Multi Momentum 10/21/42/63 — Histogram + 2xSMAMY MM INDICATOR INDIRED BY KARADI
It averages four rate-of-change snapshots of price, all anchored at today’s close.
If “Show as %” is on, the value is multiplied by 100.
Each term is a simple momentum/ROC over a different lookback.
Combining 10, 21, 42, 63 bars blends short, medium, and intermediate horizons into one number.
Positive MM → average upward pressure across those horizons; negative MM → average downward pressure.
Why those lengths?
They roughly stack into ~2× progression (10→21≈2×10, 21→42=2×21, 63≈1.5×42). That creates a “multi-scale” momentum that’s less noisy than a single fast ROC but more responsive than a long ROC alone.
How to read the panel
Gray histogram = raw Multi-Momentum value each bar.
SMA Fast/Slow lines (defaults 12 & 26 over the MM values) = smoothing of the histogram to show the trend of momentum itself.
Typical signals
Zero-line context:
Above 0 → bullish momentum regime on average.
Below 0 → bearish regime.
Crosses of SMA Fast & Slow: momentum trend shifts (fast above slow = improving momentum; fast below slow = deteriorating).
Histogram vs SMA lines: widening distance suggests strengthening momentum; narrowing suggests momentum is fading.
Divergences: price makes a new high/low but MM doesn’t → potential exhaustion.
Compared to a classic ROC
A single ROC(20) is very sensitive to that one window.
MM averages several windows, smoothing idiosyncrasies (e.g., a one-off spike 21 bars ago) and reducing “lookback luck.”
Settings & customization
Lookbacks (10/21/42/63): you can tweak for your asset/timeframe; the idea is to mix short→medium horizons.
Percent vs raw ratio: percent is easier to compare across symbols.
SMA lengths: shorter = more reactive but choppier; longer = smoother but slower.
Practical tips
Use regime + signal: trade longs primarily when MM>0 and fast SMA>slow SMA; consider shorts when MM<0 and fast
Cari dalam skrip untuk "one一季度财报"
Pairs Trading Scanner [BackQuant]Pairs Trading Scanner
What it is
This scanner analyzes the relationship between your chart symbol and a chosen pair symbol in real time. It builds a normalized “spread” between them, tracks how tightly they move together (correlation), converts the spread into a Z-Score (how far from typical it is), and then prints clear LONG / SHORT / EXIT prompts plus an at-a-glance dashboard with the numbers that matter.
Why pairs at all?
Markets co-move. When two assets are statistically related, their relationship (the spread) tends to oscillate around a mean.
Pairs trading doesn’t require calling overall market direction you trade the relative mispricing between two instruments.
This scanner gives you a robust, visual way to find those dislocations, size their significance, and structure the trade.
How it works (plain English)
Step 1 Pick a partner: Select the Pair Symbol to compare against your chart symbol. The tool fetches synchronized prices for both.
Step 2 Build a spread: Choose a Spread Method that defines “relative value” (e.g., Log Spread, Price Ratio, Return Difference, Price Difference). Each lens highlights a different flavor of divergence.
Step 3 Validate relationship: A rolling Correlation checks if the pair is moving together enough to be tradable. If correlation is weak, the scanner stands down.
Step 4 Standardize & score: The spread is normalized (mean & variability over a lookback) to form a Z-Score . Large absolute Z means “stretched,” small means “near fair.”
Step 5 Signals: When the Z-Score crosses user-defined thresholds with sufficient correlation , entries print:
LONG = long chart symbol / short pair symbol,
SHORT = short chart symbol / long pair symbol,
EXIT = mean reversion into the exit zone or correlation failure.
Core concepts (the three pillars)
Spread Method Your definition of “distance” between the two series.
Guidance:
Log Spread: Focuses on proportional differences; robust when prices live on different scales.
Price Ratio: Classic relative value; good when you care about “X per Y.”
Return Difference: Emphasizes recent performance gaps; nimble for momentum-to-mean plays.
Price Difference: Straight subtraction; intuitive for similar-scale assets (e.g., two ETFs).
Correlation A rolling score of co-movement. The scanner requires it to be above your Min Correlation before acting, so you’re not trading random divergence.
Z-Score “How abnormal is today’s spread?” Positive = chart richer than pair; negative = cheaper. Thresholds define entries/exits with transparent, statistical context.
What you’ll see on the chart
Correlation plot (blue line) with a dashed Min Correlation guide. Above the line = green zone for signals; below = hands off.
Z-Score plot (white line) with colored, dashed Entry bands and dotted Exit bands. Zero line for mean.
Normalized spread (yellow) for a quick “shape read” of recent divergence swings.
Signal markers :
LONG (green label) when Z < –Entry and corr OK,
SHORT (red label) when Z > +Entry and corr OK,
EXIT (gray label) when Z returns inside the Exit band or correlation drops below the floor.
Background tint for active state (faint green for long-spread stance, faint red for short-spread stance).
The two built-in dashboards
Statistics Table (top-right)
Pair Symbol Your chosen partner.
Correlation Live value vs. your minimum.
Z-Score How stretched the spread is now.
Current / Pair Prices Real-time anchors.
Signal State NEUTRAL / LONG / SHORT.
Price Ratio Context for ratio-style setups.
Analysis Table (bottom-right)
Avg Correlation Typical co-movement level over your window.
Max |Z| The recent extremes of dislocation.
Spread Volatility How “lively” the spread has been.
Trade Signal A human-readable prompt (e.g., “LONG A / SHORT B” or “NO TRADE” / “LOW CORRELATION”).
Risk Level LOW / MEDIUM / HIGH based on current stretch (absolute Z).
Signals logic (plain English)
Entry (LONG): The spread is unusually negative (chart cheaper vs pair) and correlation is healthy. Expect mean reversion upward in the spread: long chart, short pair.
Entry (SHORT): The spread is unusually positive (chart richer vs pair) and correlation is healthy. Expect mean reversion downward in the spread: short chart, long pair.
Exit: The spread relaxes back toward normal (inside your exit band), or correlation deteriorates (relationship no longer trusted).
A quick, repeatable workflow
1) Choose your pair in context (same sector/theme or known macro link). Think: “Do these two plausibly co-move?”
2) Pick a spread lens that matches your narrative (ratio for relative value, returns for short-term performance gaps, etc.).
3) Confirm correlation is above your floor no corr, no trade.
4) Wait for a stretch (Z beyond Entry band) and a printed LONG / SHORT .
5) Manage to the mean (EXIT band) or correlation failure; let the scanners’ state/labels keep you honest.
Settings that matter (and why)
Spread Method Defines the “mispricing” you care about.
Correlation Period Longer = steadier regime read, shorter = snappier to regime change.
Z-Score Period The window that defines “normal” for the spread; it sets the yardstick.
Use Percentage Returns Normalizes series when using return-based logic; keep on for mixed-scale assets.
Entry / Exit Thresholds Set your stretch and your target reversion zone. Wider entries = rarer but stronger signals.
Minimum Correlation The gatekeeper. Raising it favors quality over quantity.
Choosing pairs (practical cheat sheet)
Same family: two index ETFs, two oil-linked names, two gold miners, two L1 tokens.
Hedge & proxy: stock vs. sector ETF, BTC vs. BTC index, WTI vs. energy ETF.
Cross-venue or cross-listing: instruments that are functionally the same exposure but price differently intraday.
Reading the cues like a pro
Divergence shape: The yellow normalized spread helps you see rhythm fast spike and snap-back versus slow grind.
Corr-first discipline: Don’t fight the “Min Correlation” line. Good pairs trading starts with a relationship you can trust.
Exit humility: When Z re-centers, let the EXIT do its job. The edge is the journey to the mean, not overstaying it.
Frequently asked (quick answers)
“Long/Short means what exactly?”
LONG = long the chart symbol and short the pair symbol.
SHORT = short the chart symbol and long the pair symbol.
“Do I need same price scales?” No. The spread methods normalize in different ways; choose the one that fits your use case (log/ratio are great for mixed scales).
“What if correlation falls mid-trade?” The scanner will neutralize the state and print EXIT . Relationship first; trade second.
Field notes & patterns
Snap-back days: After a one-sided session, return-difference spreads often flag cleaner intraday mean reversions.
Macro rotations: Ratio spreads shine during sector re-weights (e.g., value vs. growth ETFs); look for steady corr + elevated |Z|.
Event bleed-through: If one symbol reacts to news and its partner lags, Z often flags a high-quality, short-horizon re-centering.
Display controls at a glance
Show Statistics Table Live state & key numbers, top-right.
Show Analysis Table Context/risk read, bottom-right.
Show Correlation / Spread / Z-Score Toggle the sub-charts you want visible.
Show Entry/Exit Signals Turn markers on/off as needed.
Coloring Adjust Long/Short/Neutral and correlation line colors to match your theme.
Alerts (ready to route to your workflow)
Pairs Long Entry Z falls through the long threshold with correlation above minimum.
Pairs Short Entry Z rises through the short threshold with correlation above minimum.
Pairs Trade Exit Z returns to neutral or the relationship fails your correlation floor.
Correlation Breakdown Rolling correlation crosses your minimum; relationship caution.
