled setting. 10.3 In practice Unfilled voids below price are areas where no transactions occurred during an upward move. They act as potential support and pullback targets. Unfilled voids above price are areas where no transactions occurred during a downward move. They act as potential resistance and rally targets. When a void aligns with a liquidity zone or HTF level, the overlap represents an area with both structural significance and a gap to fill. The volume label on each void gives you a sense of how much liquidity was consumed when the void was created — larger voids on higher volume represent more significant imbalances. 11. RSI divergence 11.1 How it works RSI divergence occurs when price and RSI move in opposite directions at swing points. A bullish divergence forms when price makes a lower low while RSI makes a higher low — momentum is increasing even though price is still falling, which often precedes a reversal upward. A bearish divergence forms when price makes a higher high while RSI makes a lower high — momentum is weakening even though price is still rising, which often precedes a reversal downward. The engine detects these events mechanically using pivot-based RSI analysis. When a divergence is confirmed, a box is drawn directly on the price chart spanning all candles between the two pivot points. Circle markers appear at each pivot on the price candle. This keeps the divergence signal on the chart where the price action is, rather than requiring a separate RSI pane below. Candle coloring reflects RSI momentum continuously. When RSI is above 50 and below the overbought level, candles are colored green — the gradient becomes more intense as RSI approaches the overbought threshold. The closer RSI is to overbought, the stronger the green. When RSI crosses the overbought level, coloring stops entirely — momentum is at an extreme and the gradient no longer adds information. The same logic applies in reverse below 50. Candles are colored red with increasing intensity as RSI approaches the oversold level. When RSI crosses below the oversold threshold, coloring stops. This means the gradient is always telling you how much room is left in the current momentum move — fully colored means RSI is just above 50 with a long runway ahead, faded means RSI is approaching an extreme. When the color disappears, the move is at full extension. An optional trailing stop activates after a divergence is confirmed by an RSI 50 crossover. For a bullish divergence, the stop activates when RSI crosses back above 50 and trails below price using ATR distance. It closes when price breaks the stop level or RSI reaches the overbought threshold. For a bearish divergence, the stop activates on an RSI cross below 50 and trails above price until price breaks through or RSI reaches oversold. Note: if the RSI divergence engine is disabled while a trailing stop is active, the stop line will disappear immediately without triggering a close. Do not disable the engine mid-trade while relying on the trailing stop as an active risk tool. 11.2 Settings RSI length — period for the RSI calculation. Default 14. Sensitivity — controls the pivot detection window. High detects more divergences using smaller pivots. Medium is the default. Low requires larger structural pivots and produces fewer but stronger signals. Show bullish / show bearish — each direction can be toggled independently so you only see what is relevant to your current bias. Bullish color / bearish color — the color used for the divergence box, circle markers, candle gradient, and trailing stop line. RSI candle coloring — toggle the gradient candle coloring on or off without affecting divergence detection. Overbought level — RSI level at which candle coloring stops on the upside. Default 70. Raise this to 80 for assets that tend to stay overbought for extended periods. Oversold level — RSI level at which candle coloring stops on the downside. Default 30. Raise this to 20 for assets that tend to stay oversold for extended periods. Trailing stop — toggle the trailing stop line on or off independently. ATR length / ATR multiplier — control the sensitivity of the trailing stop. A higher multiplier gives the stop more room and reduces premature exits on volatile assets. 11.3 In practice Use the divergence engine as a momentum context layer on top of the liquidity engines. A bullish divergence forming at an unmitigated liquidity zone or demand zone adds significant weight to the expectation of a reversal. A bearish divergence forming just below a major HTF level or supply zone suggests the move upward may be losing momentum before reaching that target. The dashboard row shows the current divergence state — none, bullish, or bearish — so you can monitor it without inspecting the chart. The candle gradient is the most immediately useful visual element. Watch for candles that are deeply colored — RSI has momentum but has not yet reached an extreme. When the gradient begins fading, RSI is extending. When it disappears entirely, RSI has crossed the overbought or oversold threshold and the move is at full extension. This is often where divergence begins to form on the next cycle. For overbought and oversold levels: on assets like BTC or ETH that can sustain strong trends, consider raising the overbought level to 75 or 80 and lowering the oversold level to 20 or 25. This prevents the coloring from stopping too early during genuine momentum moves. On more volatile altcoins where RSI whipsaws frequently around the extremes, the default 70/30 setting works well. 12. Dashboard The dashboard displays a live summary of all active engine data in one panel. It updates every bar. Rows shown: Header — indicator name and timeframe label. Trend — current direction from the trend engine: bull, bear, or ranging. Liq zones — count of active BSL and SSL zones in view. Nearest BSL — closest buy side liquidity level above current price. Nearest SSL — closest sell side liquidity level below current price. Top zone — highest probability unmitigated zone and its score. Safe SL — current safe stop level from the sweep detection engine. ATR (14) — current ATR value for context. HTF — section divider for higher timeframe levels. HTF above — nearest higher timeframe level above price. HTF below — nearest higher timeframe level below price. Market — section divider for market context rows. Gap — weekend gap status: off, open (direction and percentage), or filled. TL dist — distance from the nearest active trendline in ATR multiples. BOS/CHoCH — whether the supply/demand structure engine is active. EQH/EQL — count of active equal high and equal low zones. Engines — total number of active engines. Divergence — current RSI divergence state: none, bullish, or bearish. Anonycryptous — version reference. Dashboard position and text size are configurable. 13. Settings overview Liquidity zones - Enable/disable master toggle - Pivot left and right bars - Volume filter threshold - Dynamic zone width - Show fresh only - Show swept zones - Swept zone transparency - Max zones - Bull and bear zone colors - Midline toggle and color - Swept zone circle marker toggle, colors, and size Equal highs and equal lows - Enable/disable master toggle - Pivot lookback length - Tolerance (ATR×) - Minimum age - Removal mode (wick, body, body×2) - EQH and EQL zone colors - Show volume label - Show accumulated sweep volume Trend engine - Enable/disable master toggle - Trend band length - Bull and bear band colors - Show major/minor sweep volume labels - Major sweep normalized volume threshold Sweep detection - Enable/disable master toggle - Swing lookback - Minimum wick ATR multiple - Minimum rejection percentage - EMA filter toggle, length, and timeframe - Cooldown bars - Major sweep normalized volume threshold - Volume filter toggle - Bull and bear colors - Marker size Safe stop line - Line style, color, and extension bars - Glow toggle - Auto-remove after N bars HTF liquidity levels - Enable/disable master toggle - Individual toggles for monthly, weekly, daily, previous day, 4H, P4H, 1H, P1H - Line style, width, and color - Extend bars - Show liquidity label Dynamic trendlines - Enable/disable master toggle - Pivot length - Lookback bars - ATR length - Max violations - Touch tolerance (ATR×) - Max slope (degrees) - Max distance (ATR×) - Extend bars - Show channel fill - Show volume on touch - Support and resistance colors - Line width and style Supply and demand zones - Enable/disable (controls zones and BOS simultaneously) - Swing length - Zone width (ATR×0.1) - History to keep - Supply and demand colors and outlines independently - Show midline (POI) - Midline color - Show HH/LH/HL/LL labels - BOS color and line width Weekend gap - Enable/disable master toggle - Show gap fill and show Friday close line independently - Extend line (days) - Bull and bear gap colors - Friday close line color, width, and style Liquidity voids - Enable/disable master toggle - Mode (present / historical) - Lookback bars (for present mode) - Void threshold (ATR×) - Bullish and bearish void colors - Show filled voids - Filled void color - Show volume label RSI divergence - Enable/disable master toggle - RSI length - Sensitivity (high, medium, low) - Show bullish and bearish independently - Bullish and bearish colors - RSI candle coloring toggle - Overbought level (default 70) - Oversold level (default 30) - Trailing stop toggle - ATR length and multiplier for trailing stop Dashboard - Enable/disable - Position - Size 14. How to use The indicator does not prescribe a method. It provides context. How you use that context depends on your own approach. The following describes the logic behind combining the engines effectively. Start with bias. The dashboard trend row shows the current directional bias. The nearest HTF levels above and below give you the macro targets. If the weekly high is the nearest HTF above price, the market may be running toward that level before reversing. Identify the nearest liquidity. The nearest BSL and SSL rows in the dashboard show the closest unmitigated zones. These are the most likely near-term targets for price. A high-probability zone score adds weight to the expectation that price will visit that level. Look for confluence. When a liquidity zone, an EQH/EQL cluster, an HTF level, and a void all align at the same price area, the confluence is significant. Price has multiple reasons to move to that location. Once it arrives, multiple forms of liquidity can be consumed in one move. Read the sweep markers. When a sweep triangle fires, liquidity was taken. The safe stop line shows the consumed level. If the sweep occurred at a high-probability zone with volume confirmation, the conditions for a reversal are in place. The triangle type (solid for major, hollow for minor) tells you how significant the volume event was. Use the gap. In the early part of the week, the weekend gap status is visible on the dashboard. If the gap is open and price is below the Friday close, price has a tendency to return to that level. This can serve as a short-term directional bias early in the week. Check the voids. Unfilled voids represent areas the market has not yet returned to. If price is approaching an unfilled void from outside, it is approaching a zone of imbalance that the market may seek to fill. A void aligned with a swept zone or an EQH/EQL cluster adds structural weight to the expected reaction. 15. Notes - Liquidity Matrix is a context indicator. It maps where liquidity is, where it has been taken, and what levels remain unmitigated. It does not generate entry signals. - All volume values are in the base currency of the trading pair. BTC/USDT shows volume in BTC. SOL/USDT shows volume in SOL. Multiply by price to approximate USD value. - The sweep detection engine uses swing-based pivots. The supply/demand BOS engine uses a separate pivot. These are independent systems with independent lookback settings. - On lower timeframes, more engines running simultaneously increases computation. If the indicator is slow to load, reduce the number of active engines or lower lookback values. - HTF levels require the chart timeframe to be lower than the HTF being referenced. A daily chart will not show daily HTF levels accurately. - The dynamic trendline engine runs every bar. On very long chart histories with tight tolerances, this may produce slightly longer load times. - The liquidity void threshold is relative to ATR(144). On assets with low average volatility, the default threshold may produce very few voids. Reduce the threshold to increase sensitivity. - Weekend gap tracking works on all assets. On CME futures, the gap is a literal data gap. On crypto and 24/7 assets, the gap reflects the Friday close level as an institutional reference. 16. Disclaimer This indicator by Anonycryptous is provided for educational and informational purposes only. All outputs are based on historical price and volume data. Past behavior does not guarantee future results. Trading involves substantial risk of loss. Use at your own discretion.
Penunjuk Pine Script®
oleh Anonycryptous
RSI BB Wonagi pro📊 RSI BB Wonagi Pro – Description RSI BB Wonagi Pro is an advanced technical indicator that applies Bollinger Bands directly to RSI values, rather than price. This approach allows traders to analyze the volatility, expansion, contraction, and reversion behavior of RSI itself, offering a deeper layer of market insight beyond traditional RSI interpretation. Instead of relying solely on static RSI levels such as 70 (overbought) and 30 (oversold), this indicator dynamically evaluates how far RSI deviates from its normal range and how it behaves relative to its own statistical boundaries. 🔍 Core Concept The indicator calculates RSI and optionally smooths it using various moving average methods (EMA, SMA, RMA, WMA). A Bollinger Band is then constructed based on the smoothed RSI, forming: A central basis line (RSI mean) An upper band (RSI overextension zone) A lower band (RSI overshoot zone) This transforms RSI into a volatility-aware oscillator, allowing traders to identify not just levels, but contextual extremes and momentum shifts. ⚙️ Key Features 1. RSI-Based Bollinger Bands Unlike standard Bollinger Bands applied to price, this indicator builds bands around RSI values. This enables detection of statistical extremes within RSI behavior, providing a more adaptive overbought/oversold framework. 2. Re-entry Signals (Mean Reversion Insight) When RSI moves outside the Bollinger Bands and then returns back inside: A yellow diamond above signals re-entry from the upper band A yellow diamond below signals re-entry from the lower band These events often indicate momentum exhaustion or potential reversal zones. 3. Narrow Band Detection (Volatility Compression) The indicator highlights periods when the RSI Bollinger Band width contracts significantly. A background color appears during these phases This represents low volatility / compression zones, often preceding strong market moves 4. Midline (50-Level) Momentum Signals The Bollinger Band basis (center line) crossing the RSI mid-level (50) provides directional bias: Crossing above 50 → Bullish momentum shift Crossing below 50 → Bearish momentum shift This acts as a trend confirmation layer within RSI structure. 5. Smoothed RSI Option Users can apply smoothing to RSI using multiple methods to reduce noise and enhance signal clarity. This helps in filtering out minor fluctuations and focusing on meaningful moves. 6. Built-in Alerts The indicator includes alert conditions for: Buy signal (basis crossing above 50) Sell signal (basis crossing below 50) Upper band re-entry Lower band re-entry Narrow volatility zone These alerts enable automation and real-time monitoring. 🧠 How to Interpret Traditional RSI only shows static levels. RSI BB Wonagi Pro adds structure and context to RSI behavior. With this indicator, traders can: Identify when RSI is statistically overextended Detect mean reversion opportunities Spot volatility compression before expansion Understand momentum shifts around the midline Filter signals using dynamic boundaries instead of fixed thresholds 💡 In Simple Terms This is not just an RSI. It is an RSI that understands: When it moved too far When it is coming back When it is preparing for a breakout And when the market is shifting direction 🚀 Summary RSI BB Wonagi Pro transforms the traditional RSI into a dynamic, volatility-based analytical tool. By combining RSI with Bollinger Band logic, it provides traders with a more refined way to interpret momentum, extremes, and market conditions.