Final notes
The scanner is designed to keep you systematic: require relationship (correlation), quantify dislocation (Z-Score), act when stretched, stand down when it normalizes or the relationship degrades. It’s a full, visual loop for relative-value trading that stays out of your way when it should and gets loud only when the numbers line up.
OTFThis indicator identifies One Time Framing conditions directly on the chart. One Time Framing occurs when a bar’s high is higher than the previous bar’s high without breaking the previous low (for bullish OTF), or when a bar’s low is lower than the previous bar’s low without breaking the previous high (for bearish OTF).
This tool helps traders to spot continuation moves and trend confirmation within any timeframe. Customizable inputs allow users to select the desired time interval and highlight both bullish and bearish One Time Framing sequences.
How to use:
Apply this indicator on any timeframe to automatically highlight OTF events.
Use the visual markers to identify trend continuations or early reversals.
Adjust the settings panel for color preferences and OTF sensitivity.
No trading signals or strategies are provided; this indicator is strictly for identifying the OTF structure in market price action. Suitable for all levels of traders interested in market structure analysis.
Ighodalo Gold - CRT (Candles are ranges theory)This indicator is designed to automatically identify and display CRT (Candles are Ranges Theory) Candles on your chart. It draws the high and low of the identified range and extends them until price breaks out, providing clear levels of support and resistance.
The Candles are Ranges Theory (CRT) concept was originally developed and shared by a trader named Romeotpt (Raid). All credit for the trading methodology goes to him. This indicator simply makes spotting these specific candles easier.
What is a CRT Candle & How Is It Used?
A CRT candle is a single candle that has both the highest high AND the lowest low over a user-defined period. It is identified by analysing a block of recent candles and finding the one candle that contains the entire price range of that block.
Once a CRT candle is formed, its high and low act as an accumulation range.
A break above or below this range is the manipulation phase.
A reclaim of the range (price closing back inside) signifies a potential distribution phase.
On higher timeframes, this sequence can be interpreted as:
Candle 1: Accumulation
Candle 2: Manipulation
Candle 3: Distribution
Reversal (Turtle Soup):
A sweep of the high or low, followed by a quick reclaim (price closing back inside the range), can signify a reversal. According to the theory’s originator, Romeo, this reversal pattern is called “turtle soup.”
After a bearish reversal at the high, the target becomes the CRT low.
After a bullish reversal at the low, the target becomes the CRT high.
How to Use This Indicator
The indicator is flexible and can be adapted to your trading style. The most important settings are:
Max Lookback Period: Number of past candles ("n") the indicator checks within to find a CRT.
CRT Timeframe:
Select a timeframe (e.g., 1H): The indicator will look at the higher timeframe you selected and plot the most recent CRT range from that timeframe onto your current chart. This is useful for multi-timeframe analysis.
Enable Overlapping CRTs:
False (unchecked): Shows only one active CRT range at a time. The indicator won’t look for a new one until the current range is broken.
True (checked): Constantly searches for and displays all CRT ranges it finds, allowing multiple ranges to appear on the chart simultaneously.
Disclaimer & Notes
-This is a visualisation tool and not a standalone trading signal. Always use it alongside your own analysis and risk management strategy.
-All credit for the "Candles are Ranges Theory" (CRT) concept goes to its creator, Romeotpt (Raid).
"On the journey to the opposite side of the range, price often provides multiple turtle soup entry opportunities. Follow their footprints." — Raid, 2025
Volume Bubbles & Liquidity Heatmap [LuxAlgo]The Volume Bubbles & Liquidity Heatmap indicator highlights volume and liquidity clearly and precisely with its volume bubbles and liquidity heat map, allowing to identify key price areas.
Customize the bubbles with different time frames and different display modes: total volume, buy and sell volume, or delta volume.
🔶 USAGE
The primary objective of this tool is to offer traders a straightforward method for analyzing volume on any selected timeframe.
By default, the tool displays buy and sell volume bubbles for the daily timeframe over the last 2,000 bars. Traders should be aware of the difference between the timeframe of the chart and that of the bubbles.
The tool also displays a liquidity heat map to help traders identify price areas where liquidity accumulates or is lacking.
🔹 Volume Bubbles
The bubbles have three possible display modes:
Total Volume: Displays the total volume of trades per bubble.
Buy & Sell Volume: Each bubble is divided into buy and sell volume.
Delta Volume: Displays the difference between buy and sell volume.
Each bubble represents the trading volume for a given period. By default, the timeframe for each bubble is set to daily, meaning each bubble represents the trading volume for each day.
The size of each bubble is proportional to the volume traded; a larger bubble indicates greater volume, while a smaller bubble indicates lower volume.
The color of each bubble indicates the dominant volume: green for buy volume and red for sell volume.
One of the tool's main goals is to facilitate simple, clear, multi-timeframe volume analysis.
The previous chart shows Delta Volume bubbles with various chart and bubble timeframe configurations.
To correctly visualize the bubbles, traders must ensure there is a sufficient number of bars per bubble. This is achieved by using a lower chart timeframe and a higher bubble timeframe.
As can be seen in the image above, the greater the difference between the chart and bubble timeframes, the better the visualization.
🔹 Liquidity Heatmap
The other main element of the tool is the liquidity heatmap. By default, it divides the chart into 25 different price areas and displays the accumulated trading volume on each.
The image above shows a 4-hour BTC chart displaying only the liquidity heatmap. Traders should be aware of these key price areas and observe how the price behaves in them, looking for possible opportunities to engage with the market.
The main parameters for controlling the heatmap on the settings panel are Rows and Cell Minimum Size. Rows modifies the number of horizontal price areas displayed, while Cell Minimum Size modifies the minimum size of each liquidity cell in each row.
As can be seen in the above BTC hourly chart, the cell size is 24 at the top and 168 at the bottom. The cells are smaller on top and bigger on the bottom.
The color of each cell reflects the liquidity size with a gradient; this reflects the total volume traded within each cell. The default colors are:
Red: larger liquidity
Yellow: medium liquidity
Blue: lower liquidity
🔹 Using Both Tools Together
This indicator provides the means to identify directional bias and market timing.
The main idea is that if buyers are strong, prices are likely to increase, and if sellers are strong, prices are likely to decrease. This gives us a directional bias for opening long or short positions. Then, we combine our directional bias with price rejection or acceptance of key liquidity levels to determine the timing of opening or closing our positions.
Now, let's review some charts.
This first chart is BTC 1H with Delta Weekly Bubbles. Delta Bubbles measure the difference between buy and sell volume, so we can easily see which group is dominant (buyers or sellers) and how strong they are in any given week. This, along with the key price areas displayed by the Liquidity Heatmap, can help us navigate the markets.
We divided market behavior into seven groups, and each group has several bubbles, numbered from 1 to 17.
Bubbles 1, 2, and 3: After strong buyers market consolidates with positive delta, prices move up next week.
Bubbles 3, 4, and 5: Strength changes from buyers to sellers. Next week, prices go down.
Bubbles 6 and 7: The market trades at higher prices, but with negative delta. Next week, prices go down.
Bubbles 7, 8, and 9: Strength changes from sellers to buyers. Next weeks (9 and 10), prices go up.
Bubbles 10, 11, and 12: After strong buyers prices trade higher with a negative delta. Next weeks (12 and 13) prices go down.
Bubbles 12, 14, and 15: Strength changes from sellers to buyers; next week, prices increase.
Bubbles 15 and 16: The market trades higher with a very small positive delta; next week, prices go down.
Current bubble/week 17 is not yet finished. Right now, it is trading lower, but with a smaller negative delta than last week. This may signal that sellers are losing strength and that a potential reversal will follow, with prices trading higher.
This is the same BTC 1H chart, but with price rejections from key liquidity areas acting as strong price barriers.
When prices reach a key area with strong liquidity and are rejected, it signals a good time to take action.
By observing price behavior at certain key price levels, we can improve our timing for entering or exiting the markets.
🔶 DETAILS
🔹 Bubbles Display
From the settings panel, traders can configure the bubbles with four main parameters: Mode, Timeframe, Size%, and Shape.
The image above shows five-minute BTC charts with execution over the last 3,500 bars, different display modes, a daily timeframe, 100% size, and shape one.
The Size % parameter controls the overall size of the bubbles, while the Shape parameter controls their vertical growth.
Since the chart has two scales, one for time and one for price, traders can use the Shape parameter to make the bubbles round.
The chart above shows the same bubbles with different size and shape parameters.
You can also customize data labels and timeframe separators from the settings panel.
🔶 SETTINGS
Execute on last X bars: Number of bars for indicator execution
🔹 Bubbles
Display Bubbles: Enable/Disable volume bubbles.
Bubble Mode: Select from the following options: total volume, buy and sell volume, or the delta between buy and sell volume.
Bubble Timeframe: Select the timeframe for which the bubbles will be displayed.
Bubble Size %: Select the size of the bubbles as a percentage.
Bubble Shape: Select the shape of the bubbles. The larger the number, the more vertical the bubbles will be stretched.
🔹 Labels
Display Labels: Enable/Disable data labels, select size and location.
🔹 Separators
Display Separators: Enable/Disable timeframe separators and select color.
🔹 Liquidity Heatmap
Display Heatmap: Enable/Disable liquidity heatmap.
Heatmap Rows: select number of rows to be displayed.
Cell Minimum Size: Select the minimum size for each cell in each row.
Colors.
🔹 Style
Buy & Sell Volume Colors.
Smarter Money Concepts Dashboard [PhenLabs]📊Smarter Money Concepts Dashboard
Version: PineScript™v6
📌Description
The Smarter Money Concepts Dashboard is a comprehensive institutional trading analysis tool that combines six of our most powerful smarter money concepts indicators into one unified suite. This advanced system automatically detects and visualizes Fair Value Gaps, Inverted FVGs, Order Blocks, Wyckoff Springs/Upthrusts, Wick Rejection patterns, and ICT Market Structure analysis.
Built for serious traders who need institutional-grade market analysis, this dashboard eliminates subjective interpretation by automatically identifying where smart money is likely positioned. The integrated real-time dashboard provides instant status updates on all active patterns, making it easy to monitor market conditions at a glance.
🚀Points of Innovation
● Multi-Module Integration: Six different SMC concepts unified in one comprehensive system
● Real-Time Dashboard Display: Live tracking of all active patterns with customizable positioning
● Advanced Volume Filtering: Institutional volume confirmation across all pattern types
● Automated Pattern Management: Smart memory system prevents chart clutter while maintaining relevant zones
● Probability-Based Wyckoff Detection: Mathematical probability calculations for spring/upthrust patterns
● Dual FVG System: Both standard and inverted Fair Value Gap detection with equilibrium analysis
🔧Core Components
● Fair Value Gap Engine: Detects standard FVGs with volume confirmation and equilibrium line analysis
● Inverted FVG Module: Advanced IFVG detection using RVI momentum filtering for inversion confirmation
● Order Block System: Institutional order block identification with customizable mitigation methods
● Wyckoff Pattern Recognition: Automated spring and upthrust detection with probability scoring
● Wick Rejection Analysis: High-probability reversal patterns based on wick-to-body ratios
● ICT Market Structure: Simplified institutional concepts with commitment tracking
🔥Key Features
● Comprehensive Pattern Detection: All major SMC concepts in one indicator with automatic identification
● Volume-Confirmed Signals: Multiple volume filters ensure only institutional-grade patterns are highlighted
● Interactive Dashboard: Real-time status display with active pattern counts and module status
● Smart Memory Management: Automatic cleanup of old patterns while preserving relevant market zones
● Full Alert System: Complete notification coverage for all pattern types and signal generations
● Customizable Display Options: Adjustable colors, transparency, and positioning for all visual elements
🎨Visualization
● Color-Coded Zones: Distinct color schemes for bullish/bearish patterns across all modules
● Dynamic Box Extensions: Automatically extending zones until mitigation or invalidation
● Equilibrium Lines: Fair Value Gap midpoint analysis with dotted line visualization
● Signal Markers: Clear spring/upthrust signals with directional arrows and probability indicators
● Dashboard Table: Professional-grade status panel with module activation and pattern counts
● Candle Coloring: Wick rejection highlighting with transparency-based visual emphasis
📖Usage Guidelines
Fair Value Gap Settings
● Days to Analyze: Default 15, Range 1-100 - Controls historical FVG detection period
● Volume Filter: Enables institutional volume confirmation for gap validity
● Min Volume Ratio: Default 1.5 - Minimum volume spike required for gap recognition
● Show Equilibrium Lines: Displays FVG midpoint analysis for precise entry targeting
Order Block Configuration
● Scan Range: Default 25 bars - Lookback period for structure break identification
● Volume Filter: Institutional volume confirmation for order block validation
● Mitigation Method: Wick or Close-based invalidation for different trading styles
● Min Volume Ratio: Default 1.5 - Volume threshold for significant order block formation
Wyckoff Analysis Parameters
● S/R Lookback: Default 20 - Support/resistance calculation period for spring/upthrust detection
● Volume Spike Multiplier: Default 1.5 - Required volume increase for pattern confirmation
● Probability Threshold: Default 0.7 - Minimum probability score for signal generation
● ATR Recovery Period: Default 5 - Price recovery calculation for pattern strength assessment
Market Structure Settings
● Auto-Detect Zones: Automatic identification of high-volume thin zones
● Proximity Threshold: Default 0.20% - Price proximity requirements for zone interaction
● Test Window: Default 20 bars - Time period for zone commitment calculation
Display Customization
● Dashboard Position: Four corner options for optimal chart layout
● Text Size: Scalable from Tiny to Large for different screen configurations
● Pattern Colors: Full customization of all bullish and bearish zone colors
✅Best Use Cases
● Swing Trading: Identify major institutional zones for multi-day position entries
● Day Trading: Precise intraday entries at Fair Value Gaps and Order Block boundaries
● Trend Analysis: Market structure confirmation for directional bias establishment
● Risk Management: Clear invalidation levels provided by all pattern boundaries
● Multi-Timeframe Analysis: Works across all timeframes from 1-minute to monthly charts
⚠️Limitations
● Market Condition Dependency: Performance varies between trending and ranging market environments
● Volume Data Requirements: Requires accurate volume data for optimal pattern confirmation
● Lagging Nature: Some patterns confirmed after initial price movement has begun
● Pattern Density: High-volatility markets may generate excessive pattern signals
● Educational Tool: Requires understanding of smart money concepts for effective application
💡What Makes This Unique
● Complete SMC Integration: First indicator to combine all major smart money concepts comprehensively
● Real-Time Dashboard: Instant visual feedback on all active institutional patterns
● Advanced Volume Analysis: Multi-layered volume confirmation across all detection modules
● Probability-Based Signals: Mathematical approach to Wyckoff pattern recognition accuracy
● Professional Memory Management: Sophisticated pattern cleanup without losing market relevance
🔬How It Works
1. Pattern Detection Phase:
● Multi-timeframe scanning for institutional footprints across all enabled modules
● Volume analysis integration confirms patterns meet institutional trading criteria
● Real-time pattern validation ensures only high-probability setups are displayed
2. Signal Generation Process:
● Automated zone creation with precise boundary definitions for each pattern type
● Dynamic extension system maintains relevance until mitigation or invalidation occurs
● Alert system activation provides immediate notification of new pattern formations
3. Dashboard Update Cycle:
● Live status monitoring tracks all active patterns and module states continuously
● Pattern count updates provide instant feedback on current market condition density
● Commitment tracking for market structure analysis shows institutional engagement levels
💡Note:
This indicator represents institutional trading concepts and should be used as part of a comprehensive trading strategy. Pattern recognition accuracy improves with understanding of smart money principles. Combine with proper risk management and multiple confirmation methods for optimal results.
Trendline Breakout Strategy [KedArc Quant] Description
A single, rule-based system that builds two trendlines from confirmed swing pivots and trades their breakouts, with optional retest, trend-regime gates (EMA / HTF EMA), and ATR-based risk. All parts serve one decision flow: structure → breakout → gated entry → managed risk.
What it does (for traders)
Draws Up line (teal) through the last two Higher Lows and Down line (red) through the last two Lower Highs, then extends them forward.
Long when price breaks above red; Short when price breaks below teal.
Optional Retest entry: after a break, wait for a pullback toward the broken line within an ATR-scaled buffer.
Uses ATR stop and R-multiple target so risk is consistent across symbols/timeframes.
Labels HL1/HL2/LH1/LH2 so non-coders can verify which pivots built each line.
Why these components are combined
Pure breakout systems on trendlines suffer from three practical issues:
False breaks in chop → solved by trend-regime gates (EMA / HTF EMA) that only allow trades aligned with the prevailing trend.
Uneven volatility across markets/timeframes → solved by ATR-based stop/target, normalizing distance so R-multiples are comparable.
First break whipsaws near wedge apices → mitigated by the optional retest rule that demands a pullback/hold before entry.
These modules are not separate indicators with their own signals. They are support roles inside one method.
The pivot engine defines structure, the breakout detector defines signal, the regime gates decide if we’re allowed to take that signal, and the ATR module sizes risk.
Together they make the trendline breakout usable, testable, and explainable.
How it works (mechanism; each component explained)
1) Pivot engine (structure, non-repainting)
Swings are confirmed with ta.pivotlow/high(L, R). A pivot only exists after R bars (no look-ahead), so once plotted, the line built from those pivots will not repaint.
2) Trendline builder (geometry)
Teal line updates when two consecutive pivot lows satisfy HL2.price > HL1.price (and HL2 occurs after HL1).
Red line updates when two consecutive pivot highs satisfy LH2.price < LH1.price.
Lines are extended right and their current value is read every bar via line.get_price().
3) Breakout detector (signal)
On every bar, compute:
crossover(close, redLine) ⇒ Long breakout
crossunder(close, tealLine) ⇒ Short breakdown
4) Regime gates (trend filters, not separate signals)
EMA gate: allow longs only if close > EMA(len), shorts only if close < EMA(len).
HTF EMA gate (optional): same rule on a higher timeframe to avoid fighting the larger trend.
These do not create entries; they simply permit or block the breakout signal.