Penunjuk Pine Script®
oleh WonagiTV
Impulse Regime Engine [JOAT]Impulse Regime Engine Introduction Impulse Regime Engine is a hybrid breakout-and-trend indicator designed to detect when participation expands, when that expansion compresses into a tradeable box, and when price finally resolves that box with directional intent. It combines a volume regime engine with an RSI-projected price trend framework, creating a clean overlay built for timing impulsive releases without sacrificing directional context. This indicator is especially useful for traders who like breakout structures but do not want to trade every range break blindly. The regime box defines the event. The projected trend framework defines the context. Why This Indicator Exists Participation Regime Classification: Distinguishes low-quality price movement from meaningful volume expansion Lifecycle-Based Box Engine: Separates the setup into building, armed, and resolved states Projected Trend Overlay: Maps RSI into price space for contextual trend direction Strength-Based Candle Coloring: Visualizes conviction without overloading the chart Active Risk Map: Adds optional stop and target staging after valid breaks Core Components Explained 1. Volume Regime Engine volRatio = shortVolMA / longVolMA Volume is classified into Low, Normal, High, and Extreme states by comparing short-term participation to a longer-term baseline. Only elevated regimes are allowed to build a valid impulse box. 2. Regime Box Lifecycle Building: While elevated volume persists, the box expands to contain the active burst Armed: Once the burst cools, the box freezes and waits for release Resolved: A confirmed close beyond the boundary triggers the breakout event and resets the cycle The script now includes a cooldown between resolved boxes so repeated high-volume churn does not keep repainting fresh structures on every minor burst. 3. RSI Projection Framework projected = priceLow + smoothedRsi * priceRange / 100.0 avgLine = ta.ema(projected, smoothLen) Instead of reading RSI only as a sub-pane oscillator, the script converts RSI into projected price space. This produces a trend reference line directly on the chart. 4. Dynamic Tolerance Bands tolerance = avgBody * toleranceMultiplier marginUp = avgLine + tolerance marginDn = avgLine - tolerance Price above the upper band confirms bullish projected trend. Price below the lower band confirms bearish projected trend. This acts like a directional bias filter around the projection basis. 5. Breakout Risk Framework When price resolves the armed box, the script can draw one stop and three profit levels using either ATR-derived or percentage-derived distance. The lines auto-expire so old trade maps do not crowd the chart. Visual Elements Regime Box: Semi-transparent box during build and armed phases Projection Basis: Gold-accent projected trend line Tolerance Bands: Bull and bear projection boundaries Gradient Candles: Optional candle coloring by directional strength Breakout Markers: Compact IRE triangles on confirmed release TP/SL Lines: Optional risk staging while the active breakout remains valid Dashboard: Volume regime, ratio, bias, box state, signal state, RSI, and strength Input Parameters Regime Engine: Short / Long Volume MA Low / Normal / High thresholds Max build bars Max armed bars New box cooldown bars Trend Projection: RSI length and smoothing Projection range bars Projection EMA Tolerance multiplier Strength lookback Risk Framework: ATR period ATR stop multiplier TP1 / TP2 / TP3 risk-reward ratios TP/SL maximum life How to Use This Indicator Step 1: Wait for elevated participation to build the impulse box. Step 2: Let the box transition into the armed state. Step 3: Read whether projected trend bias agrees with the likely breakout direction. Step 4: Use confirmed breaks, not intrabar pokes, as the actual event trigger. Step 5: Manage the trade against the active risk map or your own execution rules. Best Practices Use on instruments with reliable participation data Prefer breakouts aligned with the projected trend state Treat extreme volume bursts as high-opportunity but also high-volatility events Use the cooldown to avoid overreacting in noisy compression cycles Disable extra visuals if you want a cleaner execution chart Indicator Limitations Volume regime logic depends on the quality of the feed Not every armed box will produce a sustained move Projected RSI trend is a contextual guide, not a guarantee Breakouts can fail or reverse quickly in low liquidity Repeated tests of the same area reduce signal quality Technical Implementation Built in Pine Script v6 using: Short-vs-long volume regime classification Stateful box lifecycle logic RSI-to-price projection Body-based tolerance bands Strength-gradient candle coloring Optional ATR or percent risk mapping Confirmed-bar breakout and trend-shift alerts Originality Statement This indicator is original in the way it combines regime participation, lifecycle breakout structure, and projected momentum context into one overlay. Its edge is not just detecting expansion, but framing when expansion is worth respecting. Disclaimer This indicator is provided for educational and informational purposes only. It is not financial advice. Breakout trading involves risk, including false breaks and fast reversals. Always manage risk carefully and confirm signals with your own process. -Made with passion by officialjackofalltrades
Penunjuk Pine Script®
oleh officialjackofalltrades
Velox Structure Ribbon [JOAT]Velox Structure Ribbon Introduction Velox Structure Ribbon (VSR) is an open-source multi-band trend structure ribbon that uses a volatility-normalized, dynamically-spaced band system to visualize how far price has extended from its trend baseline and in which direction. The ribbon is anchored by a dual SMEMA core — a fast and slow double-smoothed moving average — and radiates six equidistant bands above and below the baseline, with spacing determined by the smoothed average candle range. Each band that price has penetrated adds one point to a 0-3 bull or bear structure score. A 0-100 composite trend strength score combines band penetration with RSI momentum. Volume confirmation and RSI filters are available to sharpen signal quality. The problem VSR solves is that standard envelopes and Bollinger Bands use fixed or volatility-scaled offsets that can cluster bands too tightly in low-volatility environments and spread them too far in high-volatility ones. VSR normalizes band spacing using the market's own smoothed candle range, meaning band width automatically contracts in quiet markets and expands in active ones. This keeps the structure score meaningful across all conditions: three bands penetrated in a quiet market represents the same degree of extension relative to current volatility as three bands penetrated in a volatile market. Core Concepts 1. SMEMA Ribbon Core The ribbon center uses two SMEMA lines — slow (full period, default 20) and fast (half period). The slow SMEMA defines trend direction: sloping upward means the trend is bullish, downward means bearish. The fill between fast and slow creates a visual ribbon that contracts during consolidation and expands during trends: float smemaSlow = smema(close, smemaLen) float smemaFast = smema(close, math.max(int(smemaLen / 2), 3)) bool trendUp = smemaSlow > smemaSlow bool trendDn = smemaSlow < smemaSlow 2. Volatility-Normalized Band Spacing The step unit for band placement is SMEMA applied to the high-low range over a long smoothing period (default 100 bars). This produces an adaptive measure of the average candle body size. Each of the six bands is placed at integer multiples of this step above and below the slow SMEMA: float step = smema(high - low, stepSmooth) float up1 = smemaSlow + step * 1 float up2 = smemaSlow + step * 2 float up3 = smemaSlow + step * 3 Because the step automatically adjusts to market volatility, the bands always represent meaningful structural extensions rather than arbitrary percentage offsets. 3. Bull and Bear Structure Scoring Each bar, the indicator counts how many upper bands price has broken through (bullish penetration) and how many lower bands (bearish penetration). Each penetrated band adds one point to the respective score: int bullStr = (above1 ? 1 : 0) + (above2 ? 1 : 0) + (above3 ? 1 : 0) int bearStr = (below1 ? 1 : 0) + (below2 ? 1 : 0) + (below3 ? 1 : 0) A score of 0 means price is between the baseline and first band — neutral zone. Score of 1 means first structural extension. Score of 3 means full breakout beyond all three bands in that direction. 4. Composite Trend Strength Score (0-100) The strength score combines two inputs: the band penetration score converted to a 0-50 scale (each band = 16.7 points) and the RSI deviation from 50 on a 0-50 scale. The combination rewards moves that have both structural extension (price has pushed through multiple bands) and momentum confirmation (RSI is moving away from neutral): float bandScore = math.min(float(math.max(bullStr, bearStr)) * 16.7, 50.0) float rsiScore = math.min(math.abs(rsiVal - 50.0), 50.0) int strScore = int(math.min(bandScore + rsiScore, 100.0)) 5. Distance-Based Band Coloring Each band receives a gradient color whose intensity scales with how far price is from that band relative to its historical range. Bands that price has recently broken through or is pressing against are rendered more vividly. Bands far from price are nearly transparent. This creates a visual heat-map effect showing where structural tension exists: bandColor(float src, color col) => float dist = math.abs(close - src) float pctNorm = ta.percentile_linear_interpolation(dist, 400, 100) float colSize = pctNorm > 0 ? dist / pctNorm : 0.0 showBands ? color.from_gradient(colSize, 0, 0.5, color(na), col) : color(na) Features Six-Band Structure Grid: Three bands above and three below the slow SMEMA baseline, dynamically spaced by the smoothed candle range Dual SMEMA Core Ribbon: Fast and slow baseline with gradient fill, colored by trend direction Trend Direction Diamond: A small diamond marker on the baseline at every trend flip (when the slow SMEMA changes slope direction) Bull / Bear Structure Score (0-3): Real-time count of penetrated upper or lower bands displayed in signal labels and the dashboard Composite Strength Score (0-100): Combined band penetration and RSI momentum score with Strong/Moderate/Weak label RSI Momentum Filter: Optional filter requiring RSI alignment before a signal is confirmed (configurable threshold, default 52) Volume Filter: Optional filter requiring above-average volume (configurable multiplier, default 1.1x the 20-bar SMA). Auto-disables on volume-free instruments Signal Labels: Small numeric labels at bull and bear signal bars showing the structure score (1, 2, or 3) Strength Bar (Bottom Right): A visual bar table showing filled cells proportional to the current bull or bear structure score Candle Coloring: Bar colors reflect trend direction at reduced opacity 9-Row Dashboard (Top Right): Trend direction, last signal and bars-since count, strength score with label, bull and bear band counts, RSI value, timeframe, and version Watermark: JackOfAllTrades signature at chart center-bottom Alerts: Bull signal, bear signal, and trend-flip alertconditions with optional JSON webhook format Input Parameters Ribbon Engine: SMEMA Length: Core period for the slow baseline (default: 20). Fast = L/2 Step Smoothing: SMA period for the candle-range volatility step (default: 100) Filters: RSI Length: Momentum confirmation period (default: 14) RSI Threshold: Minimum RSI for bull signal confirmation (default: 52). Bear mirror = 100 - threshold Volume Filter: Enable/disable volume confirmation (default: off) Volume Multiplier: Required volume multiple of the 20-bar SMA (default: 1.1) Visuals / Dashboard: Theme: Auto, Dark, or Light Show Distance Bands: Toggle the six structural bands Show Core Ribbon: Toggle the fast/slow SMEMA ribbon and fill Show Signals: Toggle the numeric signal labels Show Strength Bar: Toggle the bottom-right score visualization Show Dashboard: Toggle the 9-row information panel Color Palette: Bull, Bear, and Neutral colors are individually customizable How to Use This Indicator Step 1: Read Trend Direction from the Ribbon When the ribbon is green and sloping upward, the baseline trend is bullish. When red and sloping downward, bearish. A flat ribbon in neutral color indicates a non-trending market. Step 2: Use Structure Score for Entry Timing A bull signal fires when price is above the first upper band (score 1+) and the trend slope is upward with RSI and volume confirmation. A score of 2 or 3 indicates deeper structural extension — potentially overextended for entry, better for trailing a position. Step 3: Watch for Pullbacks to the Ribbon After a bull signal, price often pulls back toward the ribbon (slow SMEMA) before continuing. Entries from the ribbon during an active bull structure are higher-probability than chasing at the outer bands. Step 4: Scale Position with Strength Score A strength score above 70 (labeled Strong) indicates both structural extension and momentum alignment — use for higher conviction. Below 40 (Weak) may indicate a fading move or early-stage structure not worth full position sizing. Indicator Limitations The warmup period (SMEMA length x3 or step smoothing + 50, whichever is larger) means the indicator is inactive for the first several dozen bars on any chart The band spacing adapts to the smoothed candle range with a 100-bar lookback. On instruments with sharp volatility regime changes, the bands may lag behind the new volatility environment for many bars The volume filter is automatically disabled when volume data is unavailable (e.g., indices, some forex pairs). In those cases, volume confirmation is effectively always true regardless of the toggle setting Signal labels fire on every bull or bear structure bar — this can be frequent in strongly trending markets. The labels are informational, not entry triggers, and users should apply their own discretion for entry timing Originality Statement VSR is original in its use of the SMEMA-smoothed candle range as the band spacing unit. This indicator is published because: The volatility-normalized step unit (SMEMA of high-low range) is a unique approach to band spacing that differs from standard ATR envelopes, Bollinger Bands (which use standard deviation), and Keltner Channels (which use raw ATR). The SMEMA smoothing produces a more stable, noise-resistant step unit than raw ATR The 0-3 integer band-penetration scoring is a discrete structural measure that complements continuous oscillators. It quantifies how far price has extended structurally rather than how fast it has moved The distance-based gradient coloring using percentile normalization creates an adaptive visual heat-map — the same visual logic is computationally novel within the band-coloring approach The composite strength score combining band penetration with RSI deviation creates a measure that rewards both structural extension and momentum alignment simultaneously Disclaimer This indicator is provided for educational and informational purposes only. It is not financial advice or a recommendation to buy or sell any financial instrument. Trading involves substantial risk of loss. Band structure scores are based on historical price position relative to smoothed averages and do not predict future price movement. A score of 3 (maximum bullish extension) can increase further or reverse immediately. Always use proper risk management. The author is not responsible for any trading losses resulting from the use of this indicator. -Made with passion by jackofalltrades
Penunjuk Pine Script®
oleh officialjackofalltrades
JOAT Institutional Convergence [JOAT]JOAT Institutional Convergence Introduction The JOAT Institutional Convergence strategy is a systematic, rules-based trading framework that unifies the logic from all five JOAT indicators into a single coherent entry and exit engine. Each indicator contributes a specific filter layer: the Volumetric Structure Engine provides directional market structure bias, the Adaptive Spectral Bands Hann ribbon provides the primary entry trigger, the Institutional Session Profiler contributes optional session timing, the Imbalance Zone Classifier contributes optional FVG proximity filtering, and the Fractal Liquidity Map contributes fractal-anchored stop placement. No layer is redundant — each addresses a different dimension of trade selection. The core problem this solves: most TradingView strategies use a single indicator as both entry and exit signal, producing over-fitting to one methodology. This strategy uses five independent measurement systems simultaneously. An entry only fires when multiple independent conditions converge — structure, momentum, regime, and optionally session and imbalance context. The result is a strategy that takes trades for quantifiable, multi-factor reasons, not because a single line crossed. Core Concepts 1. Entry Logic — Hann Ribbon Crossover Primary The primary entry trigger is the Hann FIR ribbon crossover — when the fastest layer (h0) crosses above the second layer (h1), a potential long entry is flagged. This is the earliest mathematically-grounded signal that momentum is shifting: bool cross_bull = ta.crossover(h0, h1) bool cross_bear = ta.crossunder(h0, h1) bool long_sig = (cross_bull or (bos_bull_sig and h0 > h2)) and struct_trend >= 0 and adx >= i_adx_min and adx <= i_adx_max and sess_ok and fvg_ok The crossover fires on the bar where momentum begins to shift — not after full ribbon alignment is confirmed. This is intentional: waiting for full alignment reduces trade count significantly and enters late. The structural trend filter (struct_trend >= 0) ensures the crossover is not taken against a confirmed downtrend. 2. Structure Filter — VSE Swing Classification Market structure is classified using the same non-repainting swing detection as the Volumetric Structure Engine. Higher highs and higher lows (struct_trend = 1) are bullish; lower highs and lower lows (struct_trend = -1) are bearish; a mixed state (struct_trend = 0) is neutral. The strategy allows longs in bullish or neutral structure (>= 0) and shorts in bearish or neutral structure (<= 0): bool new_sh = high == ta.highest(high, i_sw_len) and high < ta.highest(high, i_sw_len) bool new_sl = low == ta.lowest (low, i_sw_len) and low > ta.lowest (low, i_sw_len) This prevents the ribbon crossover from triggering entries during confirmed counter-trend structure without requiring perfect alignment. 3. Regime Filter — ADX Gating ADX gates entries in both directions. Below the minimum ADX, the market has no directional momentum — ribbon crossovers in flat, dead markets produce noise. Above the maximum ADX, the market is over-extended and new entries chase moves that are already mature: float adx_val = ta.rma(math.abs(dmi_p - dmi_m) / (dmi_p + dmi_m + 0.001) * 100, i_adx_len) bool adx_ok = adx_val >= i_adx_min and adx_val <= i_adx_max Default range: 8–60. This wide range accommodates crypto and forex markets that trend aggressively for extended periods (ADX 40–60) as well as early-stage trends (ADX 8–15). 