5) Retest module (optional confirmation)
After a breakout, record the line price. A valid retest occurs if price pulls back within an ATR-scaled buffer toward that broken line and then closes back in the breakout direction.
This reduces first-tick fakeouts.
6) Risk module (position exit)
Initial stop = ATR(len) × atrMult from entry.
Target = tpR × (ATR × atrMult) (e.g., 2R).
This keeps results consistent across instruments/timeframes.
Entries & exits
Long entry
Base: close breaks above red and passes EMA/HTF gates.
Retest (if enabled): after the break, price pulls back near the broken red line (within the ATR buffer) and holds; then enter.
Short entry
Mirror logic with teal (break below & gates), optionally with a retest.
Exit
strategy.exit places ATR stop & R-multiple target automatically.
Optional “flip”: close if the opposite base signal triggers.
How to use it (step-by-step)
Timeframe: 1–15m for intraday, 1–4h for swing.
Start defaults: Pivot L/R = 5, EMA len = 200, ATR len = 14, ATR mult = 2, TP = 2R, Retest = ON.
Tune sensitivity:
Faster lines (more trades): set L/R = 3–4.
Fewer counter-trend trades: enable HTF EMA (e.g., 60-min or Daily).
Visual audit: labels HL1/HL2 & LH1/LH2 show which pivots built each line—verify by eye.
Alerts: use Long breakout, Short breakdown, and Retest alerts to automate.
Originality (why it merits publication)
Trades the visualization: many “auto-trendline” tools only draw lines; this one turns them into testable, alertable rules.
Integrated design: each component has a defined role in the same pipeline—no unrelated indicators bolted together.
Transparent & non-repainting: pivot confirmation removes look-ahead; labels let non-coders understand the setup that produced each signal.
Notes & limitations
Lines update only after pivot confirmation; that lag is intentional to avoid repainting.
Breakouts near an apex can whipsaw; prefer Retest and/or HTF gate in choppy regimes.
Backtests are idealized; forward-test and size risk appropriately.
⚠️ Disclaimer
This script is provided for educational purposes only.
Past performance does not guarantee future results.
Trading involves risk, and users should exercise caution and use proper risk management when applying this strategy.
Multipower Entry SecretMultipower Entry Secret indicator is designed to be the ultimate trading companion for traders of all skill levels—especially those who struggle with decision-making due to unclear or overwhelming signals. Unlike conventional trading systems cluttered with too many lines and confusing alerts, this indicator provides a clear, adaptive, and actionable guide for market entries and exits.
Key Points:
Clear Buy/Sell/Wait Signals:
The script dynamically analyzes price action, candle patterns, volume, trend strength, and higher time frame context. This means it gives you “Buy,” “Sell,” or “Wait” signals based on real, meaningful market information—filtering out the noise and weak trades.
Multi-Timeframe Adaptive Analysis:
It synchronizes signals between higher and current timeframes, ensuring you get the most reliable direction—reducing the risk of getting caught in fake moves or sudden reversals.
Automatic Support, Resistance & Liquidity Zones:
Key levels like support, resistance, and liquidity zones are auto-detected and displayed directly on the chart, helping you make precise decisions without manual drawing.
Real-Time Dashboard:
All relevant information, such as trend strength, market intent, volume sentiment, and the reason behind each signal, is neatly summarized in a dashboard—making monitoring effortless and intuitive.
Customizable & Beginner-Friendly:
Whether you’re a newcomer wanting straightforward guidance or a professional needing advanced customization, the indicator offers flexible options to adjust analysis depth, timeframes, sensitivity, and more.
Visual & Clutter-Free:
The design ensures that your chart remains clean and readable, showing only the most important information. This minimizes mental overload and allows for instant decision-making.
Who Will Benefit?
Beginners who want to learn trading logic, avoid common traps, and see the exact reason behind every signal.
Advanced traders who require adaptive multi-timeframe analytics, fast execution, and stress-free monitoring.
Anyone who wants to save screen time, reduce analysis paralysis, and have more confidence in every trade they take.
1. No Indicator Clutter
Intent:
Many traders get confused by charts filled with too many indicators and signals. This often leads to hesitation, missed trades, or taking random, risky trades.
In this Indicator:
You get a clean and clutter-free chart. Only the most important buy/sell/wait signals and relevant support/resistance/liquidity levels are shown. These update automatically, removing the “overload” and keeping your focus sharp, so your decision-making is faster and stress-free.
2. Exact Entry Guide
Intent:
Traders often struggle with entry timing, leading to FOMO (fear of missing out) or getting trapped in sudden market reversals.
In this Indicator:
The system uses powerful adaptive logic to filter out weak signals and only highlight the strongest market moves. This not only prevents you from entering late or on noise, but also helps avoid losses from false breakouts or whipsaws. You get actionable suggestions—when to enter, when to hold back—so your entries are high-conviction and disciplined.
3. HTF+LTF Logic: Multitimeframe Sync Analysis
Intent:
Most losing trades happen when you act only on the short-term chart, ignoring the bigger market trend.
In this Indicator:
Signals are based on both the current chart timeframe (LTF) and a higher (HTF, like hourly/daily) timeframe. The indicator synchronizes trend direction, momentum, and structure across both levels, quickly adapting to show you when both are aligned. This filtering results in “only trade with the bigger trend”—dramatically increasing your win rate and market confidence.
4. Auto Support/Resistance & Liquidity Zones
Intent:
Drawing support/resistance and liquidity zones manually is time-consuming and error-prone, especially for beginners.
In this Indicator:
The system automatically identifies and plots the most crucial support/resistance levels and liquidity zones on your chart. This is based on adaptive, real-time price and volume analysis. These zones highlight where major institutional activity, trap setups, or real breakouts/reversals are most likely, removing guesswork and giving you a clear reference for entries, exits, and stop placements.
5. Clear Action/Direction
Intent:
Traders need certainty—what does the market want right now? Most indicators are vague.
In this Indicator:
Your dashboard always displays in plain words (like “BUY”, “SELL”, or “WAIT”) what action makes sense in the current market phase. Whether it’s a bull trap, volume spike, wick reversal, or exhaustion—it’s interpreted and explained clearly. No more confusion—just direct, real-time advice.
6. For Everyone (Beginner to Pro)
Intent:
Most advanced indicators are overwhelming for new traders; simple ones lack depth for professionals.
In this Indicator:
It is simple enough for a beginner—just add it to the chart and instantly see what action to consider. At the same time, it includes advanced adaptive analysis, multi-timeframe logic, and customizable settings so professional traders can fine-tune it for their strategies.
7. Ideal Usage and User Benefits
Instant Decision Support:
Whenever you’re unsure about a trade, just look at the indicator’s suggestion for clarity.
Entry Learning:
Beginners get real-time “practice” by not only seeing signals, but also the reason behind them—improving your chart reading and market understanding.
Screen Time & Stress Reduction:
Clear, relevant information only; no noise, less fatigue, faster decisions.
Makes Trading Confident & Simple:
The smart dashboard splits actionable levels (HTF, LTF, action) so you never miss a move, avoid traps, and stay aligned with high-probability trades.
8. Advanced Input Settings (Smart Customization)
Explained with Examples:
Enable Wick Analysis:
Finds candles with strong upper/lower wicks (signs of rejection/buying/selling force), alerting you to hidden reversals and protecting from FOMO entries.
Enable Absorption:
Detects when heavy order flow from one side is “absorbed” by the other (shows where institutional buyers/sellers are likely active, helps spot fake breakouts).
Enable Unusual Breakout:
Highlights real breakouts—large volatility plus high volume—so you catch genuine moves and avoid random spikes.
Enable Range/Expansion:
Smartly flags sudden range expansions—when the market goes from quiet to volatile—so you can act at the start of real trends.
Trend Bar Lookback:
Adjusts how many bars/candles are used in trend calculations. Short (fast trades, more signals), long (more reliability, fewer whipsaws).
Bull/Bear Bars for Strong Trend Min:
Sets how many candles in a row must support a trend before calling it “strong”—prevents flipping signals, keeps you disciplined.
Volume MA Length:
Lets you adjust how many bars back volume is averaged—fine-tune for your asset and trading style for best volume signals.
Swing Lookback Bars:
Set how many bars to use for swing high/low detection—short (quick swing levels), long (stronger support/resistance).
HTF (Bias Window):
Decide which higher timeframe the indicator should use for big-picture market mood. Adjustable for any style (scalp, swing, position).
Adaptive Lookback (HTF):
Choose how much HTF history is used for detecting major extremes/zones. Quick adjust for more/less sensitivity.
Show Support/Resistance, Liquidity Zones, Trendlines:
Toggle them on/off instantly per your needs—keeps your chart relevant and tailored.
9. Live Dashboard Sections Explained
Intent HTF:
Shows if the bigger timeframe currently has a Bullish, Bearish, or Neutral (“Chop”) intent, based on strict volume/price body calculations. Instant clarity—no more guessing on trend bias.
HTF Bias:
Clear message about which side (buy/sell/sideways) controls the market on the higher timeframe, so you always trade with the “big money.”
Chart Action:
The central action for the current bar—Whether to Buy, Sell, or Wait—calculated from all indicator logic, not just one rule.