4. Position Sizing — Percentage Risk per Trade Position sizing is calculated dynamically based on the user's equity risk percentage and the distance to the stop-loss level: float sl_dist = math.abs(close - sl_price) float qty = sl_dist > 0 ? (strategy.equity * i_risk_pct / 100.0) / sl_dist : 1.0 strategy.entry("Long", strategy.long, qty = qty) This ensures every trade risks the same percentage of equity regardless of market volatility — a wider stop reduces size, a tighter stop increases size. The default is 1% risk per trade. 5. Stop-Loss Placement — Fractal Extreme + ATR Buffer The stop-loss is placed beyond the most recent 20-bar fractal extreme in the direction of the trade, plus one ATR buffer. This anchors the stop to genuine structural pivots rather than arbitrary fixed-pip distances: float sl_long = ta.lowest(low, 20) - atr_14 * i_sl_atr_buf float sl_short = ta.highest(high, 20) + atr_14 * i_sl_atr_buf Features Five-Layer Entry Filter: Structure + Ribbon + Regime + Session (optional) + FVG proximity (optional) Hann FIR Ribbon Crossover: Primary entry trigger — earliest mathematically-valid momentum signal BOS-Armed Entries: Break of Structure signals additionally arm entries for up to 30 bars Percentage Risk Sizing: Dynamic position size calculated from equity risk % and SL distance Fractal-Anchored Stop Loss: Stop at 20-bar fractal extreme + ATR buffer Fixed R:R Take Profit: Configurable reward-to-risk ratio for TP placement Trailing Stop: Built-in trail_offset activates immediately from entry, protecting profits Session Filter (optional): Trade only during Asia, London, and/or New York sessions. Off by default for 24h markets. FVG Proximity Filter (optional): Require entry to be near an active imbalance zone. Off by default for maximum trade count. Performance Dashboard: Displays trade count, win rate, average R, last trade result, and active filter states Realistic Simulation: 2-tick slippage + 0.05% commission built into all backtests Input Parameters Structure (VSE): Swing Length: Lookback for swing high/low detection (default: 20) Ribbon Filter (ASB): Hann Base Length: Core FIR filter period (default: 20) Ribbon Spacing: Gap between ribbon layers (default: 3) Regime Filter: ADX Length: Period for ADX calculation (default: 14) Min ADX for Entry: Minimum ADX to allow entries (default: 8). Lower = more trades. Raise to filter ranging markets. Max ADX for Entry: Maximum ADX to allow entries (default: 60). Lower = skip over-extended moves. Session Filter (ISP): Enable Session Filter: Gate entries by session time (default: off — recommended for crypto and indices) Trade Asia / London / NY: Toggle per-session entry permission Imbalance Filter (IZC): Require Near FVG Zone: Entry must be within ATR proximity of an active imbalance (default: off) FVG Proximity (x ATR): Distance threshold for FVG proximity check (default: 1.5) Risk Management: Risk Per Trade (%): Equity percentage risked per trade (default: 1.0) Reward:Risk Ratio: Take profit as a multiple of the SL distance (default: 2.0) SL ATR Buffer: ATR multiple added beyond fractal extreme for stop (default: 0.5) Trail Offset (ATR): Trail stop distance from price (default: 1.5) BOS Armed Bars: How many bars a BOS signal remains active for entry (default: 30) How to Use This Strategy Step 1: Select Your Market and Timeframe Start on the 1-hour chart. The strategy is calibrated for 1H on crypto, forex majors, and equity indices with default settings. Shorter timeframes (15m) can increase trade count further but require tighter ADX filtering to avoid noise. Step 2: Run the Backtest with Defaults With all optional filters off (session and FVG disabled), the strategy trades every valid ribbon crossover that passes structure and regime. This produces the highest trade count. Review the equity curve for smoothness — you want consistent growth, not reliance on a few large winners. Step 3: Add Filters Progressively Enable the session filter to restrict to London and NY on forex pairs. Enable the FVG proximity filter to require imbalance context on entries. Each filter reduces trade count but should improve win rate if the underlying edge is present on your instrument. Step 4: Interpret the Dashboard The dashboard shows the current state of every filter layer — which ones are active and whether each condition is currently met. This is the diagnostic view: if no trades are firing, the dashboard tells you exactly which filter is blocking entries. Originality Statement This strategy is original as a unified multi-indicator convergence framework where each component is an independently published, standalone indicator. Its publication is justified because: The five-layer filter architecture uses genuinely independent measurement dimensions — market structure (price action), momentum (FIR frequency domain), trend strength (ADX), session timing, and price inefficiency (FVG) — reducing the risk of correlated signals that appear to confirm each other but measure the same thing Hann FIR crossover as the primary trigger provides a mathematically grounded entry timing signal with lower lag than EMA crossovers of equivalent period — a meaningful improvement to the timing of systematic entries Dynamic position sizing calculated from SL distance anchored to fractal extremes creates risk-normalized sizing that adapts to each trade's structural context rather than using fixed lot sizes The modular filter design allows each filter to be toggled independently, making the strategy adaptable to different asset classes (crypto, forex, equities) without code changes — session filter off for 24h markets, FVG filter off for maximum trade generation Limitations Backtesting results depend critically on the instrument, timeframe, and parameter settings. Past performance in strategy tester does not guarantee future live trading results. The 2-tick slippage and 0.05% commission defaults are approximations. Actual execution costs vary by broker, instrument, and session liquidity. High-slippage instruments (illiquid crypto, micro-cap) will perform worse than the backtest indicates. The FVG proximity filter references FVG logic computed internally. It does not import live data from the separately published Imbalance Zone Classifier indicator — it recomputes the same logic in isolation. The strategy does not incorporate news filters or earnings event exclusions. Entering positions around major economic releases (FOMC, NFP) during high-volatility events will produce results inconsistent with normal market behavior. Trailing stop and take profit interact. If price reaches the TP level before the trail stop triggers, the TP closes the trade. Users should verify via strategy properties which exit is dominant in their use case. Disclaimer This strategy is provided for educational and informational purposes only. It does not constitute financial advice or a recommendation to buy or sell any instrument. All trading involves risk of loss. Backtested strategy results are hypothetical and do not account for the psychological challenges of live trading. Past results do not guarantee future performance. Always use proper risk management and never risk more than you can afford to lose. -Made with passion by jackofalltrades
Strategi Pine Script®
oleh officialjackofalltrades
Haar Wavelet RSI [Jamallo]Author's Note This is the oscillator companion to the Haar Wavelet Range Filter. Both indicators share the same MODWT Haar wavelet foundation, creating a synergistic effect when used together — trend and momentum derived from the same mathematical decomposition of price. Introduction The Haar Wavelet RSI is a momentum oscillator that replaces the standard price-difference input of a traditional RSI with wavelet detail coefficients derived from a Maximal Overlap Discrete Wavelet Transform (MODWT) with a Haar basis. Instead of measuring bar-to-bar price change, it measures momentum at a specific frequency scale — filtering out the noise above and below that scale before the RSI calculation even begins. How It Works MODWT Haar Wavelet Decomposition The script decomposes hl2 through up to 5 wavelet levels using a shift-invariant Haar transform. At each level, the detail coefficients capture the local price delta at that specific scale — Level 1 is 2-bar momentum, Level 3 is 8-bar momentum, Level 5 is 32-bar momentum. These detail coefficients become the input to the RSI in place of raw price change, meaning the oscillator is measuring directional energy at a single isolated frequency rather than the full noisy price series. Wavelet RSI Calculation The selected detail coefficient is split into its upward and downward components, smoothed with Wilder's RMA, and fed into the standard RSI formula. The math is identical to a conventional RSI — the only difference is what it is measuring. Because the detail coefficients are already frequency-isolated, the resulting RSI is inherently cleaner than applying RSI to raw price. Adaptive Deadband Step-Hold The wavelet RSI output is then passed through an adaptive deadband filter. The threshold is self-derived from the RSI's own recent volatility — a short rolling average of absolute RSI changes — scaled by the deadband multiplier. The RSI only updates when it departs from its held value by more than this threshold. Below the threshold it holds flat. This eliminates the continuous micro-oscillation that makes standard RSI difficult to read on noisy bars, producing a stepped line that moves with conviction or not at all. Closing This is not a standard RSI with cosmetic changes. The wavelet decomposition fundamentally changes what the oscillator is measuring — momentum at a defined frequency scale rather than raw bar-to-bar noise. The decomposition level is the most important setting: lower levels suit faster timeframes and shorter momentum cycles, higher levels filter more aggressively and are better suited to swing-level momentum reads.
Penunjuk Pine Script®
oleh Jamallo22
2
Convergence Protocol [JOAT] Convergence Protocol Introduction Convergence Protocol is an open-source strategy that combines four analytical modules — structural trend, volatility regime, delta pressure, and liquidity/structure break detection — into a multi-pathway entry and exit system. The strategy generates trade signals through five independent entry mechanisms, each requiring alignment between different analytical dimensions, and manages positions with ATR-based stops, dual take-profit levels, and an optional trailing stop that activates after the first target is reached. The design rationale for combining these four modules is that each answers a different question about the market. Structure and trend analysis answers: what direction is the market likely to move? Volatility regime answers: does the market have the energy to sustain a directional move? Delta pressure answers: is volume supporting the proposed direction? Liquidity and structure break detection answers: has the market made a meaningful structural commitment that confirms directional intent? No single module alone provides a robust enough basis for a trade. Convergence across multiple modules provides a higher-quality signal set that reduces the frequency of marginal trades while maintaining enough opportunities to be practical. Strategy Properties and Backtesting Settings Default settings used for publication: Initial Capital: Default TradingView account size Position Size: 5% of equity per trade Commission: 0.04% per side (realistic for most crypto and equity platforms) Slippage: 1 tick Risk Per Trade: 5% of equity maximum (within sustainable limits) Stop Loss: 1.5x ATR from entry TP1: 1.2x risk (50% of position closed) TP2: 2.5x risk (remaining position) Trailing Stop: 1.0x ATR trailing offset, activates after TP1 hit Backtesting results will vary significantly by instrument and timeframe. This strategy is intended to be evaluated across multiple instruments and market conditions before drawing conclusions. A single backtest run does not constitute evidence of future performance. Core Modules Module 1: Structural Trend Engine The baseline uses a double-smoothed moving average (SMEMA). Swing highs and lows are tracked to classify market structure as bullish (HH+HL), bearish (LH+LL), or neutral. A 0-7 confluence score is assembled from: regime direction, structural alignment, volatility expansion, absence of squeeze, delta pressure, structure break confirmation, and liquidity sweep confirmation. Each module contributes a binary point to the score. Module 2: Volatility Regime Short-period ATR is compared to long-period ATR. A ratio above 1.05 with a rising oscillator confirms volatility expansion — the market has enough energy for directional moves. A squeeze condition (fast ATR well below slow ATR and its own moving average) signals that the market is coiling; entries are filtered or blocked depending on settings. Module 3: Delta Pressure Bar-by-bar delta (positive on bullish bars, negative on bearish bars) is smoothed into fast and slow EMAs. Their cross and relative position provide a directional bias from the volume perspective. Module 4: Liquidity and Structure A break of structure (BOS) is confirmed when price closes beyond the most recent pivot in any direction on a confirmed bar. Liquidity sweeps are detected when price wicks beyond a prior swing and closes back on the correct side. Both conditions contribute to the confluence score. Entry Mechanisms 1. Confluence Score Entry All four modules must be aligned and score at or above the minimum threshold (default: 2 of 7). This is the primary high-conviction entry. 2. Baseline Pullback Entry In an established trend (regime confirmed), when price returns to within the step band of the baseline with positive delta confirmation, a pullback entry is generated. This produces more frequent entries by adding trend-continuation trades within an established directional move. 3. Squeeze Breakout Entry When a detected squeeze condition resolves (squeeze ends) with trend and delta alignment, a breakout entry fires. This targets the expansion phase immediately following volatility compression. 4. Delta Crossover Entry When the fast delta EMA crosses above the slow delta EMA in the direction of the regime, and the market is not in a squeeze, a momentum entry is generated. 5. Sweep Reversal Entry When a liquidity sweep occurs with confirming delta pressure, a reversal entry is generated in the direction of the sweep reversal. This targets the classic sweep-and-go pattern. Exit Logic TP1: 50% of position closed at 1.2× risk. Locks in partial profit and reduces position size for the remainder of the trade TP2: Remaining 50% targets 2.5× risk with a hard stop at the original stop level Trailing Stop: After TP1 is hit, the strategy optionally converts to a trailing stop with an ATR-based offset, allowing the winning portion of the trade to capture extended moves Regime Exit: If the market regime flips against the position (bullish regime while short, or bearish regime while long), the position is closed at market. This protects against holding trades through structural regime reversals Limitations and Considerations The strategy uses OHLCV-based calculations throughout. It does not have access to tick data, order book information, or real-time execution data that institutional traders use Backtesting results are inherently optimistic due to perfect execution assumed at bar close prices. Real-world execution will differ The five entry mechanisms produce different trade frequencies. Users should evaluate each mechanism independently in backtesting before enabling all simultaneously The regime change exit can produce early exits in choppy markets where the regime briefly flips before resuming the original direction The trailing stop activation after TP1 is a fixed ATR offset from the highest/lowest price reached. It does not adapt to subsequent volatility changes during the trade The strategy is designed for trending markets. In persistent ranging environments, the confluence score-based entries will underperform because the regime module will frequently return a Ranging classification, suppressing primary entries Commission and slippage settings in the strategy Properties should be adjusted to match the actual costs on the instrument and broker being used before drawing any performance conclusions Originality Statement This strategy is original in its specific multi-pathway entry architecture and the unified 0-7 confluence scoring system that synthesizes structural, volatility, delta, and liquidity analysis into a single conviction metric. Each of the five entry pathways serves a distinct market condition: confluence entries target high-alignment setups; pullback entries target trend continuation in established moves; squeeze breakout entries target volatility expansion transitions; delta crossover entries target momentum initiation; sweep reversal entries target institutional accumulation/distribution patterns. No single existing strategy approach covers all five scenarios. The combination is justified because these five market conditions occur at different points in the market cycle, and a strategy limited to one condition type will sit idle during the other four. Disclaimer This strategy is provided for educational and informational purposes only. Past backtest results do not guarantee future performance. No backtesting result should be interpreted as evidence that this strategy will be profitable in live trading. Markets change, and conditions that produced past results may not recur. The strategy does not account for taxes, broker requirements, or psychological factors in live trading. Always use proper risk management and consult with a qualified financial professional before making any investment decisions. The author is not responsible for any losses incurred from using this strategy. -Made with passion by officialjackofalltrades
Strategi Pine Script®
oleh officialjackofalltrades
Volatility Terrain Engine [JOAT] Volatility Terrain Engine Introduction Volatility Terrain Engine is a pane-based oscillator that measures the current volatility regime using the ratio between a fast ATR and a slow ATR, combined with a percentile rank of current volatility within a historical window. The indicator classifies every bar into one of three states — Expansion, Compression, or Transition — and identifies squeeze conditions (volatility compressing well below its average) and expansion bursts (volatility accelerating rapidly). The oscillator, centered at zero, makes it immediately clear whether volatility is expanding or contracting relative to its baseline. Volatility regime is one of the most underappreciated dimensions of market analysis. A trend-following strategy applied during volatility compression produces poor results because the market is not moving directionally with sufficient energy. A mean-reversion strategy applied during volatility expansion gets stopped out repeatedly because the market is generating outsized moves. Identifying the current volatility terrain before applying any strategy is a prerequisite for selecting the appropriate approach. Core Concepts 1. Fast/Slow ATR Ratio The primary oscillator compares a short-period ATR (default 14) against a long-period ATR (default 100). Their ratio, centered at 1.0, is shifted to center at 0.0 by subtracting 1. Values above 0 mean recent volatility is expanding relative to the longer-term baseline; values below 0 mean it is contracting. This ratio is more informative than ATR alone because it provides context — the same ATR value means different things in a historically volatile versus historically calm market. 2. Percentile Rank The ATR percentile rank answers: where does today's volatility sit within its historical distribution? A 90th percentile reading means volatility is higher than 90% of observations in the lookback period. This is used to classify whether the current environment is historically extreme or within normal parameters. 3. Squeeze and Expansion Burst Detection A squeeze is defined as fast ATR falling below 82% of slow ATR and also below its own 20-bar average. This double condition filters single-bar dips. A squeeze represents stored energy — the market is coiling. An expansion burst is defined as the ATR ratio exceeding 1.25 with the fast ATR making successive higher values. This marks the initial stages of a volatility explosion. 4. Signal Line and Histogram The oscillator is triple-processed: EMA of ratio → SMA signal → histogram. The histogram shows the divergence between the oscillator and its signal, providing a leading read on whether volatility momentum is building or fading. Features Volatility Regime Oscillator: Gradient-colored histogram bars centered at zero Squeeze Detection: Dashboard alert and dot marker when squeeze conditions are active Expansion Burst Markers: Dot markers when volatility breaks out from compression ATR Percentile Band: Normalized ATR rank plotted as a secondary line Zone Fills: Expansion and compression zones filled with transparent color 8-Row Dashboard: Regime, ATR values, ratio, percentile rank, squeeze status, oscillator values Input Parameters Fast ATR Period: Short-term volatility measurement (default: 14) Slow ATR Period: Long-term volatility baseline (default: 100) Percentile Lookback: Historical window for rank calculation (default: 252) Signal Smoothing: Signal line period (default: 9) Expansion, Compression, and Transition color inputs How to Use This Indicator Compression → Expansion Transition The most significant signal is when a squeeze resolves into an expansion burst. This represents a volatility state change — the market has been coiling and is now releasing energy. The direction of that release is not predicted by this indicator; it must be determined using price structure and other context. Oscillator Zero Cross The oscillator crossing from negative to positive territory indicates that short-term volatility has exceeded the long-term baseline. This is not a trade signal — it is a condition indicator confirming that the market is entering a higher-energy phase. High Percentile + Expansion When the oscillator is in expansion territory and the ATR percentile rank is above 80, the market is experiencing historically significant volatility. Stops must be sized accordingly. Limitations ATR is backward-looking. Sudden volatility spikes from news events will appear in the oscillator only after those bars close The squeeze condition uses fixed multipliers (0.82 for the ATR ratio threshold). Markets with different typical volatility profiles may require adjustments to these thresholds The percentile lookback of 252 bars requires approximately one year of daily data or equivalent for the rank to be historically meaningful. On shorter data sets the rank will be computed on whatever bars are available but will be less statistically robust This indicator classifies current conditions only. It does not predict when a squeeze will resolve or in which direction Originality Statement The dual-ATR ratio approach combined with percentile ranking provides more contextual information than either measure alone. The squeeze detection using a double condition (ratio below threshold and below its own moving average) produces more reliable squeeze identification than a single-condition approach. The four-state histogram coloring (expanding positive, fading positive, expanding negative, fading negative) provides more nuanced momentum information than standard positive/negative coloring. Disclaimer This indicator is for educational and informational purposes only. Volatility regime classification does not predict price direction. A squeeze does not guarantee a subsequent expansion, and the direction of any expansion is unknowable from volatility data alone. Always use appropriate risk management. -Made with passion by officialjackofalltrades
Penunjuk Pine Script®
oleh officialjackofalltrades
Adaptive Regime Momentum [JOAT]Adaptive Regime Momentum Introduction The majority of publicly available trend-following strategies rely on one of two entry mechanisms: a moving average crossover, or a price-versus-MA relationship. These are valid starting points, but they share a common weakness — they fire signals based on a single confirmatory condition that can be triggered by brief, low-conviction price moves. A single bar pushing above a moving average while volume is thin and the MA is barely sloping is not the same market condition as a sustained directional move with volume behind it and a clearly sloping MA. Yet a simple strategy would treat both identically. Adaptive Regime Momentum is a trend-following strategy that requires three independent conditions to align before generating an entry signal. These three layers — MA slope confirmation over multiple consecutive bars, price position relative to the MA, and a volume-based demand filter — must all agree simultaneously. The result is a strategy that generates fewer signals but with higher internal consistency between entry conditions. It is designed for liquid markets on daily or higher timeframes where each component is reliably measurable. This is an overlay strategy — all visuals are plotted directly on the price chart. --- Strategy Properties The following default settings are used for all backtests unless modified: Initial capital: $10,000 Position sizing: 5% of equity per trade Commission: 0.05% per side Pyramiding: 0 (only one open position at a time; new signals are ignored while a position is active) Stop loss: 2.5x ATR below the entry price (long), 2.5x ATR above the entry price (short), calculated from strategy.position_avg_price Take profit: 4.0x ATR above the entry price (long), 4.0x ATR below the entry price (short), calculated from strategy.position_avg_price Trail / slope exit: Position is closed early if price crosses to the wrong side of ComboMA ± 1.5x ATR, or if the MA slope reverses direction The stop and take profit are anchored to strategy.position_avg_price — the actual average fill price of the position — rather than the signal bar's close. This ensures that in backtesting, stop and TP distances are measured from where the trade was actually opened, not from a theoretical signal level. These are backtesting defaults only. They do not represent a recommendation for live trading position sizing or risk management. --- Core Concepts Signal 1 — ComboMA Slope Confirmation (Structural Momentum) The ComboMA is a blend of two moving averages: ALMA (Arnaud Legoux Moving Average) — a smooth MA with reduced lag, fitting to recent price without overreacting to single bars ZLMA (Zero-Lag Moving Average) — a lag-compensated MA designed to reduce the delay between price movement and MA response The two are blended into a single ComboMA value. The slope of this composite is then evaluated not just on the current bar, but across the last N consecutive bars (default: 3). A slope is only confirmed as UP if all of the last 3 bars showed a positive slope. A slope is only confirmed as DOWN if all 3 bars showed a negative slope. A single slope fluctuation — even if the most recent bar shows a positive slope — does not trigger confirmation unless all N bars agree. This multi-bar slope confirmation is the primary mechanism that distinguishes this strategy from a simple MA-based entry. A one-bar slope flip that immediately reverses is filtered out. Only a sustained slope direction triggers the first condition. Signal 2 — Price vs. ComboMA (Real-Time Confirmation) The second condition requires that price is currently on the correct side of the ComboMA: For a long: close > ComboMA For a short: close < ComboMA This condition is evaluated at the current bar, providing real-time confirmation that price is aligned with the structural slope direction. The MA slope could be upward from prior bars, but if price has already pulled back below the MA, the second condition vetoes the entry. Both the historical slope and the current price position must agree. Signal 3 — Volume RSI (Demand Pressure Validation) Volume RSI is RSI applied to raw volume over an 8-bar period, then divided by 50. A result above 1.0 (the default threshold) means the Volume RSI is above 50 — indicating that volume activity on recent bars has been relatively elevated compared to the preceding period. For a long entry: Volume RSI / 50 must exceed the threshold For a short entry: same condition applies Volume RSI does not confirm direction — it confirms participation . A move accompanied by above-average volume has more demand/supply backing than a low-volume drift. When volume is below threshold, the third condition is not met and no entry is generated, even if slope and price position align. RSI Filter An additional RSI filter is applied to the close: RSI(14) must be above 50 for long entries RSI(14) must be below 50 for short entries This acts as a momentum gating condition — confirming that short-term momentum is consistent with the trade direction before entry is permitted. Non-Repainting Execution All entry conditions are gated by barstate.isconfirmed . No signal is generated until the current bar has fully closed. This prevents intra-bar signal flickering and ensures that the backtest accurately represents what would have been traded on confirmed bar closes. --- Exit Logic The strategy uses a layered exit system combining fixed risk-defined targets with adaptive trend exits: Fixed exits (via strategy.exit): Stop loss at 2.5x ATR from entry price Take profit at 4.0x ATR from entry price Trail exits (via strategy.close): Price closes beyond ComboMA ± 1.5x ATR on the wrong side The ComboMA slope reverses (multi-bar confirmation fails in the opposite direction) The trail exit allows winning positions to exit earlier if the trend deteriorates before reaching the fixed take profit, while the fixed TP provides a defined maximum target. The stop loss is the unconditional floor regardless of trail conditions. --- ATR Shadow Visual The chart displays two layers of ATR bands around the ComboMA: Inner band: ComboMA ± 1x ATR Outer band: ComboMA ± 2x ATR These bands give a visual read of how extended price is from the MA relative to recent volatility, and where the trail exit threshold sits (1.5x ATR, between the two bands). They are visual aids only and do not affect strategy logic. --- Performance Table A table is displayed on the chart showing current strategy metrics: Net P&L Open P&L (current unrealized) Win Rate Average winning trade Average losing trade Maximum drawdown Total trades Current position direction Current MA slope status --- Features Three-layer entry confirmation: multi-bar MA slope, price vs. MA, and Volume RSI RSI momentum filter as an additional gating condition ALMA + ZLMA blend for the ComboMA, reducing lag without sacrificing smoothness Multi-bar slope confirmation preventing single-bar slope flickers from triggering entries ATR-based stop and take profit anchored to actual fill price via strategy.position_avg_price Trail exit on slope reversal or price-vs-MA breach Non-repainting: all signals confirmed via barstate.isconfirmed Pyramiding disabled — one position at a time ATR shadow bands for visual context around the ComboMA Live performance table with key metrics --- Input Parameters ALMA / ZLMA settings — length, offset, and sigma for each MA component Slope Confirm Bars (default 3) — consecutive bars of slope agreement required for confirmation Volume RSI Length (default 8) — RSI period applied to volume Volume Threshold (default 1.0) — Volume RSI / 50 minimum for the demand filter RSI Length (default 14) — RSI period for the momentum filter ATR Length — period for ATR used in stop, TP, trail, and visual bands Stop Multiplier (default 2.5) — ATR multiplier for the fixed stop loss TP Multiplier (default 4.0) — ATR multiplier for the fixed take profit Trail Multiplier (default 1.5) — ATR multiplier for the trail exit threshold --- How to Use Apply to daily or higher timeframes on liquid instruments. Volume RSI is most meaningful where volume data is consistent and representative of actual market participation. Allow the chart to load sufficient historical bars before evaluating backtest results. The ComboMA slope confirmation requires multiple bars of agreement, and early bars in the dataset may not reflect the strategy's typical behavior. Aim for at least several hundred bars of data for meaningful backtest statistics. Review the performance table while backtesting to understand average win size relative to average loss, drawdown, and total trade count. A strategy with very few trades may show favorable metrics by chance rather than edge — consider whether the trade count is sufficient to draw conclusions. The default 5% equity position size produces moderate equity curve sensitivity. Smaller sizes will reduce drawdown and return proportionally; larger sizes will amplify both. Commission is set to 0.05% per side (0.1% round trip) by default. Adjust this to match your actual trading costs. Higher commission rates — especially relevant for frequent-trading timeframes — will reduce net results. Do not optimize parameters on the same data you use to evaluate performance. Optimization on historical data produces settings tuned to past noise, not future edge. The trail exit on slope reversal means that strongly trending markets where the MA briefly flattens before resuming may see early exits. This is the tradeoff for using slope as an exit condition. --- Limitations Backtest results are calculated on historical data and do not guarantee future performance. Market conditions change, and a strategy that performed well in a particular regime may perform differently as conditions evolve. The Volume RSI filter requires reliable volume data. This strategy is not recommended for synthetic instruments, CFDs where volume represents contracts rather than underlying market activity, or very short intraday timeframes where volume is fragmented and noisy. On such instruments, the third entry condition may be meaningless or misleading. The multi-bar slope confirmation requirement means the strategy will miss fast, sharp trend initiations where the MA slope has not yet had N bars to confirm. This is a deliberate tradeoff — reducing false entries at the cost of some late entries on fast moves. Pyramiding is disabled. The strategy will not add to winning positions. This limits upside during strongly trending markets where additional entries might be beneficial, but it also limits drawdown from compounding positions that subsequently reverse. ATR-based stops and TPs are fixed at entry. They do not adjust after the trade is open (apart from the trail exit). If volatility expands significantly after entry, a 2.5x ATR stop that was appropriate at entry may become relatively tight. The performance table reflects cumulative backtest results as of the current bar. Results will vary across different lookback windows and instruments. Default capital of $10,000 with 5% equity sizing means each trade risks approximately $500 before the stop is hit (assuming stop is the loss floor). This is a backtesting convention — it is not a recommendation for live account sizing. No strategy produces guaranteed results. The three-layer entry system improves internal signal consistency but cannot eliminate the inherent uncertainty of financial markets. --- Originality Statement Standard MA-based trend strategies treat a single bar's price-vs-MA relationship as sufficient for entry. ARM's primary differentiation is the multi-bar slope confirmation requirement : the ComboMA slope must be consistently positive (or negative) across N consecutive bars before the first condition is met. A one-bar slope deviation — common during consolidations and brief retracements — does not trigger entry. Only a sustained slope direction qualifies. The ComboMA itself is a blend of ALMA and ZLMA, combining the smoothness and Gaussian weighting of ALMA with the lag-compensation of ZLMA. Neither is used in isolation because each has a specific weakness: ALMA can lag on sharp moves; ZLMA can be sensitive to noise. The blend leverages the strengths of both while partially offsetting their weaknesses. The three-layer confirmation architecture — slope duration, price position, and demand validation — requires agreement across genuinely different measurement types: structural momentum over time, current price location, and volume activity. These are not three views of the same quantity. The stop and TP placement using strategy.position_avg_price rather than the signal bar close is a practical accuracy measure: in backtesting, it means risk distances are calculated from the price at which the trade was actually filled, not from where the signal was generated, which can differ from the fill price particularly on gap opens. --- Disclaimer This strategy is provided for educational and informational purposes only. It does not constitute financial advice, investment advice, or a recommendation to buy or sell any security. Backtested results are hypothetical and do not reflect actual trading. Hypothetical performance results have inherent limitations and do not account for execution slippage, liquidity constraints, or the psychological challenges of live trading. All trading involves risk, including the possible loss of principal. Always conduct your own research and consult a qualified financial professional before making any trading or investment decisions. -Made with passion by officialjackofalltrades
Strategi Pine Script®
oleh officialjackofalltrades