TrendScore Long/Short:
See how many candles in your chosen window were bullish or bearish, at a glance. Instantly gauge market momentum.
Reason (WHY):
Every time a signal appears, the “reason” cell tells you the primary logic (breakout, wick, strong trend, etc.) behind it. Full transparency and learning—never trade blindly.
Strong Trend:
Shows if the market is currently in a powerful trend or not—helping you avoid choppy, risky entries.
HTF Vol/Body:
Displays current higher timeframe volume and candle body %—helping spot when big players are active for higher probability trades.
Volume Sentiment:
A real-time analysis of market psychology (strong bullish/bearish, neutral)—making your decision-making much more confident.
10. Smart and User-Friendly Design
Multi-timeframe Adaptive:
All calculations can now be drawn from your choice of higher or current timeframe, ensuring signals are filtered by larger market context.
Flexible Table Position:
You can set the live dashboard/summary anywhere on the chart for best visibility.
Refined Zone Visualization:
Liquidity and order blocks are visually highlighted, auto-tuning for your settings and always cleaning up to stay clutter-free.
Multi-Lingual & Beginner Accessible:
With Hindi and simple English support, descriptions and settings are accessible for a wide audience—anyone can start using powerful trading logic with zero language barrier.
Efficient Labels & Clear Reasoning:
Signal labels and reasons are shown/removed dynamically so your chart stays informative, not messy.
Every detail of this indicator is designed to make trading both simpler and smarter—helping you avoid the common pitfalls, learn real price action, stay in sync with the market’s true mood, and act with discipline for higher consistency and confidence.
This indicator makes professional-grade market analysis accessible to everyone. It’s your trusted assistant for making smarter, faster, and more profitable trading decisions—providing not just signals, but also the “why” behind every action. With auto-adaptive logic, clear visuals, and strong focus on real trading needs, it lets you focus on capturing the moves that matter—every single time.
Kalman Adjusted Average True Range [BackQuant]Kalman Adjusted Average True Range
A volatility-aware trend baseline that fuses a Kalman price estimate with ATR “rails” to create a smooth, adaptive guide for entries, exits, and trailing risk.
Built on my original Kalman
This indicator is based on my original Kalman Price Filter:
That core smoother is used here to estimate the “true” price path, then blended with ATR to control step size and react proportionally to market noise.
What it plots
Kalman ATR Line the main baseline that turns up/down with the filtered trend.
Optional Moving Average of the Kalman ATR a secondary line for confluence (SMA/Hull/EMA/WMA/DEMA/RMA/LINREG/ALMA).
Candle Coloring (optional) paint bars by the baseline’s current direction.
Why combine Kalman + ATR?
Kalman reduces measurement noise and produces a stable path without the lag of heavy MAs.
ATR rails scale the baseline’s step to current volatility, so it’s calm in chop and more responsive in expansion.
The result is a single, intelligible line you can trade around: slope-up = constructive; slope-down = caution.
How it works (plain English)
Each bar, the Kalman filter updates an internal state (tunable via Process Noise , Measurement Noise , and Filter Order ) to estimate the underlying price.
An ATR band (Period × Factor) defines the allowed per-bar adjustment. The baseline cannot “jump” beyond those rails in one step.
A direction flip is detected when the baseline’s slope changes sign (upturn/downturn), and alerts are provided for both.
Typical uses
Trend confirmation Trade in the baseline’s direction; avoid fading a firmly rising/falling line.
Pullback timing Look for entries when price mean-reverts toward a rising baseline (or exits on tags of a falling one).
Trailing risk Use the baseline as a dynamic guide; many traders set stops a small buffer beyond it (e.g., a fraction of ATR).
Confluence Enable the MA overlay of the Kalman ATR; alignment (baseline above its MA and rising) supports continuation.
Inputs & what they do
Calculation
Kalman Price Source which price the filter tracks (Close by default).
Process Noise how quickly the filter can adapt. Higher = more responsive (but choppier).
Measurement Noise how much you distrust raw price. Higher = smoother (but slower to turn).
Filter Order (N) depth of the internal state array. Higher = slightly steadier behavior.
Kalman ATR
Period ATR lookback. Shorter = snappier; longer = steadier.
Factor scales the allowed step per bar. Larger factors permit faster drift; smaller factors clamp movement.
Confluence (optional)
MA Type & Period compute an MA on the Kalman ATR line , not on price.
Sigma (ALMA) if ALMA is selected, this input controls the curve’s shape. (Ignored for other MA types.)
Visuals
Plot Kalman ATR toggle the main line.
Paint Candles color bars by up/down slope.
Colors choose long/short hues.
Signals & alerts
Trend Up baseline turns upward (slope crosses above 0).
Alert: “Kalman ATR Trend Up”
Trend Down baseline turns downward (slope crosses below 0).
Alert: “Kalman ATR Trend Down”
These are state flips , not “price crossovers,” so you avoid many one-bar head-fakes.
How to start (fast presets)
Swing (daily/4H) ATR Period 7–14, Factor 0.5–0.8, Process Noise 0.02–0.05, Measurement Noise 2–4, N = 3–5.
Intraday (5–15m) ATR Period 5–7, Factor 0.6–1.0, Process Noise 0.05–0.10, Measurement Noise 2–3, N = 3–5.
Slow assets / FX raise Measurement Noise or ATR Period for calmer lines; drop Factor if the baseline feels too jumpy.
Reading the line
Rising & curving upward momentum building; consider long bias until a clear downturn.
Flat & choppy regime uncertainty; many traders stand aside or tighten risk.
Falling & accelerating distribution lower; short bias until a clean upturn.
Practical playbook
Continuation entries After a Trend Up alert, wait for a minor pullback toward the baseline; enter on evidence the line keeps rising.
Exit/reduce If long and the baseline flattens then turns down, trim or exit; reverse logic for shorts.
Filters Add a higher-timeframe check (e.g., only take longs when the daily Kalman ATR is rising).
Stops Place stops just beyond the baseline (e.g., baseline − x% ATR for longs) to avoid “tag & reverse” noise.
Notes
This is a guide to state and momentum, not a guarantee. Combine with your process (structure, volume, time-of-day) for decisions.
Settings are asset/timeframe dependent; start with the presets and nudge Process/Measurement Noise until the baseline “feels right” for your market.
Summary
Kalman ATR takes the noise-reduction of a Kalman price estimate and couples it with volatility-scaled movement to produce a clean, adaptive baseline. If you liked the original Kalman Price Filter (), this is its trend-trading cousin purpose-built for cleaner state flips, intuitive trailing, and confluence with your existing
RedFlagCounter-trend strategy
Condition to open a long position:
Buys if the price drops by a specified percentage from the previous candle’s close. Only one purchase can be made within a single candle.
Condition to close a position:
Places a separate individual closing limit order for each purchase, or uses one common take-profit order for the whole position.
⚠️ Attention : Stop-loss is not implemented in the current first version of the strategy.
Options description:
Drop_percent , % — Percentage drop in price from the From point
From — The reference point on the closed candle from which the Drop_percent is calculated (Open, Close, High, Low)
Tp , % — Take-profit level as a percentage
Count — Number of allowed additional purchases (scaling in)
Each_tp — Mode switch:
True — a separate take-profit is placed for each purchase
False — one common take-profit is placed based on the average entry price of the position
Continuous Accumulation Strategy [DCA] v9🇬🇧 English: Continuous Accumulation Strategy v9.4
This script is a full-featured strategy designed to backtest the "Buy the Dip" or "Dollar Cost Averaging" (DCA) philosophy. Its core feature is the Dynamic Peak Detection logic, which solves the "lock-in" problem of previous versions. Instead of getting stuck on an old high, the strategy constantly adapts to the market by referencing the most recent peak.
Key Features
* Dynamic Peak Detection: You define the "Peak Lookback Period." For example, on a Daily chart, setting it to `5` references the peak of the last business week.
* Stable Order Management: The strategy consistently uses a fixed cash amount (e.g., $100) for each entry, which prevents any runtime errors related to negative equity.
* Publishing-Ready: To meet TradingView's requirement for a backtest report, this strategy executes a symbolic, one-time "dummy trade" (one buy and one sell) at the very beginning of the test period. This first trade should be ignored when analyzing performance , as its only purpose is to enable publication.
How It Works
The main logic follows an adaptive cycle: Find Dynamic Peak -> Wait for a Drop -> Buy on Crossover -> Repeat.
1. Finds the Dynamic Peak: On every bar, it identifies the highest price within your defined lookback period.
2. Calculates the Drop: It constantly calculates the percentage drop from this moving peak.
3. Executes an Entry: The moment the price crosses below a target drop percentage, it executes a buy order.
4. Continuously Adapts: As the price moves, the dynamic peak is constantly updated, meaning the strategy never gets locked and is always ready for the next opportunity.
How to Use This Strategy
* Focus on the Strategy Tester: After adding it to the chart, analyze the Equity Curve, Net Profit, and Max Drawdown to see how this accumulation philosophy would have performed on your favorite asset.
* Optimize Parameters: Adjust the "Peak Lookback Period" and "Drop Percentages" to fit the volatility of the asset you are testing.