Confluence Signal Engine [JOAT]Confluence Signal Engine Introduction Most traders encounter a common trap: stacking multiple indicators that all claim to measure something different, yet each one is ultimately derived from the same price data. The result is not confirmation — it is correlated noise presented as agreement. The Confluence Signal Engine was built to address this directly. This indicator assigns a composite score to the current market condition by evaluating six deliberately chosen dimensions of market behavior. Each dimension is designed to measure a fundamentally different property of price action. When multiple dimensions agree, that agreement carries more weight than any single indicator firing alone. The result is a single, normalised score between -1 and +1, accompanied by a visual confidence meter and a score breakdown table so you can see exactly what is driving the signal. This is an overlay indicator — it plots directly on the price chart. --- Core Concepts The Six Scoring Dimensions Each dimension returns one of three values: +1 (bullish contribution), -1 (bearish contribution), or 0 (neutral / insufficient data). These are summed and divided by 6.0 to produce the composite score. D1 — EMA Alignment (Trend Direction) Compares a fast EMA to a slow EMA. If the fast EMA is above the slow EMA, the trend dimension scores +1. If below, it scores -1. This is the structural backbone — a baseline read on which side of the trend the price currently sits. D2 — Price Z-Score (Statistical Deviation) Calculates how many standard deviations the current close is from a baseline EMA. A Z-score below the negative threshold suggests the price has deviated far enough below the mean to be considered statistically stretched — a potential reversion candidate, scored +1. A Z-score above the positive threshold scores -1. This dimension does not measure trend; it measures relative price position against recent statistical norms. D3 — Volume Pressure (Demand Validation) Uses a Volume RSI (RSI applied to volume over 8 bars, divided by 50) as a proxy for whether volume activity is elevated. When volume pressure exceeds the threshold, the candle's direction (close vs. open) determines the score: a bullish candle in high-volume conditions scores +1; a bearish candle scores -1. When volume is not elevated, this dimension returns 0, contributing nothing. This prevents volume noise on low-activity bars from polluting the signal. D4 — RSI Momentum (Momentum Quality) Evaluates both the current RSI value and its slope. A rising RSI above 50 scores +1 — confirming that momentum is positive and strengthening. A falling RSI below 50 scores -1. This differs from a simple RSI threshold because the slope requirement means momentum must be actively moving in the scored direction, not merely sitting above or below a level. D5 — Structural Position (Range Placement) Compares the current close to the midpoint of the highest high and lowest low over a configurable lookback period. Closing above the midpoint scores +1; closing below scores -1. This is a simple but useful structural context: is price holding in the upper or lower half of its recent range? D6 — Volatility Context (Environment Quality) Divides a fast ATR by a slow ATR to produce a volatility ratio. A low ratio (calm, contracting volatility) scores +1 — historically a more favorable environment for trend continuation. A high ratio (expanding, elevated volatility) scores -1, flagging that the current environment may be erratic. A ratio between the two thresholds is neutral. This dimension does not predict price direction; it assesses whether current conditions are conducive to acting on the other signals. --- Composite Score and Confidence compositeScore = (D1 + D2 + D3 + D4 + D5 + D6) / 6.0 confidence = math.abs(compositeScore) * 100 The composite score ranges from -1.0 (all six dimensions bearish) to +1.0 (all six dimensions bullish). The confidence value is simply the absolute magnitude — a score of ±1.0 represents 100% agreement across all dimensions, while a score near 0 represents disagreement or neutrality. Signal thresholds: Score > buy threshold (default 0.3) → bullish signal Score < sell threshold (default -0.3) → bearish signal Score > high-confidence threshold (default ±0.6) → high-confidence signal Signals are gated by barstate.isconfirmed — they only fire on fully closed bars, preventing intra-bar repainting. State tracking also prevents the same directional signal from repeating consecutively without a change in direction first. --- Visual Components 24-Cell Gradient Confidence Meter A horizontal bar of 24 cells is displayed at the bottom of the chart. The left side is the bearish extreme, the center is neutral, and the right side is the bullish extreme. The current composite score position is highlighted within the meter, giving a continuous visual read of where the market sits in the conviction range — not just whether a signal has fired, but how strongly. Score Breakdown Table A table showing three columns for each dimension: dimension name, dimension number, and its current score (+1, -1, or 0). This allows you to see exactly which dimensions are contributing to the composite and which are neutral or conflicting. Gradient Bar Coloring Price bars are colored using a gradient that interpolates from a neutral color toward the signal color, weighted by the absolute value of the composite score. A high-confidence bull signal produces a strong green bar; a low-confidence or mixed signal produces a muted or neutral color. This keeps bar coloring proportional to actual conviction rather than using a binary flip. --- Features Six-dimension composite scoring system covering trend, statistics, volume, momentum, structure, and volatility Composite score normalised to with confidence percentage Non-repainting: all signals confirmed on bar close via barstate.isconfirmed State-tracked signals prevent repeated same-direction firing 24-cell gradient confidence meter with continuous position display Score breakdown table showing each dimension's individual contribution Gradient bar coloring proportional to conviction level Configurable thresholds for all six dimensions and signal levels --- Input Parameters EMA Fast / Slow (default 21 / 55) — D1 trend alignment Z-Score Baseline EMA (default 50) — the mean used for Z-score calculation Z-Score Window (default 50) — standard deviation lookback Z-Score Threshold (default 1.5) — how many standard deviations trigger the score Volume RSI Length (default 8) — RSI period applied to volume Volume Threshold (default 1.2) — Volume RSI / 50 must exceed this to activate D3 RSI Length (default 14) — standard RSI period for D4 Structure Lookback (default 20) — bars used to define the high/low range for D5 ATR Fast / Slow (default 14 / 50) — periods for the volatility ratio in D6 Volatility Thresholds (default 0.8 / 1.5) — low and high boundaries for the ATR ratio Buy Threshold (default 0.3) — minimum composite score to generate a long signal Sell Threshold (default -0.3) — maximum composite score to generate a short signal High-Confidence Threshold (default ±0.6) — score level at which a signal is classified as high-confidence --- How to Use Apply to any chart. The overlay paints directly on price bars. Watch the confidence meter for the current composite score position. A score pressed toward either extreme with multiple dimensions aligned is a higher-quality read than one sitting near center. Use the score breakdown table to understand why the composite score is what it is. If only 2 of 6 dimensions are contributing, the signal is weaker regardless of whether it crossed the threshold. High-confidence signals (score beyond ±0.6 by default) indicate that four or more of the six dimensions are in agreement. These can be treated as stronger setups than threshold-level signals. Combine the composite score read with your own price action, support/resistance, or higher-timeframe context before entering a trade. This indicator is a confluence tool, not a standalone entry system. If several dimensions are conflicting (score near 0), the market is not in a clear state — no action is the appropriate response. --- Limitations No indicator can predict future price. The composite score reflects current market conditions based on recent historical data — not what will happen next. Z-score and structural position dimensions are mean-reverting in nature, while EMA alignment and RSI momentum are trend-following. In strongly trending markets, D2 and D5 may produce persistent bearish readings even during a healthy uptrend, suppressing the composite score. This is by design — the indicator is more suited to environments where confluence across all dimensions is achievable. Volume RSI (D3) is only reliable on instruments and timeframes with consistent, meaningful volume data. On synthetic instruments, indices, or very low-timeframe charts, volume data may be unreliable and D3's contribution should be weighted accordingly. The volatility context dimension (D6) measures the environment , not direction. A low-volatility score of +1 does not mean the market is about to move up — only that conditions are historically more favorable for clean signals. Signal state tracking prevents consecutive same-direction signals, which reduces noise but also means the indicator will not re-fire during a prolonged trending move. This is a deliberate design choice but should be understood before use. Default thresholds were chosen for general applicability. Different asset classes, timeframes, and volatility regimes may benefit from threshold adjustment. Past signal quality on any given instrument does not guarantee future performance. --- Originality Statement The core innovation of this indicator is the deliberate selection of six dimensions that measure fundamentally different market properties rather than multiple views of the same property. Standard multi-indicator approaches tend to combine RSI, MACD, and Stochastic — all of which are momentum oscillators derived from price, generating correlated signals that appear independent but are not. This indicator separates the problem into distinct domains: trend direction (EMA alignment), statistical deviation from the mean (Z-score), demand-side pressure (Volume RSI), momentum quality and direction (RSI slope + level), structural placement within recent range (midpoint comparison), and environmental favorability (ATR ratio). Because these dimensions are largely uncorrelated with each other, genuine multi-dimension agreement represents a qualitatively different kind of confluence than stacking three oscillators. The 24-cell gradient meter goes further — it provides a continuous conviction read rather than a binary signal, treating market condition as a spectrum. --- Disclaimer This indicator is provided for educational and informational purposes only. It does not constitute financial advice, investment advice, or a recommendation to buy or sell any security. All trading involves risk, including the possible loss of principal. Past indicator performance does not guarantee future results. Always conduct your own research and consult a qualified financial professional before making any trading decisions. -Made with passion by officialjackofalltrades
Penunjuk Pine Script®
oleh officialjackofalltrades
Tidal Volume Oscillator [JOAT]Tidal Volume Oscillator Introduction The Tidal Volume Oscillator is a separate-pane oscillator that attempts to answer a single question: is the current price movement being carried by genuine volume participation, or is it occurring on weak flow? It constructs a volume-weighted momentum score, normalizes it to a bounded range of −100 to +100, applies a Fourier-inspired exponential decay smoothing pass to reduce noise without introducing phase lag, and then scales the result with an adaptive trend filter. A flow momentum line tracks the acceleration of the oscillator itself. A divergence engine scans for all four divergence types simultaneously — regular bullish, regular bearish, hidden bullish, and hidden bearish — and plots them directly in the oscillator panel. The indicator does not predict future price. It contextualizes current price movement relative to volume behavior and flags when price action and volume-weighted momentum are moving in opposite directions, which historically precedes changes in directional character — though not always, and not reliably in all instruments or conditions. --- Core Concepts The VZO Foundation The Volume Zone Oscillator (VZO) is an established concept that categorizes volume as positive or negative based on the direction of price change, then computes a ratio of positive to negative volume over a rolling window. This indicator rebuilds that concept from the ground up using a different normalization approach: Relative Volume: Instead of using raw volume, the oscillator first normalizes each bar's volume against a rolling SMA of volume. This produces a relative volume reading — a value above 1.0 means the bar traded heavier than average, below 1.0 means lighter. This step removes the absolute scale of volume from the calculation, allowing the oscillator to behave comparably across instruments with vastly different volume profiles and across timeframes where absolute volume differs by orders of magnitude. Volume-Weighted Momentum: The price change on each bar is smoothed via EMA, and the relative volume is separately smoothed via EMA. Multiplying these two smoothed values produces a volume-weighted momentum signal. This is then smoothed again to form a base momentum reading. RSI-Style Normalization: Positive and negative portions of the base momentum are separated, each independently smoothed, and their ratio is fed into an RSI-style formula: vzo = 100 * (ratio - 1) / (ratio + 1) . This bounds the oscillator strictly between −100 and +100 and gives it a symmetric zero-line structure where positive values indicate dominant upward volume momentum and negative values indicate dominant downward volume momentum. Fourier Exponential Decay Smoothing After the initial VZO is computed, a second smoothing pass is applied using exponential decay weights. For each bar, the contribution of each of the prior N bars is weighted by exp(-i / (len * 0.3)) , where i is the number of bars back. This means the most recent bar carries maximum weight and each earlier bar contributes exponentially less. The window clips naturally as the weights approach zero. The result is a smoothing pass that is inspired by frequency-domain thinking: it emphasizes recent values and de-emphasizes older values in a continuous decay rather than in the binary on/off fashion of a simple rolling average. The smoothed output tracks the oscillator's underlying shape while suppressing high-frequency noise without the phase shift that a centered moving average would introduce. ADF Trend Filter An adaptive multiplier is derived by comparing a short SMA and a long SMA of price, normalizing their difference by the rolling standard deviation of price over a matching window. This produces a dimensionless value that reflects the strength of the current trend relative to recent volatility — conceptually analogous to the logic behind an Augmented Dickey-Fuller trend test applied in a simplified real-time form. This multiplier is kept close to 1.0 intentionally. Its role is not to dramatically change the oscillator's value but to apply a mild scaling that slightly amplifies the VZO when trend conditions are strong and slightly suppresses it during choppy, mean-reverting conditions. The effect is subtle but helps the oscillator's readings align better with the underlying market character. Final Blended VZO The final oscillator value blends the EMA-smoothed VZO and the Fourier-smoothed VZO according to a blend parameter, scales the result by the ADF multiplier, and clamps the output to the range. The blend parameter controls how much weight goes to the Fourier-smoothed version versus the EMA-smoothed version, allowing the user to tune between responsiveness and smoothness. Flow Momentum Line A secondary line is plotted alongside the main oscillator, computed as: flow_momentum = (vzo - ema(vzo, lookback)) * 0.5 This measures the rate of change of the oscillator — its acceleration — and scales it to stay visually proportional. When the flow momentum line is rising, the oscillator is accelerating upward. When it is falling, the oscillator is losing momentum regardless of its absolute level. Crossovers between the oscillator and the flow momentum line can highlight inflection points in volume-weighted momentum. Divergence Engine The divergence engine uses pivot high and pivot low detection to identify four divergence types: Regular Bullish Divergence: Price makes a lower low while the oscillator makes a higher low. Suggests weakening downward volume participation on the new price low. Regular Bearish Divergence: Price makes a higher high while the oscillator makes a lower high. Suggests weakening upward volume participation on the new price high. Hidden Bullish Divergence: Price makes a higher low while the oscillator makes a lower low. Often associated with pullbacks within an established uptrend where volume momentum remains stronger than the pullback's depth implies. Hidden Bearish Divergence: Price makes a lower high while the oscillator makes a higher high. Often associated with rallies within an established downtrend where volume momentum is failing to confirm the price bounce. The engine uses ta.valuewhen to retrieve the oscillator's value at the most recent prior pivot of the same type, then compares it to the current pivot. Lines and labels are drawn directly in the oscillator pane, keeping all divergence context in a single panel. Dynamic Color Blending The oscillator line and histogram (if enabled) use color blending that responds to both the direction of the oscillator and the intensity of the flow momentum. Colors transition smoothly between bull and bear palettes as conditions shift, with intensity modulated by momentum acceleration. This avoids binary color flips and gives a continuous visual read of the oscillator's strength and direction. --- Features Relative-volume-normalized VZO foundation — removes absolute volume scale bias RSI-style normalization producing a symmetric −100 to +100 oscillator Fourier exponential decay smoothing pass for noise reduction without phase lag ADF-inspired adaptive trend multiplier for regime-sensitive scaling Blended output combining EMA and Fourier smoothing with user-adjustable weighting Flow momentum line showing oscillator acceleration Full four-type divergence engine: regular bull/bear and hidden bull/bear Divergence lines and labels rendered directly in the oscillator pane Dynamic color blending based on direction and momentum intensity Overbought/oversold level lines at user-defined thresholds (default ±80) Fully toggleable visual components including divergence types individually --- Input Parameters VZO Length: Primary lookback for the volume-weighted momentum and normalization calculations (default: 14) Smoothing Length: Short EMA length used in the initial volume-weighted momentum construction (default: 5) Signal Length: EMA length applied to the final VZO for the signal/flow line (default: 9) Fourier Window: Number of bars used in the exponential decay smoothing pass (default: 20) Fourier Blend: Proportion of the final output taken from the Fourier-smoothed VZO versus the EMA-smoothed VZO (default: 0.4, meaning 40% Fourier / 60% EMA) Overbought Level: Upper reference line threshold (default: +80) Oversold Level: Lower reference line threshold (default: −80) Pivot Bars: Number of bars on each side required to confirm a pivot high or low for divergence detection Visual Toggles: Individual controls for divergence types (regular bull, regular bear, hidden bull, hidden bear), flow momentum line, bar coloring, and OB/OS lines --- How to Use Reading the oscillator: Values above zero indicate that volume-weighted momentum favors buyers over the lookback window. Values below zero indicate it favors sellers. The magnitude reflects how dominant one side is. A reading of +60 is meaningfully different from +20 — the former suggests strong participation on the upside, the latter suggests modest positive lean. Overbought/oversold levels: The default ±80 levels are deliberately set wide. Reaching ±80 indicates a statistically strong skew in volume momentum, not simply a directional bias. A reading at +85 that begins to decline is worth noting; a reading that has been above +80 for many bars without declining suggests strong persistent flow, not an automatic reversal condition. Flow momentum line: Use the flow momentum line to identify when the oscillator is accelerating or decelerating. If the oscillator is above zero but the flow momentum line is falling and crossing below the oscillator, volume-weighted momentum is losing strength even if it has not crossed zero. This can be an early warning of a fading move. Divergences: Divergence signals appear as labeled lines in the oscillator pane. They flag a disagreement between price structure and volume momentum structure. Regular divergences are typically associated with potential trend reversal conditions; hidden divergences are typically associated with trend continuation conditions during a pullback. Neither type is a standalone entry signal — they require context from price structure, higher timeframe trend, and other confirmation. Combining types: A regular bearish divergence occurring while the oscillator is above +60 and the flow momentum line is declining is a more compelling condition than a divergence occurring at a neutral oscillator reading. Look for confluence between divergence signals, oscillator level, and flow momentum direction. Timeframe notes: On lower timeframes, the divergence engine will fire frequently and many signals will resolve as noise. On higher timeframes, divergence signals are structurally more significant but rarer. The Fourier blend and VZO length should be calibrated to the timeframe being traded. --- Limitations This indicator does not predict future price movement. All readings are computed from past and current bar data. Volume data quality varies significantly across instruments and data providers. On instruments with unreliable, synthetic, or missing volume data (some forex pairs, certain CFDs, spread-betting instruments), the oscillator's readings will be distorted or meaningless. Divergences are detected only at confirmed pivot points, which by definition require a lookback into past bars. A divergence signal will appear after the pivot is confirmed, not at the pivot bar itself. This is inherent to pivot-based divergence detection and is not a bug. Hidden divergences can occur frequently during strong trends and produce many signals that resolve without follow-through on shorter timeframes. The ADF-inspired filter is a simplified heuristic, not a formal statistical test. It does not guarantee that the adaptive scaling accurately reflects whether a market is trending or mean-reverting at any given moment. The Fourier exponential decay smoothing is not a formal frequency-domain Fourier transform. The term is used descriptively to indicate the exponential weighting pattern, not to imply that the calculation resolves into sinusoidal components. Extreme or sustained overbought/oversold readings do not guarantee a reversal. Strong trends can keep the oscillator pinned at extremes for extended periods. The oscillator is bounded at ±100 by construction. This means that at extreme readings, additional strengthening of volume momentum does not move the line further — the clamping obscures incremental changes at extremes. Past divergence performance on a given instrument is not indicative of future performance. --- Originality Statement The VZO concept is established in the public domain. This implementation departs from the standard in several meaningful ways. Using relative volume (each bar's volume divided by a rolling SMA of volume) rather than raw volume removes the absolute scale of volume from the oscillator's behavior — a standard VZO applied to a futures contract and a low-float equity will behave differently purely due to volume magnitude; this version will not. The RSI-style normalization of the volume-weighted momentum ratio is retained from the VZO concept but is applied to a momentum signal constructed differently from the standard signed-volume approach. The Fourier exponential decay smoothing layer is an original addition: it is not a standard EMA, WMA, or VWMA — it applies a decaying weight function that is conceptually distinct from any standard Pine Script built-in smoothing function, producing a cleaner oscillator output with less phase distortion than an equivalent EMA. The ADF-inspired adaptive multiplier is a real-time regime-sensitivity mechanism not present in any standard oscillator. The four-type divergence engine built into the same panel, detecting all four divergence classes simultaneously using pivot comparison logic, provides complete divergence coverage without requiring additional scripts or manual line drawing. The combination of these elements — relative-volume normalization, Fourier decay smoothing, adaptive trend scaling, blended output, flow momentum line, and full-coverage divergence detection — into a single oscillator panel represents an original synthesis that is not replicated by any standard built-in indicator. --- Disclaimer This indicator is provided for educational and informational purposes only. It does not constitute financial advice, investment advice, or a recommendation to buy or sell any financial instrument. Trading involves substantial risk of loss. Past performance of any indicator or strategy is not indicative of future results. Always conduct your own research and consult a qualified financial professional before making any trading decisions. -Made with passion by officialjackofalltrades
Penunjuk Pine Script®
oleh officialjackofalltrades
Structural Deviation Compass [JOAT]Structural Deviation Compass Introduction The Structural Deviation Compass is an overlay indicator designed to map where price stands relative to its own statistical history. Rather than drawing fixed-distance envelopes or relying on a single moving average, it constructs a hybrid centerline from two distinct low-lag moving average types, then wraps that centerline in volatility-adaptive bands derived from Z-score normalization. A secondary oscillator layer — applied to RSI — creates a dual-confirmation signal gate that fires only when both price deviation and momentum reach simultaneous extremes. Shadow bands built from the Average True Range provide additional spatial context across three volatility tiers. The indicator does not predict future price. It identifies statistically unusual deviations from an estimated mean structure and flags conditions where a reversion or continuation setup may be forming, subject to confirmation from the trader's own process. Core Concepts The ComboMA Centerline The foundation of the indicator is a composite moving average called the ComboMA, formed by averaging two lines: ALMA (Arnaud Legoux Moving Average): Uses a Gaussian-weighted kernel positioned asymmetrically along the lookback window. The offset and sigma parameters control how far toward the recent end the weight mass sits and how tightly it is concentrated. This produces a smooth line that tracks price closely while suppressing noise better than a simple EMA of the same length. ZLMA (Zero-Lag Moving Average): Constructed by doubling a base EMA and subtracting a second EMA of that EMA — a technique that estimates and removes the inherent lag of an exponential average. The result is then smoothed once more to reduce the noise amplification that zero-lag constructions can introduce. Averaging the two produces a centerline that carries reduced lag from the ZLMA side while retaining the smooth, noise-filtered character of the ALMA side. Neither line alone fully satisfies both goals; together they produce a more balanced result. Z-Score Price Bands Rather than plotting bands at a fixed multiple of a standard deviation (as Bollinger Bands do using a rolling standard deviation of price itself), the SDC first computes the deviation of close from the ComboMA, then Z-score normalizes that deviation series over a separate lookback window. The bands are then placed back on the price chart by multiplying the rolling standard deviation of deviations by the chosen Z-score threshold values. The practical effect is that the band width reflects how unusual the current deviation is relative to the recent distribution of deviations — not simply how wide price has swung in a raw sense. Two threshold levels are provided, creating an inner and outer band pair on each side of the ComboMA. RSI Z-Score RSI is computed in the standard way, then subjected to the same Z-score normalization: the RSI value is compared to its own rolling mean and expressed in standard deviations. This removes the fixed-level bias of RSI (where 30/70 thresholds mean different things in different market regimes) and produces a momentum reading that is self-calibrating to recent RSI behavior. Dual Z-Score Signal Gate A long signal requires all of the following simultaneously: Price Z-score below the negative trigger threshold (price is statistically far below the ComboMA) RSI Z-score below the negative trigger threshold (momentum is statistically depressed) RSI EMA below 38 (confirming a bearish momentum context rather than a pullback within strength) The current bar closed above the prior bar's close (a micro-confirmation that selling pressure may be easing) The bar is confirmed (signal does not repaint on the forming bar) Short signals apply the mirror logic. The requirement for extremes in both dimensions simultaneously is intentionally strict — it filters out the many cases where price is extended but momentum is not, or vice versa. ATR Shadow Bands Three pairs of shadow bands are drawn around the ComboMA at 1x, 2x, and 3x of a rolling ATR. These are not signal bands — they serve as a spatial reference, helping to contextualize how far price has traveled from the estimated mean in volatility-adjusted terms. A move to the 3x ATR shadow in a low-volatility environment carries different significance than the same move in a high-volatility environment. RGB Smooth Color Transition The ComboMA line color transitions smoothly between a bull and bear palette by independently blending the red, green, and blue channels via EMA. Each channel tracks a target value set by the current bull/bear state, and converges toward it gradually. This avoids abrupt color flips and gives a visual sense of momentum continuity. Gradient Bar Coloring Individual bars are colored based on where the close sits within the band range relative to the ComboMA. Bars near the upper bands trend toward the bull color; bars near the lower bands trend toward the bear color. Bars near the ComboMA receive a neutral tone. This is a visual aid only and does not constitute a signal. Information Table A 9-row table displays the current readings for: market regime, price Z-score, RSI Z-score, RSI EMA, band width, signal strength, active signal, and ComboMA value. This gives a snapshot of the indicator's internal state without requiring the trader to hover over each plotted element. --- Features Hybrid ComboMA centerline combining ALMA and ZLMA Volatility-adaptive Z-score bands at two threshold levels (inner and outer) RSI Z-score normalization for regime-independent momentum reading Dual Z-score signal gate requiring simultaneous extremes in price and momentum Three-layer ATR shadow bands for spatial volatility context Smooth RGB channel blending on the ComboMA line color Gradient bar coloring based on position within band range Real-time information table with 9 indicator state readings Non-repainting signals (barstate.isconfirmed) Fully toggleable visual components --- Input Parameters MA Length: Base length for the ZLMA and ATR calculations ALMA Offset: Controls asymmetric weight positioning within the ALMA window (0 = old end, 1 = recent end) ALMA Sigma: Controls weight concentration; lower values spread the weight, higher values tighten it Z-Score Lookback: Rolling window for computing the mean and standard deviation of price deviations (default: 50) Inner Band Threshold: Z-score level for the inner band pair (default: 1.5σ) Outer Band Threshold: Z-score level for the outer band pair (default: 2.5σ) RSI Length: Period for RSI calculation (default: 14) RSI Z-Score Lookback: Rolling window for normalizing RSI Signal Trigger: Z-score threshold required in both dimensions to generate a signal (default: 1.8σ) ATR Multipliers: Multipliers for the three shadow band tiers (1x, 2x, 3x) Visual Toggles: Individual on/off controls for bands, shadows, bar coloring, table, and signals --- How to Use Reading the centerline: The ComboMA acts as the estimated mean structure. Price consistently above it with a bull-colored line suggests sustained upward bias; price oscillating around it suggests a ranging environment. Reading the bands: The inner bands (±1.5σ by default) represent moderately unusual deviations. The outer bands (±2.5σ by default) represent statistically rare deviations. A touch or breach of the outer band does not by itself mean a reversal is due — it means the move is statistically uncommon and warrants attention. Reading the shadow bands: Use the ATR shadows to understand how far, in volatility-adjusted terms, price has moved from the ComboMA. Price at the 3x shadow while also at the outer Z-score band is a more notable condition than either reading alone. Acting on signals: The dual Z-score signals flag confluent extremes. They should be used as an alert layer within a broader trading framework — not as standalone entry triggers. Consider the broader trend context, the timeframe, and supporting structure before acting. Using the table: Monitor the signal strength reading to understand how close the current state is to triggering a signal. This is useful for watching a developing setup in real time. Timeframe notes: The indicator functions on any timeframe. Higher timeframes produce fewer but more structurally significant signals. Lower timeframes will produce more signals, many of which will be noise. Adjust the Z-score lookback and trigger threshold accordingly. --- Limitations This indicator does not predict future price movement. All readings are descriptive of past and current bar data. The ComboMA, like all moving averages, will lag price during sharp trend changes. The ZLMA component reduces but does not eliminate this lag. Z-score bands assume that price deviations are approximately normally distributed. In instruments with fat-tailed distributions or during extreme events, the statistical thresholds will underestimate the probability of outlier moves. Signals are non-repainting on confirmed bars but will update on the forming bar until it closes. Always wait for bar close before acting on a signal. A signal firing does not mean price will reverse. Trending markets can sustain extreme Z-score readings for extended periods. The RSI EMA threshold (38 for longs) is a fixed filter that may not suit all instruments or regimes. It should be adjusted or disabled if it is filtering out valid setups in the instrument being traded. The ATR shadow bands are informational only and carry no predictive weight. Past signal performance on a given instrument is not indicative of future performance. --- Originality Statement The ALMA and ZLMA are established concepts. The ComboMA is not either of them — it is a blended centerline that takes the asymmetric-weight smoothness of ALMA and the lag-reduction property of ZLMA and produces a composite that neither achieves individually. The Z-score normalization of price deviations is a statistical adaptation that makes the bands self-calibrating to the instrument's deviation distribution rather than fixed. Applying the same normalization independently to RSI produces a momentum reading that is self-referential to recent RSI behavior rather than anchored to universal threshold levels. The signal gate that requires simultaneous Z-score extremes in both price deviation and RSI — not one or the other — creates a logical AND condition that is substantially stricter than conventional oscillator crossovers or single-band-touch triggers. The three ATR shadow tiers, smooth RGB color blending, and gradient bar coloring are supporting visual constructs that serve interpretation rather than adding trading logic. The combination of these elements into a single overlay tool — ComboMA centerline, adaptive Z-score bands, normalized momentum gate, ATR spatial context, and state table — represents an original integration not replicated by any standard built-in indicator. --- Disclaimer This indicator is provided for educational and informational purposes only. It does not constitute financial advice, investment advice, or a recommendation to buy or sell any financial instrument. Trading involves substantial risk of loss. Past performance of any indicator or strategy is not indicative of future results. Always conduct your own research and consult a qualified financial professional before making any trading decisions. -Made with passion by officialjackofalltrades
Penunjuk Pine Script®
oleh officialjackofalltrades