This is a tool for testing and analyzing a "buy and accumulate" philosophy. Its main logic does not generate sell signals.
Trend FriendTrend Friend — What it is and how to use it
I built Trend Friend to stop redrawing the same trendlines all day. It automatically connects confirmed swing points (fractals) and keeps the most relevant lines in front of you. The goal: give you clean, actionable structure without the guesswork.
What it does (in plain English)
Finds swing highs/lows using a Fractal Period you choose.
Draws auto-trendlines between the two most recent confirmed highs and the two most recent confirmed lows.
Colours by intent:
Lines drawn from highs (potential resistance / bearish) = Red
Lines drawn from lows (potential support / bullish) = Green
Keeps the chart tidy: The newest lines are styled as “recent,” older lines are dimmed as “historical,” and it prunes anything beyond your chosen limit.
Optional crosses & alerts: You can highlight when price closes across the most recent line and set alerts for new lines formed and upper/lower line crosses.
Structure labels: It tags HH, LH, HL, LL at the swing points, so you can quickly read trend/rotation.
How it works (under the hood)
A “fractal” here is a confirmed pivot: the highest high (or lowest low) with n bars on each side. That means pivots only confirm after n bars, so signals are cleaner and less noisy.
When a new pivot prints, the script connects it to the prior pivot of the same type (high→high, low→low). That gives you one “bearish” line from highs and one “bullish” line from lows.
The newest line is marked as recent (brighter), and the previous recent line becomes historical (dimmed). You can keep as many pairs as you want, but I usually keep it tight.
Inputs you’ll actually use
Fractal Period (n): this is the big one. It controls how swingy/strict the pivots are.
Lower n → more swings, more lines (faster, noisier)
Higher n → fewer swings, cleaner lines (slower, swing-trade friendly)
Max pair of lines: how many pairs (up+down) to keep on the chart. 1–3 is a sweet spot.
Extend: extend lines Right (my default) or Both ways if you like the context.
Line widths & colours: recent vs. historical are separate so you can make the active lines pop.
Show crosses: toggle the X markers when price crosses a line. I turn this on when I’m actively hunting breakouts/retests.
Reading the chart
Red lines (from highs): I treat these as potential resistance. A clean break + hold above a red line often flips me from “fade” to “follow.”
Green lines (from lows): Potential support. Same idea in reverse: break + hold below and I stop buying dips until I see structure reclaim.
HH / LH / HL / LL dots: quick read on structure.
HH/HL bias = uptrend continuation potential
LH/LL bias = downtrend continuation potential
Mixed prints = rotation/chop—tighten risk or wait for clarity.
My H1 guidance (fine-tuning Fractal Period)
If you’re mainly on H1 (my use case), tune like this:
Fast / aggressive: n = 6–8 (lots of signals, good for momentum days; more chop risk)
Balanced (recommended): n = 9–12 (keeps lines meaningful but responsive)
Slow / swing focus: n = 13–21 (filters noise; better for trend days and higher-TF confluence)
Rule of thumb: if you’re getting too many touches and whipsaws, increase n. If you’re late to obvious breaks, decrease n.
How I trade it (example workflow)
Pick your n for the session (H1: start at 9–12).
Mark the recent red & green lines. That’s your immediate structure.
Look for interaction:
Rejections from a line = fade potential back into the range.
Break + close across a line = watch the retest for continuation.
Confirm with context: session bias, HTF structure, and your own tools (VWAP, RSI, volume, FVG/OB, etc.).
Plan the trade: enter on retest or reclaim, stop beyond the line/last swing, target the opposite side or next structure.
Alerts (set and forget)
“New trendline formed” — fires when a new high/low pivot confirms and a fresh line is drawn.
“Upper/lower trendline crossed” — fires when price crosses the most recent red/green line.
Use these to track structure shifts without staring at the screen.
Good to know (honest limitations)
Confirmation lag: pivots need n bars on both sides, so signals arrive after the swing confirms. That’s by design—less noise, fewer fake lines.
Lines update as structure evolves: when a new pivot forms, the previous “recent” line becomes “historical,” and older ones can be removed based on your max setting.
Not an auto trendline crystal ball: it won’t predict which line holds or breaks—it just keeps the most relevant structure clean and up to date.
Final notes
Works on any timeframe; I built it with H1 in mind and scale to H4/D1 by increasing n.
Pairs nicely with session tools and VWAP for intraday, or with supply/demand / FVGs for swing planning.
Risk first: lines are structure, not guarantees. Manage position size and stops as usual.
Not financial advice. Trade your plan. Stay nimble.
RSI ADX Bollinger Analysis High-level purpose and design philosophy
This indicator — RSI-ADX-Bollinger Analysis — is a compact, educational market-analysis toolkit that blends momentum (RSI), trend strength (ADX), volatility structure (Bollinger Bands) and simple volumetrics to provide traders a snapshot of market condition and trade idea quality. The design philosophy is explicit and layered: use each component to answer a different question about price action (momentum, conviction, volatility, participation), then combine answers to form a more robust, explainable signal. The mashup is intended for analysis and learning, not automatic execution: it surfaces the why behind signals so traders can test, learn and apply rules with risk management.
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What each indicator contributes (component-by-component)
RSI (Relative Strength Index) — role and behavior: RSI measures short-term momentum by comparing recent gains to recent losses. A high RSI (near or above the overbought threshold) indicates strong recent buying pressure and potential exhaustion if price is extended. A low RSI (near or below the oversold threshold) indicates strong recent selling pressure and potential exhaustion or a value area for mean-reversion. In this dashboard RSI is used as the primary momentum trigger: it helps identify whether price is locally over-extended on the buy or sell side.
ADX (Average Directional Index) — role and behavior: ADX measures trend strength independently of direction. When ADX rises above a chosen threshold (e.g., 25), it signals that the market is trending with conviction; ADX below the threshold suggests range or weak trend. Because patterns and momentum signals perform differently in trending vs. ranging markets, ADX is used here as a filter: only when ADX indicates sufficient directional strength does the system treat RSI+BB breakouts as meaningful trade candidates.
Bollinger Bands — role and behavior: Bollinger Bands (20-period basis ± N standard deviations) show volatility envelope and relative price position vs. a volatility-adjusted mean. Price outside the upper band suggests pronounced extension relative to recent volatility; price outside the lower band suggests extended weakness. A band expansion (increasing width) signals volatility breakout potential; contraction signals range-bound conditions and potential squeeze. In this dashboard, Bollinger Bands provide the volatility/structural context: RSI extremes plus price beyond the band imply a stronger, volatility-backed move.
Volume split & basic MA trend — role and behavior: Buy-like and sell-like volume (simple heuristic using close>open or closeopen) or sell-like (close1.2 for validation and compare win rate and expectancy.
4. TF alignment: Accept signals only when higher timeframe (e.g., 4h) trend agrees — compare results.
5. Parameter sensitivity: Vary RSI threshold (70/30 vs 80/20), Bollinger stddev (2 vs 2.5), and ADX threshold (25 vs 30) and measure stability of results.
These exercises teach both statistical thinking and the specific failure modes of the mashup.
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Limitations, failure modes and caveats (explicit & teachable)
• ADX and Bollinger measures lag during fast-moving news events — signals can be late or wrong during earnings, macro shocks, or illiquid sessions.
• Volume classification by open/close is a heuristic; it does not equal TAPEDATA, footprint or signed volume. Use it as supportive evidence, not definitive proof.
• RSI can remain overbought or oversold for extended stretches in persistent trends — relying solely on RSI extremes without ADX or BB context invites large drawdowns.
• Small-cap or low-liquidity instruments yield noisy band behavior and unreliable volume ratios.
Being explicit about these limitations is a strong point in a TradingView description — it demonstrates transparency and educational intent.
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Originality & mashup justification (text you can paste)
This script intentionally combines classical momentum (RSI), volatility envelope (Bollinger Bands) and trend-strength (ADX) because each indicator answers a different and complementary question: RSI answers is price locally extreme?, Bollinger answers is price outside normal volatility?, and ADX answers is the market moving with conviction?. Volume participation then acts as a practical check for real market involvement. This combination is not a simple “indicator mashup”; it is a designed ensemble where each element reduces the others’ failure modes and together produce a teachable, testable signal framework. The script’s purpose is educational and analytical — to show traders how to interpret the interplay of momentum, volatility, and trend strength.
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TradingView publication guidance & compliance checklist
To satisfy TradingView rules about mashups and descriptions, include the following items in your script description (without exposing source code):
1. Purpose statement: One or two lines describing the script’s objective (educational multi-indicator market overview and idea filter).
2. Component list: Name the major modules (RSI, Bollinger Bands, ADX, volume heuristic, SMA trend checks, signal tracking) and one-sentence reason for each.
3. How they interact: A succinct non-code explanation: “RSI finds momentum extremes; Bollinger confirms volatility expansion; ADX confirms trend strength; all three must align for a BUY/SELL.”
4. Inputs: List adjustable inputs (RSI length and thresholds, BB length & stddev, ADX threshold & smoothing, volume MA, table position/size).
5. Usage instructions: Short workflow (check TF alignment → confirm participation → define stop & R:R → backtest).
6. Limitations & assumptions: Explicitly state volume is approximated, ADX has lag, and avoid promising guaranteed profits.
7. Non-promotional language: No external contact info, ads, claims of exclusivity or guaranteed outcomes.
8. Trademark clause: If you used trademark symbols, remove or provide registration proof.
9. Risk disclaimer: Add the copy-ready disclaimer below.
This matches TradingView’s request for meaningful descriptions that explain originality and inter-component reasoning.
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Copy-ready short publication description (paste into TradingView)
Advanced RSI-ADX-Bollinger Market Overview — educational multi-indicator dashboard. This script combines RSI (momentum extremes), Bollinger Bands (volatility envelope and band expansion), ADX (trend strength), simple SMA trend bias and a basic buy/sell volume heuristic to surface high-quality idea candidates. Signals require alignment of momentum, volatility expansion and rising ADX; volume participation is displayed to support signal confidence. Inputs are configurable (RSI length/levels, BB length/stddev, ADX length/threshold, volume MA, display options). This tool is intended for analysis and learning — not for automated execution. Users should back test and apply robust risk management. Limitations: volume classification here is a heuristic (close>open), ADX and BB measures lag in fast news events, and results vary by instrument liquidity.
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Copy-ready risk & misuse disclaimer (paste into description or help file)
This script is provided for educational and analytical purposes only and does not constitute financial or investment advice. It does not guarantee profits. Indicators are heuristics and may give false or late signals; always back test and paper-trade before using real capital. The author is not responsible for trading losses resulting from the use or misuse of this indicator. Use proper position sizing and risk controls.
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Risk Disclaimer: This tool is provided for education and analysis only. It is not financial advice and does not guarantee returns. Users assume all risk for trades made based on this script. Back test thoroughly and use proper risk management.
EMA Cross Alert V666 [noFuck]EMA Cross Alert — What it does
EMA Cross Alert watches three EMAs (Short, Mid, Long), detects their crossovers, and reports exactly one signal per bar by priority: EARLY > Short/Mid > Mid/Long > Short/Long. Optional EARLY mode pings when Short crosses Long while Mid is still between them—your polite early heads-up.
Why you might like it
Three crossover types: s/m, m/l, s/l
EARLY detection: earlier hints, not hype
One signal per bar: less noise, more focus
Clear visuals: tags, big cross at signal price, EARLY triangles
Alert-ready: dynamic alert text on bar close + static alertconditions for UI
Inputs (plain English)
Short/Mid/Long EMA length — how fast each EMA reacts
Extra EMA length (visual only) — context EMA; does not affect signals
Price source — e.g., Close
Show cross tags / EARLY triangles / large cross — visual toggles
Enable EARLY signals (Short/Long before Mid) — turn early pings on/off
Count Mid EMA as "between" even when equal (inclusive) — ON: Mid counts even if exactly equal to Short or Long; OFF (default): Mid must be strictly between them
Enable dynamic alerts (one per bar close) — master alert switch
Alert on Short/Mid, Mid/Long, Short/Long, EARLY — per-signal alert toggles
Quick tips
Start with defaults; if you want more EARLY on smooth/low-TF markets, turn “inclusive” ON
Bigger lengths = calmer trend-following; smaller = faster but choppier
Combine with volume/structure/risk rules—the indicator is the drummer, not the whole band
Disclaimer
Alerts, labels, and triangles are not trade ideas or financial advice. They are informational signals only. You are responsible for entries, exits, risk, and position sizing. Past performance is yesterday; the future is fashionably late.
Credits
Built with the enthusiastic help of Code Copilot (AI)—massively involved, shamelessly proud, and surprisingly good at breakfasting on exponential moving averages.
Pivot Points mura visionWhat it is
A clean, single-set pivot overlay that lets you choose the pivot type (Traditional/Fibonacci), the anchor timeframe (Daily/Weekly/Monthly/Quarterly, or Auto), and fully customize colors, line width/style , and labels . The script never draws duplicate sets—exactly one pivot pack is displayed for the chosen (or auto-detected) anchor.
How it works
Pivots are computed with ta.pivot_point_levels() for the selected anchor timeframe .
The script supports the standard 7 levels: P, R1/S1, R2/S2, R3/S3 .
Lines span exactly one anchor period forward from the current bar time.
Label suffix shows the anchor source: D (Daily), W (Weekly), M (Monthly), Q (Quarterly).
Auto-anchor logic
Intraday ≤ 15 min → Daily pivots (D)
Intraday 20–120 min → Weekly pivots (W)
Intraday > 120 min (3–4 h) → Monthly pivots (M)
Daily and above → Quarterly pivots (Q)
This keeps the chart readable while matching the most common trader expectations across timeframes.
Inputs
Pivot Type — Traditional or Fibonacci.
Pivots Timeframe — Auto, Daily (1D), Weekly (1W), Monthly (1M), Quarterly (3M).
Line Width / Line Style — width 1–10; style Solid, Dashed, or Dotted.
Show Labels / Show Prices — toggle level tags and price values.
Colors — user-selectable colors for P, R*, S* .
How to use
Pick a symbol/timeframe.
Leave Pivots Timeframe = Auto to let the script choose; or set a fixed anchor if you prefer.
Toggle labels and prices to taste; adjust line style/width and colors for your theme.
Read the market like a map:
P often acts as a mean/rotation point.
R1/S1 are common first reaction zones; R2/S2 and R3/S3 mark stronger extensions.
Confluence with S/R, trendlines, session highs/lows, or volume nodes improves context.
Good practices
Use Daily pivots for intraday scalps (≤15m).
Use Weekly/Monthly for swing bias on 1–4 h.
Use Quarterly when analyzing on Daily and higher to frame larger cycles.
Combine with trend filters (e.g., EMA/KAMA 233) or volatility tools for entries and risk.
Notes & limitations
The script shows one pivot pack at a time by design (prevents clutter and duplicates).
Historical values follow TradingView’s standard pivot definitions; results can vary across assets/exchanges.
No alerts are included (levels are static within the anchor period).
Market Pulse Dip RadarThis indicator is designed to help traders spot meaningful dips in price and then evaluate whether those dips are worth trading or not. It doesn’t just mark a dip; it also helps with risk management, trade planning, and filtering out weak signals.
Here’s how it works:
First, it looks at the recent high price and checks how much the market has dropped from that high. If the drop is larger than the minimum percentage you set, it marks it as a potential dip.
Next, it checks the trend structure by using two moving averages (a fast one and a slow one). If the fast average is below the slow average, it means the market is in a weaker structure, and that dip is considered more valid.
On top of that, you can enable a multi-timeframe filter. For example, if you are trading on the 15-minute chart, you can ask the indicator to confirm that the 1-hour trend is also supportive before showing you a dip. This helps avoid trading against the bigger trend.
Risk management is built in. The indicator automatically suggests a stop-loss by combining volatility (ATR) and recent swing lows. It then draws three profit target levels (1x risk, 2x risk, and 3x risk). This makes it easier to plan where to exit if the trade works.
A key part of this tool is the confidence score. Each dip signal is rated from 0 to 100. The score depends on how deep the dip is, how far apart the moving averages are, how healthy volatility is, and whether the higher timeframe supports the trade. The score is then labeled as High, Medium, Low, or Wait. This helps traders focus only on the stronger setups.
On the chart, dip signals are marked with a diamond shape under the bars. The color of the diamond tells you if it’s high, medium, or low quality. When a signal appears, the indicator also plots horizontal lines for the entry, stop, and targets.
To make it easier to read, there is also a dashboard box that shows the current score, quality, dip percentage, and suggested stop-loss. This means you don’t have to calculate or check different things yourself – everything is visible in one place.
Finally, it comes with alerts. You can set alerts for when a dip signal happens, or when it’s medium or high confidence. This way, you don’t need to stare at charts all day; TradingView can notify you.
So in short, this tool:
• Finds dips based on your rules.
• Filters them using structure, volatility, and higher timeframe trend.
• Suggests stop-loss and profit targets.
• Rates each dip with a confidence score.
• Shows all this info in a clean dashboard and alerts you when it happens.
👉 Do you want me to now explain how a trader would actually use it in practice (step by step, from signal to trade)?
Mikula's Master 360° Square of 12Mikula’s Master 360° Square of 12
An educational W. D. Gann study indicator for price and time. Anchor a compact Square of 12 table to a start point you choose. Begin from a bar’s High or Low (or set a manual start price). From that anchor you can progress or regress the table to study how price steps through cycles in either direction.
What you’re looking at :
Zodiac rail (far left): the twelve signs.
Degree rail: 24 rows in 15° steps from 15° up to 360°/0°.
Transit rail and Natal rail: track one planet per rail. Each planet is placed at its current row (℞ shown when retrograde). As longitude advances, the planet climbs bottom → top, then wraps to the bottom at the next sign; during retrograde it steps downward.
Hover a planet’s cell to see a tooltip with its exact longitude and sign (e.g., 152.4° ♌︎). The linked price cell in the grid moves with the planet’s row so you can follow a planet’s path through the zodiac as a path through price.