QuantEdge Momentum ML [PRO]🟦 QuantEdge Momentum ML PRO is a k-Nearest Neighbors driven momentum oscillator built on an adaptive machine-learning core. Unlike RSI, Stochastic, or MACD — which apply the same static formula to every asset — QE-ML PRO learns the dual-horizon RSI fingerprints that have historically led to bullish versus bearish outcomes on the exact instrument being traded, then scores the current bar against the N closest historical matches. The result is a non-parametric, self-calibrating oscillator whose decision boundary is shaped by the asset's own behaviour rather than a hard-coded curve. The indicator integrates nine independent layers — feature engine, training sampler, k-NN predictor, WMA signal line, stdev-adjusted OB/OS bands, filtered signal dots, gradient channel, theme-adaptive dashboard, and a nine-theme palette — all rendered on a single, clean oscillator panel. 🟦 HOW THE CORE ENGINE WORKS **Dual-Horizon RSI Feature Vector** Each bar, the Feature Engine computes two RSI values at different lookback windows and smooths both through a shared trend-length WMA: - `rsiFast = WMA(RSI(close, FastPeriod), TrendLength)` — reactive short-term momentum - `rsiSlow = WMA(RSI(close, SlowPeriod), TrendLength)` — structural mid-term momentum The pair `(rsiSlow, rsiFast)` is a 2-dimensional point in RSI feature space. Every training sample stores one such point along with a ±1 label that records whether price rose or fell since the previous sample. Over time the dataset accumulates a cloud of labelled points that maps which RSI states historically preceded up-moves versus down-moves on this exact asset. **Training Sampler — Multi-Trigger Collector** Three collection modes decide when to append a new labelled sample: | Mode | Trigger | Use Case | |---|---|---| | **MA Crossover** | Fast WMA crosses Slow WMA | Clean, sparse samples — classic single-trigger behaviour | | **Periodic** | Every N bars (user-set) | Fills dataset fast on new / low-history charts | | **Hybrid** | MA crossover **OR** every N bars | Richest training set — recommended for fresh assets | Sampling is gated by `barstate.isconfirmed` so the dataset never absorbs unconfirmed values from a flickering live bar. **k-NN Predictor with Adaptive k** On every bar, the predictor computes Euclidean distance in the 2D RSI feature space between the live `(rsiSlow, rsiFast)` point and every historical sample: ``` d = sqrt((rsiSlow_now - rsiSlow_hist)² + (rsiFast_now - rsiFast_hist)²) ``` The K closest historical points vote by summing their ±1 labels. The effective K is resolved adaptively using the classical statistical heuristic: ``` kEff = max(3, min(kMax, floor(sqrt(N)))) ``` This means early bars — when only a handful of samples exist — use a small K, and the value stabilises as the dataset fills. On a fresh chart you never get a noisy prediction from an undersized neighborhood, and on a mature dataset K automatically scales up for smoother output. **Bias Correction — Label-Mean Recentering** Raw k-NN output is biased whenever the label distribution is skewed. On a trending asset, Periodic sampling fills the dataset with mostly +1 (or mostly −1) labels, pushing every prediction off zero. QE-ML PRO subtracts the expected value from the raw sum: ``` prediction = neighborLabelSum − (kEff × meanLabelAcrossDataset) ``` This keeps the mid-level visually centred at zero regardless of how trending the underlying asset has been. The correction is applied on every bar and is what makes the oscillator read cleanly on both sideways and strongly trending markets. **Minimum Sample Gate** Until the dataset has reached the user-defined Minimum Training Samples threshold, the predictor outputs exactly zero. This prevents unreliable readings during the warm-up phase on fresh charts. **FIFO Rotation** The dataset is hard-capped at Max Dataset Size. Once the cap is reached, the oldest sample is discarded on every new insertion — classical rolling window memory that keeps the k-NN scan bounded and the indicator fast on long histories. 🟦 PREDICTION LINE — FIVE VISUAL STYLES All five styles are line-based. Only the visual effect differs — the underlying k-NN math is identical across styles. | Style | Character | |---|---| | **Stratum** | Thick adaptive line with zone-based opacity: solid in extreme zones, semi-transparent in the mid zone. Layered intensity aesthetic — default | | **Neon** | Bright core line with an outer glow halo. Cyberpunk luminous effect, best on dark backgrounds | | **Resonance** | LRI-style gradient line that fades near the midline and brightens toward the rolling extremes | | **Pulse** | Adaptive bull/bear color (above midline = bull, below = bear) plus the WMA signal line. The QE-ML PRO classic look | | **Mono** | Single flat theme-bull line, no gradient, no adaptive coloring. Minimalist single-color silhouette | 🟦 SIGNAL LINE A WMA of the raw prediction output, used as a crossover trigger line in the MACD convention. Crossovers between the prediction and signal line mark momentum regime changes. **Two Visual Styles** | Style | Rendering | |---|---| | **Neon** | Bright core line wrapped in a wider semi-transparent glow halo — cyberpunk aesthetic | | **Flat** | Plain single-color line, no halo, no gradient — minimalist clean look | 🟦 SIGNAL DOTS — FILTERED CROSSOVER MARKERS A two-layer neon cross-dot renderer fires on every Prediction × Signal crossover that survives the active filter mode. Four progressive filters decide which raw crosses reach the chart: | Filter Mode | Behaviour | Signal Count | |---|---|---| | **All Crosses** | Every cross becomes a dot | Highest — noisy on choppy assets | | **Zone Only** | Only crosses inside an OB or OS strip | Mean-reversion triggers — strongest reversal setups | | **Mid Aligned** | Bull dots only above mid, bear dots only below | Trend-following — keeps you on regime side | | **Strict** | Zone Only + Mid Aligned + extra strength multiplier on mid-zone crosses | Fewest signals, highest conviction — default | Two additional gates filter out whipsaws: - **Cooldown (bars)** — minimum spacing between consecutive dots, prevents cluster spam in ranges - **Min Strength** — minimum `|prediction − signal|` separation at the moment of the cross, drops razor-thin crossovers that close back on themselves Each dot is a two-layer plot: an outer glow halo with user-adjustable size and opacity, and a bright solid core on top — independently sized and opacity-controlled so users can dial in the exact visual weight they want. The dot is placed at the actual cross point: bull dots at `min(prediction, signalLine)`, bear dots at `max(prediction, signalLine)`. 🟦 DYNAMIC BANDS — STDEV-ADJUSTED OB / OS ZONES QE-ML PRO does not use fixed 80 / 20 overbought / oversold levels. Instead, the bands adapt to the actual historical range of the prediction output: - **Channel Extremes** — rolling highest / lowest of the prediction over a user-configurable lookback - **Stdev Band** — EMA of rolling standard deviation of the prediction, multiplied by the user's stdev length - **OB Level** = `rangeHi − stdevBand` (inner boundary of the overbought strip) - **OS Level** = `rangeLo + stdevBand` (inner boundary of the oversold strip) The result is a pair of mean-reversion zones that tighten during quiet markets and widen during volatile ones — no manual recalibration needed across assets. The strips are rendered as gradient fills anchored on the live prediction plot, so they only appear visually while the prediction is actually inside the zone. 🟦 CHANNEL GRADIENT Two symmetric gradient fills bracket the mid line. The upper fill stretches from `midValue` to `rangeHi`, the lower fill from `midValue` to `rangeLo`. Opacity fades from full intensity at the extremes to fully transparent at the midline — a visual range meter showing how close the prediction is sitting to its historical boundaries. Colors are pulled from the active Theme. A single opacity slider controls the gradient intensity. 🟦 DASHBOARD — LIVE DATA PANEL A compact 2-column × 7-row monospace panel drawn on the last bar only (zero historical overhead). Every field updates in real time on the live bar. | Row | Left | Right | |---|---|---| | Header | QE-ML PRO | Regime (▲ BULL / ▼ BEAR / ■ NEUTRAL) | | Row 1 | Prediction | Raw value + trend arrow vs previous bar | | Row 2 | Signal | WMA trigger line value | | Row 3 | Strength | 10-block gauge of `|prediction − signal|` normalised against rolling channel | | Row 4 | Zone | OB / MID / OS tag | | Row 5 | Dataset | Sample count / effective k | | Row 6 | Mode | Active Learning Mode (MA Cross / Periodic / Hybrid) | **Theme-Aware Auto-Invert** The panel background scaffolds auto-switch: - **Tropic / Amber / Pastel / Cyber / Gold / Electric / Candy** → dark panel with bright theme accent text - **Midnight / Graphite** → light panel with dark theme accent text This guarantees legibility on every theme without breaking the theme's color identity — because Midnight and Graphite use deep dark bull tones that would drown against a black panel. **Direction via Glyphs, Not Color** Both columns share the same full-strength theme tone. Regime direction is conveyed by `▲ ▼ ■` glyphs rather than color shifts, which keeps the panel reading cleanly even on the most minimal themes. 🟦 NINE COLOR THEMES One theme selector drives every colored component — Prediction line, Signal line, Channel fill, OB / OS strips, Mid-level line, Signal Dots, and Dashboard panel. No per-color manual inputs. | Theme | Character | Bull | Bear | |---|---|---|---| | **Tropic** | Cyan steel + deep orange — electric contrast (default) | Cyan | Deep Orange | | **Amber** | Warm amber + indigo blue — fire tones | Amber | Red | | **Pastel** | Sky blue + soft lavender — cool arctic glow | Sky Blue | Lavender | | **Cyber** | Neon lime + hot crimson — cyber terminal | Neon Green | Crimson | | **Gold** | Bright gold + scarlet — solar warmth | Yellow Gold | Red | | **Electric** | Electric aqua + magenta — high-voltage neon | Aqua | Magenta | | **Candy** | Neon green + hot pink — dark energy pop | Mint Green | Hot Pink | | **Midnight** | Deep navy + dark crimson — dark depth (auto light dashboard) | Navy Blue | Dark Red | | **Graphite** | Near-black + silver grey — monochrome minimal (auto light dashboard) | Near Black | Grey | 🟦 ALERT SYSTEM — TEN CONDITIONS Every alert is gated by its matching "Show X" visibility toggle — if a component is hidden from the chart, its alerts are automatically suppressed. This eliminates the mismatch between visual signals and alert signals that plagues many indicators. | Alert | Condition | Gated By | |---|---|---| | Crossover OB | Prediction crosses above the overbought boundary | Show OB/OS Fill | | Crossunder OB | Prediction crosses back down through OB | Show OB/OS Fill | | Crossover OS | Prediction crosses up through oversold boundary | Show OB/OS Fill | | Crossunder OS | Prediction crosses below the oversold boundary | Show OB/OS Fill | | Crossover Mid | Prediction crosses above the mid line — bullish regime flip | Show Mid Level | | Crossunder Mid | Prediction crosses below the mid line — bearish regime flip | Show Mid Level | | Crossover Signal | Prediction crosses above its WMA signal line (MACD bullish) | Show Signal Line | | Crossunder Signal | Prediction crosses below its WMA signal line (MACD bearish) | Show Signal Line | | Bull Signal Dot | A filtered Bull Signal Dot is plotted (uses Filter Mode + Cooldown + Min Strength) | Show Signal Dots | | Bear Signal Dot | A filtered Bear Signal Dot is plotted (uses Filter Mode + Cooldown + Min Strength) | Show Signal Dots | 🟦 SETTINGS REFERENCE **Visual** - Theme — nine cohesive palettes. Default: Tropic **Machine Learning** - Neighbors (k) — upper bound on neighbors used by the predictor. Default: 100 - Adaptive k — scales k with dataset size using the `floor(sqrt(N))` heuristic. Default: ON - Learning Mode — MA Crossover / Periodic / Hybrid. Default: MA Crossover - Sample Every (bars) — bar interval for the Periodic / Hybrid trigger. Default: 5 - Minimum Training Samples — warm-up gate, predictor outputs zero until reached. Default: 30 - Max Dataset Size — hard FIFO cap. Default: 500 (safe on all timeframes) **Feature Engine** - Trend Length — WMA smoothing applied to both RSI features. Default: 20 - RSI Fast Period — first feature dimension. Default: 5 - RSI Slow Period — second feature dimension. Default: 20 - MA Fast Period — fast WMA for the crossover training trigger. Default: 5 - MA Slow Period — slow WMA for the crossover training trigger. Default: 20 **Prediction Line** - Show Prediction Line — master toggle. Default: ON - Prediction Style — Stratum / Neon / Resonance / Pulse / Mono. Default: Stratum - Prediction Width — 1 to 5. Default: 2 **Signal Line** - Show Signal Line — toggle. Default: ON - Signal Style — Neon / Flat. Default: Neon - Signal Period — WMA length of the signal line. Default: 20 - Signal Width — 1 to 5. Default: 1 **Signal Dots** - Show Signal Dots — toggle. Default: ON - Filter Mode — All Crosses / Zone Only / Mid Aligned / Strict. Default: Strict - Cooldown (bars) — minimum spacing between dots. Default: 5 - Min Strength — minimum `|prediction − signal|` at the cross. Default: 0.5 - Core Dot Size — 1 to 8. Default: 3 - Core Dot Opacity — 0 to 100. Default: 100 - Glow Dot Size — 1 to 12. Default: 8 - Glow Dot Opacity — 0 to 100. Default: 30 **Channel Fill** - Show Channel Fill — toggle. Default: ON - Channel Opacity — 0 to 100. Default: 25 - Channel Lookback — rolling highest / lowest window. Default: 500 **OB / OS Fill** - Show OB/OS Fill — toggle. Default: ON - Zone Stdev Length — stdev window that offsets the OB / OS boundaries inward. Default: 20 **Mid Level** - Show Mid Level — toggle. Default: ON - Mid Level Value — Y-value of the reference line. Default: 0 - Mid Level Style — Solid / Dashed / Dotted. Default: Dashed **Dashboard** - Show Dashboard — toggle. Default: ON - Panel Position — six slots (Top/Middle/Bottom × Right/Left). Default: Middle Right - Panel Text Size — Tiny / Small / Normal / Large. Default: Small **Alerts** - Ten opt-in toggles, one per alert condition. All default: ON 🟦 TRADER PRESETS — SETTINGS BY STYLE QE-ML PRO is volatility-agnostic thanks to the adaptive bands and bias correction, but the reactivity of the predictor scales directly with the feature and sampler parameters. The four presets below are tested starting points you can drop straight into the settings panel — adjust by ±20% to taste. --- ** SCALPER — 1m / 3m / 5m** High-frequency entries, tight stops, many signals per session. Priority is reaction speed — you want the predictor to flip states within a handful of bars of an actual move. | Setting | Value | |---|---| | Trend Length | 10 | | RSI Fast Period | 3 | | RSI Slow Period | 14 | | MA Fast Period | 3 | | MA Slow Period | 10 | | Signal Period | 8 | | Neighbors (k) | 40 | | Adaptive k | ON | | Learning Mode | **Hybrid** | | Sample Every | 2 | | Minimum Training Samples | 20 | | Max Dataset Size | **300** (keeps 1m charts fast) | | Filter Mode | **All Crosses** or Zone Only | | Cooldown | 2 | | Min Strength | 0.3 | | Channel Lookback | 200 | | Zone Stdev Length | 10 | | Prediction Style | Neon or Stratum | **Why:** Low smoothing (Trend=10) + short RSI pair (3/14) keeps the features razor-sharp. Hybrid learning means you never wait for an MA crossover during quiet 1m sessions. Max Dataset capped at 300 protects you from the TradingView per-bar calculation limit on long 1m histories. --- ** DAY TRADER — 15m / 30m / 1H** Balanced reactivity and conviction — the default profile. You want clean crosses without noise spam, and signals that survive the open / close volatility spikes. | Setting | Value | |---|---| | Trend Length | 20 (default) | | RSI Fast Period | 5 (default) | | RSI Slow Period | 20 (default) | | MA Fast Period | 5 (default) | | MA Slow Period | 20 (default) | | Signal Period | 20 (default) | | Neighbors (k) | 100 (default) | | Adaptive k | ON | | Learning Mode | **MA Crossover** (default) | | Minimum Training Samples | 30 (default) | | Max Dataset Size | 500 (default) | | Filter Mode | **Strict** (default) | | Cooldown | 5 (default) | | Min Strength | 0.5 (default) | | Channel Lookback | 500 (default) | | Zone Stdev Length | 20 (default) | | Prediction Style | Stratum (default) | **Why:** Every default value was tuned for this range. Strict filter + 5-bar cooldown keeps the dot count honest on a 30m chart. MA Crossover sampling gives you clean sparse data since 15m+ charts already have enough crossover events. --- ** SWING TRADER — 4H / 1D** Lower signal frequency, higher conviction per signal. You're holding for days or weeks — every dot needs to mean something. | Setting | Value | |---|---| | Trend Length | 30 | | RSI Fast Period | 7 | | RSI Slow Period | 30 | | MA Fast Period | 7 | | MA Slow Period | 30 | | Signal Period | 30 | | Neighbors (k) | 150 | | Adaptive k | ON | | Learning Mode | MA Crossover | | Minimum Training Samples | 50 | | Max Dataset Size | 800 | | Filter Mode | **Strict** | | Cooldown | 10 | | Min Strength | 0.8 | | Channel Lookback | 800 | | Zone Stdev Length | 30 | | Prediction Style | Stratum or Mono | **Why:** Longer feature periods mean the predictor only moves on genuine structural shifts. Larger k (150) + bigger dataset (800) gives the k-NN vote a wider base so outliers don't flip the sign. Cooldown of 10 bars on a 4H chart = 40 hours minimum between dots — exactly what a swing trader wants. --- ** POSITION / LONG-TERM — 1D / 1W / 1M** Macro regime detection. You're looking for the handful of generational setups per year — noise is the enemy. | Setting | Value | |---|---| | Trend Length | 50 | | RSI Fast Period | 10 | | RSI Slow Period | 40 | | MA Fast Period | 10 | | MA Slow Period | 40 | | Signal Period | 40 | | Neighbors (k) | 200 | | Adaptive k | ON | | Learning Mode | **Hybrid** | | Sample Every | 3 | | Minimum Training Samples | 40 | | Max Dataset Size | 1000 | | Filter Mode | **Strict** | | Cooldown | 15 | | Min Strength | 1.0 | | Channel Lookback | 1000 | | Zone Stdev Length | 40 | | Prediction Style | Mono or Pulse | **Why:** Weekly and monthly charts have few crossover events per year — without Hybrid mode the dataset starves. Sample Every = 3 on a weekly chart means one sample every 3 weeks, which is plenty of structural density. Min Strength 1.0 filters out every shallow cross — you only see dots on generational momentum inflections. --- **Tuning Tip** If the predictor feels **too reactive** → increase Trend Length and Signal Period by 25%, raise Cooldown. If the predictor feels **too sluggish** → switch Learning Mode to Hybrid, decrease Min Samples, lower Trend Length. If the dashboard shows **Dataset N is stuck low** → switch Learning Mode from MA Crossover to Hybrid — crossover events are too rare on your current settings. If you see **runtime / timeout errors** on long histories → drop Max Dataset Size to 300 and Channel Lookback to 300. 🟦 COMPATIBILITY Works on all asset classes and all timeframes in TradingView Pine Script v6. - **Crypto** — Spot, futures, perpetual contracts - **Forex** — All pairs - **Equities** — Stocks, ETFs, indices - **Commodities** — Metals, energy, agriculture - **Timeframes** — 1m through Monthly The k-NN engine learns each asset's own RSI fingerprint distribution, and the stdev-adjusted bands auto-scale to the volatility of that distribution, so the indicator is truly self-calibrating across assets and timeframes — no manual recalibration required. 🟦 TECHNICAL NOTES - Pine Script v6 - No repainting — training samples are gated by `barstate.isconfirmed` so the dataset never absorbs unconfirmed live-bar values - Dataset is hard-capped via FIFO rotation; no unbounded memory growth - Dashboard renders only on `barstate.islast` — zero historical overhead - All drawing objects are stateless plots (no label / box / line object pools), so `max_*_count` limits cannot be exceeded - k-NN distance pass is O(N), sort is O(N log N), both bounded by Max Dataset Size - Default Max Dataset Size of 500 is tuned to stay within TradingView's per-bar calculation budget on histories up to ~50,000 bars - Bias correction uses a single extra accumulator pass during the distance sweep — no performance penalty 🟦 DISCLAIMER This indicator is provided for educational and informational purposes only. It does not constitute financial advice. Past performance does not guarantee future results. The k-NN engine learns from historical patterns, but markets do not guarantee that historical patterns will repeat. Always conduct your own analysis and apply proper risk management.
Penunjuk Pine Script®
oleh a_jabbaroff
24
Swing + Value Setup [Marcos]Swing + Value Setup — Descripción para TradingView Título sugerido Swing + Value Setup — Multi-Filter Entry Signal Descripción (inglés — recomendado para mayor alcance) 🎯 What is this indicator? Swing + Value Setup is a multi-condition entry filter designed for swing traders looking for high-quality setups in stocks with strong technical and structural foundations. Instead of relying on a single signal, this indicator requires 6 simultaneous conditions to be met before printing an entry label — dramatically reducing false signals and noise. It also features a real-time status panel that shows exactly which conditions are passing or failing on any given bar, so you always know how close a setup is to triggering. ⚙️ How it works The indicator combines trend, momentum, volume, and structure analysis into a single unified signal: ✅ 6 Required Conditions (all must be true simultaneously): Price above EMA 200 — confirms the stock is in a long-term uptrend Supertrend bullish — active trend filter, eliminates choppy/sideways markets RSI between 40–55 — entry during healthy pullback, not extreme oversold MACD signal — bullish crossover OR histogram rising below zero (momentum recovering) OBV above its EMA — confirms institutional accumulation behind the move Pullback to EMA 21 or EMA 50 (±1.5%) — optimal entry zone, not chasing price ⭐ High Conviction Bonus: When a bullish RSI divergence is also detected (price making lower lows while RSI makes higher lows), the label upgrades to a High Conviction signal — historically the strongest setups. 📊 Visual elements EMA 21 / 50 / 200 plotted directly on price Supertrend line changes color with trend direction Green background shading when a valid setup is active Brighter shading for high conviction entries Labels printed at signal candles (standard ✅ or high conviction 🎯) Status table (top-right corner) showing live ✅/❌ for each condition 🔔 Built-in Alerts (3 total) AlertTriggerSetup Swing/ValueAll 6 conditions met for the first timeSetup ALTA CONVICCIÓN ⭐Full setup + RSI divergence confirmedDivergencia RSI BullishBullish divergence in uptrend (early warning) Set alerts from the indicator menu → Add Alert → select the condition. 🕐 Recommended Timeframes TimeframePurposeWeeklyOverall bias and macro structureDailyPrimary signal timeframe (recommended)4H / 1HEntry timing and fine-tuning Best results on Daily charts for swing positions of 5–30 days. 📐 Trade Management (suggested) Stop Loss: Below the signal candle low or EMA 50 Target 1: Prior resistance / VPVR high-volume node Target 2: Fibonacci 1.272 or 1.618 extension Minimum R:R: 1:2.5 ⚠️ Disclaimer This indicator is a technical analysis tool only. It does not constitute financial advice. Always manage your risk, use stop losses, and do your own research before entering any trade. Past performance of any indicator does not guarantee future results. Descripción (español — versión alternativa) 🎯 ¿Qué es este indicador? Swing + Value Setup es un filtro de entrada multi-condición diseñado para swing traders que buscan setups de alta calidad en acciones con estructura técnica sólida. En lugar de depender de una sola señal, el indicador exige que 6 condiciones se cumplan simultáneamente antes de generar una señal — reduciendo drásticamente las falsas entradas y el ruido del mercado. Incluye un panel de estado en tiempo real que muestra exactamente qué condiciones están activas o fallando en cualquier vela, para que siempre sepas qué tan cerca está un setup de activarse. ⚙️ Cómo funciona ✅ 6 Condiciones obligatorias (todas deben cumplirse a la vez): Precio sobre EMA 200 — confirma tendencia alcista de largo plazo Supertrend alcista — filtra mercados laterales y tendencias bajistas RSI entre 40 y 55 — entrada en pullback sano, sin sobreventa extrema Señal MACD — cruce alcista O histograma subiendo bajo cero OBV sobre su media — confirma acumulación institucional detrás del movimiento Pullback a EMA 21 o EMA 50 (±1.5%) — zona de entrada óptima sin perseguir precio ⭐ Bonus Alta Convicción: Cuando además se detecta una divergencia bullish en RSI (precio haciendo mínimos más bajos mientras el RSI hace mínimos más altos), la señal se convierte en Alta Convicción — históricamente los setups más fuertes. 🔔 Alertas incluidas Setup Swing/Value — cuando se cumplen las 6 condiciones Setup Alta Convicción ⭐ — setup completo + divergencia RSI Divergencia RSI Bullish — aviso temprano de posible giro ⚠️ Aviso legal Este indicador es únicamente una herramienta de análisis técnico. No constituye asesoramiento financiero. Gestiona siempre tu riesgo y realiza tu propio análisis antes de operar. swing trading value ema supertrend rsi macd obv multi-condition stocks entry signal divergence trend following pullback screener alerts
Penunjuk Pine Script®
oleh hardcoresporto
MULTIVITAMIN1. What is MULTIVITAMIN? MULTIVITAMIN is a custom-built, open-source algorithmic scalping indicator designed for TradingView. Its primary goal is to capture high-probability momentum trades by combining pure Price Action (PA) mechanics with advanced trend and volatility filters, specifically engineered to avoid "chop" (ranging/flat markets) and deliver healthy, actionable signals. 2. What does it cover? (Core Modules) Price Action Engine: The core of the system. It detects real-time structural market shifts by identifying Engulfing patterns, Order Blocks (OB) with volume confirmation, and Fair Value Gaps (FVG). Trend & Momentum Filters: Utilizes a multi-timeframe Hull Moving Average (HMA) for signal smoothing, a 50-period EMA for macro trend direction, and an ADX filter to ensure the market has sufficient momentum before entering a trade. Pro Walls (Anti-Chop System): Features advanced, optional defensive mechanisms: an ATR-based volatility filter (ensuring candle size is larger than average market noise) and an EMA slope filter (ensuring the trend line is actually pointing up or down, not moving sideways). Volume Supported Breakout (BKR): An optional hybrid feature that looks for extreme volume spikes (compared to a 20-period SMA) combined with local high/low breakouts. Lifecycle Management: A built-in state machine (Idle, Long, Short) that tracks the trade's status, preventing overlapping entries and managing exits based on user-defined criteria. 3. What is its operational logic? Step 1: Scanning & Setup: The script continuously monitors price action for base entry conditions. Step 2: The Gauntlet (Filtering): A setup must pass through all active user filters (EMA, ADX, Volatility, etc.) before being validated. Step 3: State Execution: If all conditions align, the internal bot state shifts from 0 (Idle) to 1 or -1, plotting an ENTER shape on the chart and triggering an external webhook alert. Step 4: The Exit: The bot remains in this state until a valid exit condition (like a reverse PA signal) is met. 4. ⚠️ CRITICAL: How to Set Up Alerts (The Anti-Repainting Rule) ⚠️ If you are using the "Exit on Reverse Signal" (Ters Sinyalde Çık) feature in the settings, you MUST configure all your TradingView alerts (both ENTER and EXIT alerts) to trigger "Once Per Bar Close". Why? If you set them to "Once Per Bar" (anlık tetikleme), intra-bar price fluctuations (wicks) will trigger premature exit/entry orders to your exchange before the candle officially closes, leading to repainting on the chart and ghost orders in your account. Always wait for the candle to close to confirm the structural shift!
Penunjuk Pine Script®
oleh lisabyco
1
Liquidity Architecture Scanner [JOAT]Liquidity Architecture Scanner Introduction Liquidity Architecture Scanner is an open-source overlay indicator that maps equal high and equal low liquidity pools — price levels where two consecutive highs or lows are within an adaptive tolerance of each other — into persistent box-based zones with session-colored borders, RSI-strength opacity, intrazone volume POC lines computed from lower-timeframe data, retest tracking with progressive border brightening, and volume-filtered sweep labels. The system continuously monitors active zones for retests and sweeps, maintains live sweep counts on the dashboard, and applies a gradient barcolor that deepens when price is inside or approaching a zone. The core problem this indicator addresses is that equal highs and equal lows represent clusters of resting limit orders placed by traders defending the same price twice — the institutional order flow concept of liquidity pools. When price sweeps through these levels, it typically triggers those orders and may reverse sharply. Standard equal-level detection tools use a fixed pip tolerance, which breaks down across instruments and timeframes. The LAS uses an EMA-normalized adaptive tolerance derived from recent bar-to-bar variance, making the detection self-calibrating. Layering a RSI filter ensures the equal high is detected above a bull momentum threshold and the equal low is detected below a bear threshold — filtering out levels formed in the wrong momentum context. Core Concepts 1. Adaptive Tolerance The tolerance level that determines whether two consecutive highs (or lows) are "equal" is computed from the EMA of average bar-to-bar absolute variance: barVar = avg(|high - high |, |low - low |), smoothed over the configurable EMA length. This variance-normalized tolerance automatically tightens in low-volatility environments and widens in high-volatility ones, ensuring equal-level detection remains meaningful across instruments, timeframes, and market regimes without manual parameter adjustment. 2. RSI Momentum Filter An equal high only registers if the RSI is above the bull threshold (default 55) at detection time. An equal low only registers if the RSI is below the bear threshold (default 45). This dual-gate ensures that EQH zones are detected during upside momentum — when resting sell orders above the market are the relevant liquidity pool — and EQL zones are detected during downside momentum. Equal highs formed with a weak RSI below 55 represent a different structural context and are excluded. 3. Lower-Timeframe Volume POC The indicator requests intrabar close and volume data from a lower timeframe via request.security_lower_tf(). For each zone's price range, the algorithm distributes intrabar volume into bins across the zone's height and identifies the bin with the highest cumulative volume — the Point of Control (POC). A dotted line is drawn at the POC price inside each zone box. This provides a volume-based reference level within the zone: the price at which the most trading activity occurred inside the equal-level band. Traders can use the POC as a more precise entry or target reference than the zone midpoint. 4. Session-Colored Borders and RSI Opacity Each zone's birth session is stored and used to color its border: London zones receive a blue border (#60a5fa), NY zones a pink border (#f472b6), Asia zones a green border (#34d399), and off-hours zones a lighter gray. The zone fill opacity is derived from the RSI distance from the relevant threshold at the time of detection: the farther RSI is from the threshold, the more opaque the fill, communicating higher-conviction detections with stronger visual presence. 5. Retest Tracking and Sweep Logic Each bar, the indicator checks whether price has entered a zone it was previously outside of. On first retest entry, the border width and brightness increase. On subsequent retests, the border continues brightening and a "RETEST n" label fires at the zone edge. When price closes fully through a zone — above the top for EQH, below the bottom for EQL — the zone is marked as swept, the sweep counter increments, and optionally a "SWEPT" label appears (subject to a volume filter that requires volume > SMA(20) * 1.3 for label display). Features Adaptive EMA-Normalized Tolerance: Equal-level detection threshold adjusts automatically to recent bar-to-bar variance, remaining calibrated across all instruments and timeframes RSI Momentum Gate: EQH only detected when RSI is above bull threshold; EQL only detected when RSI is below bear threshold — filters out levels formed in wrong momentum context Lower-TF Volume POC: Intrabar volume profiling using request.security_lower_tf() identifies the highest-volume price bin inside each zone Box-Based Zone Rendering: Solid box fills with configurable session-colored borders and RSI-strength opacity Session-Colored Borders: London blue / NY pink / Asia green — session context encoded directly in the zone visual RSI-Strength Opacity: Fill transparency inversely proportional to RSI distance from threshold — stronger momentum detections are more visually prominent Zone Midpoint Reference Line: Dotted midpoint line inside each zone for quick visual reference of the level center Retest Tracking: Progressive border brightening and border width increase with each confirmed retest entry; RETEST n label fires on each new entry Volume-Filtered Sweep Labels: SWEPT labels appear when price closes through a zone, optionally filtered to only show when volume exceeds 1.3x the SMA(20) Formation Signals: Small EQH/EQL labels fire at the bar of each confirmed zone detection Proximity Approach Markers: Diamond markers when price first enters within ATR * proximity buffer of a zone edge Gradient Bar Coloring: Bars deepen in zone color when inside a zone, lighter when approaching, trend-tinted otherwise Zone Expiry: Zones older than the configurable max age are automatically removed 10-Row Dashboard: Liquidity trend direction, active EQH/EQL counts, sweep counts per side, in-zone state, session, RSI, adaptive tolerance level 6 Alertconditions: Zone formation, zone entry, and liquidity trend flip alerts for both EQH and EQL Input Parameters Equal Levels: EQ Tolerance Multiplier: Scales the adaptive tolerance — higher values allow wider "equal" windows (default 0.05) Tolerance EMA Length: Smoothing period for the variance normalization EMA (default 500) RSI Length: RSI lookback for the momentum filter (default 14) RSI Bull Threshold: Minimum RSI for EQH detection (default 55) RSI Bear Threshold: Maximum RSI for EQL detection (default 45) Zone Max Age (bars): Zones older than this are deleted (default 300) Proximity Buffer (ATR): Approach detection buffer as ATR multiple (default 0.5) Volume Profile: Lower TF (Volume): Intrabar timeframe for volume profiling — must be below the chart timeframe (default 3) POC Bin Count: Number of price bins in the volume profile (default 7) Visuals: Toggles for POC line, zone midline, labels, formation signals, sweep labels, sweep volume filter, and dashboard EQH Color (default violet #a78bfa), EQL Color (default teal #34d399) How to Use This Indicator Primary Setup — Liquidity Sweep Entry: When price sweeps through a zone and a SWEPT label fires, watch for a reversal candle on a lower timeframe. The sweep has collected the resting orders; the price may reverse sharply. Enter on the first opposing candle after the sweep close with a stop beyond the swept level. Retest Entry: When price returns to a zone from the opposite direction after having moved away, watch for the RETEST label. Zones that have survived multiple retests (bright borders, high retest count) with no sweep are demonstrating price respect. Enter at the zone edge on the retest candle, stop beyond the far edge. POC as Precision Reference: The POC line marks where the most intrabar volume concentrated inside the zone. If price is approaching from below an EQL zone, the POC is a more precise target than the zone top. If price is inside the zone and stalling at the POC, this may be the key inflection level. Liquidity Trend: The dashboard Liq Trend shows BULLISH after an EQH sweep (sell-side liquidity was taken, likely pushing price up) and BEARISH after an EQL sweep (buy-side liquidity taken). Using this as a directional bias filter on lower-timeframe setups adds context from the liquidity architecture. Indicator Limitations Equal level detection requires consecutive bars with nearly identical highs or lows. In fast, impulsive markets where equal highs/lows rarely form, zone detection frequency will be low regardless of tolerance setting Lower-timeframe volume profiling adds security calls per bar. On very high-frequency timeframes or instruments with large lower-TF arrays, this may slow indicator rendering The RSI filter will prevent zone detection in any momentum condition that does not meet the threshold, which means zones formed during neutral RSI readings (45-55) are not mapped — these may still represent meaningful liquidity Sweep detection requires a confirmed close through the zone boundary. Intrabar wicks that sweep through a level but close back inside will not register as a sweep, despite triggering orders in live trading Zone expiry by age removes all zones older than the max age parameter regardless of whether they remain structurally significant — very long-lived confluence levels may be deleted in trend-persistent market conditions Originality Statement This indicator is original in its adaptive EMA-normalized tolerance, RSI-gated liquidity detection, lower-timeframe volume POC integration, and progressive retest border feedback system. The publication is justified because: EMA-normalized adaptive tolerance makes equal-level detection self-calibrating across instruments and timeframes without manual adjustment — a significant improvement over fixed-pip tolerance approaches RSI-gated zone detection filters equal levels by momentum context, ensuring only liquidity pools formed in the correct directional bias are mapped — a filtering mechanism not present in standard equal-level tools Lower-timeframe volume POC computation inside each zone adds a volume-based precision reference that identifies the intrazone price with the highest transaction concentration — combining liquidity structure with volume analysis in a single overlay Progressive border brightening as a retest counter provides an ever-updating interaction history on the zone visual itself, eliminating the need for a separate touch-count display The sweep counter and liquidity trend directional state provide a market microstructure bias indicator derived purely from liquidity pool dynamics, without using any traditional trend filter Disclaimer This indicator is provided for educational and informational purposes only and does not constitute financial advice or a recommendation to buy or sell any financial instrument. Past performance of any pattern or signal does not guarantee future results. All trading involves substantial risk. Always use proper risk management and conduct your own independent analysis. — Made with passion by officialjackofalltrades
Penunjuk Pine Script®
oleh officialjackofalltrades
2