Price grid (right): the 12×24 Square of 12. Each column is a cycle; cells are stepped price levels from your start price using your increment.
Bottom rail: shows the current square number and labels the twelve columns in that square.
How the square is read
The square always begins at the bottom left. Read each column bottom → top. At the top, return to the bottom of the next column and read up again. One square contains twelve cycles. Because the anchor can be a High or a Low, you can progress the table upward from the anchor or regress it downward while keeping the same bottom-to-top reading order.
Iterate Square (shifting)
Iterate Square shifts the entire 12×24 grid to the next set of twelve cycles.
Square 1 shows cycles 1–12; Square 2 shows 13–24; Square 3 shows 25–36, etc.
Visibility rules
Pivot cells are table-bound. If you shift the square beyond those prices, their highlights won’t appear in the table.
A/B levels and Transit/Natal planetary lines are chart overlays and can remain visible on the table as you shift the square.
Quick use
Choose an anchor (date/time + High/Low) or enable a manual start price .
Set the increment. If you anchored with a Low and want the table to step downward from there, use a negative value.
Optional: pick Transit and Natal planets (one per rail), toggle their plots, and hover their cells for longitude/sign.
Optional: turn on A/B levels to display repeating bands from the start price.
Optional: enable swing pivots to tint matching cells after the anchor.
Use Iterate Square to shift to later squares of twelve cycles.
Examples
These are exploratory examples to spark ideas:
Overview layout (zodiac & degree rails, Transit/Natal rails, price grid)
A-levels plotted, pivots tinted on the table, real-time price highlighted
Drawing angles from the anchor using price & time read from the table
Using a TradingView Gann box along the A-levels to study reactions
Attribution & originality
This script is an original implementation (no external code copied). Conceptual credit to Patrick Mikula, whose discussion of the Master 360° Square of 12 inspired this study’s presentation.
Further reading (neutral pointers)
Patrick Mikula, Gann’s Scientific Methods Unveiled, Vol. 2, “W. D. Gann’s Use of the Circle Chart.”
W. D. Gann’s Original Commodity Course (as provided by WDGAN.com).
No affiliation implied.
License CC BY-NC-SA 4.0 (non-commercial; please attribute @Javonnii and link the original).
Dependency AstroLib by @BarefootJoey
Disclaimer Educational use only; not financial advice.
DYNAMIC TRADING DASHBOARDStudy Material for the "Dynamic Trading Dashboard"
This Dynamic Trading Dashboard is designed as an educational tool within the TradingView environment. It compiles commonly used market indicators and analytical methods into one visual interface so that traders and learners can see relationships between indicators and price action. Understanding these indicators, step by step, can help traders develop discipline, improve technical analysis skills, and build strategies. Below is a detailed explanation of each module.
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1. Price and Daily Reference Points
The dashboard displays the current price, along with percentage change compared to the day’s opening price. It also highlights whether the price is moving upward or downward using directional symbols. Alongside, it tracks daily high, low, open, and daily range.
For traders, daily levels provide valuable reference points. The daily high and low are considered intraday support and resistance, while the median price of the day often acts as a pivot level for mean reversion traders. Monitoring these helps learners see how price oscillates within daily ranges.
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2. VWAP (Volume Weighted Average Price)
VWAP is calculated as a cumulative average price weighted by volume. The dashboard compares the current price with VWAP, showing whether the market is trading above or below it.
For traders, VWAP is often a guide for institutional order flow. Price trading above VWAP suggests bullish sentiment, while trading below VWAP indicates bearish sentiment. Learners can use VWAP as a training tool to recognize trend-following vs. mean reversion setups.
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3. Volume Analysis
The system distinguishes between buy volume (when the closing price is higher than the open) and sell volume (when the closing price is lower than the open). A progress bar highlights the ratio of buying vs. selling activity in percentage.
This is useful because volume confirms price action. For instance, if prices rise but sell volume dominates, it can signal weakness. New traders learning with this tool should focus on how volume often precedes price reversals and trends.
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4. RSI (Relative Strength Index)
RSI is a momentum oscillator that measures price strength on a scale from 0 to 100. The dashboard classifies RSI readings into overbought (>70), oversold (<30), or neutral zones and adds visual progress bars.
RSI helps learners understand momentum shifts. During training, one should notice how trending markets can keep RSI extended for longer periods (not immediate reversal signals), while range-bound markets react more sharply to RSI extremes. It is an excellent tool for practicing trend vs. range identification.
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5. MACD (Moving Average Convergence Divergence)
The MACD indicator involves a fast EMA, slow EMA, and signal line, with focus on crossovers. The dashboard shows whether a “bullish cross” (MACD above signal line) or “bearish cross” (MACD below signal line) has occurred.
MACD teaches traders to identify trend momentum shifts and divergence. During practice, traders can explore how MACD signals align with VWAP trends or RSI levels, which helps in building a structured multi-indicator analysis.
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6. Stochastic Oscillator
This indicator compares the current close relative to a range of highs and lows over a period. Displayed values oscillate between 0 and 100, marking zones of overbought (>80) and oversold (<20).
Stochastics are useful for students of trading to recognize short-term momentum changes. Unlike RSI, it reacts faster to price volatility, so false signals are common. Part of the training exercise can be to observe how stochastic “flips” can align with volume surges or daily range endpoints.
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7. Trend & Momentum Classification
The dashboard adds simple labels for trend (uptrend, downtrend, neutral) based on RSI thresholds. Additionally, it provides quick momentum classification (“bullish hold”, “bearish hold”, or neutral).
This is beneficial for beginners as it introduces structured thinking: differentiating long-term market bias (trend) from short-term directional momentum. By combining both, traders can practice filtering signals instead of trading randomly.
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8. Accumulation / Distribution Bias
Based on RSI levels, the script generates simplified tags such as “Accumulate Long”, “Accumulate Short”, or “Wait”.
This is purely an interpretive guide, helping learners think in terms of accumulation phases (when markets are low) and distribution phases (when markets are high). It reinforces the concept that trading is not only directional but also involves timing.
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9. Overall Market Status and Score
Finally, the dashboard compiles multiple indicators (VWAP position, RSI, MACD, Stochastics, and price vs. median levels) into a Market Score expressed as a percentage. It also labels the market as Overbought, Oversold, or Normal.
This scoring system isn’t a recommendation but a learning framework. Students can analyze how combining different indicators improves decision-making. The key training focus here is confluence: not depending on one indicator but observing when several conditions align.
Extended Study Material with Formulas
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1. Daily Reference Levels (High, Low, Open, Median, Range)
• Day High (H): Maximum price of the session.
DayHigh=max(Hightoday)DayHigh=max(Hightoday)
• Day Low (L): Minimum price of the session.
DayLow=min(Lowtoday)DayLow=min(Lowtoday)
• Day Open (O): Opening price of the session.
DayOpen=OpentodayDayOpen=Opentoday
• Day Range:
Range=DayHigh−DayLowRange=DayHigh−DayLow
• Median: Mid-point between high and low.
Median=DayHigh+DayLow2Median=2DayHigh+DayLow
These act as intraday guideposts for seeing how far the price has stretched from its key reference levels.
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2. VWAP (Volume Weighted Average Price)
VWAP considers both price and volume for a weighted average:
VWAPt=∑i=1t(Pricei×Volumei)∑i=1tVolumeiVWAPt=∑i=1tVolumei∑i=1t(Pricei×Volumei)
Here, Price_i can be the average price (High + Low + Close) ÷ 3, also known as hlc3.
• Interpretation: Price above VWAP = bullish bias; Price below = bearish bias.
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3. Volume Buy/Sell Analysis
The dashboard splits total volume into buy volume and sell volume based on candle type.
• Buy Volume:
BuyVol=Volumeif Close > Open, else 0BuyVol=Volumeif Close > Open, else 0
• Sell Volume:
SellVol=Volumeif Close < Open, else 0SellVol=Volumeif Close < Open, else 0
• Buy Ratio (%):
VolumeRatio=BuyVolBuyVol+SellVol×100VolumeRatio=BuyVol+SellVolBuyVol×100
This helps traders gauge who is in control during a session—buyers or sellers.
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4. RSI (Relative Strength Index)
RSI measures strength of momentum by comparing gains vs. losses.
Step 1: Compute average gains (AG) and losses (AL).
AG=Average of Upward Closes over N periodsAG=Average of Upward Closes over N periodsAL=Average of Downward Closes over N periodsAL=Average of Downward Closes over N periods
Step 2: Calculate relative strength (RS).
RS=AGALRS=ALAG
Step 3: RSI formula.
RSI=100−1001+RSRSI=100−1+RS100
• Used to detect overbought (>70), oversold (<30), or neutral momentum zones.
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5. MACD (Moving Average Convergence Divergence)
• Fast EMA:
EMAfast=EMA(Close,length=fast)EMAfast=EMA(Close,length=fast)
• Slow EMA:
EMAslow=EMA(Close,length=slow)EMAslow=EMA(Close,length=slow)
• MACD Line:
MACD=EMAfast−EMAslowMACD=EMAfast−EMAslow
• Signal Line:
Signal=EMA(MACD,length=signal)Signal=EMA(MACD,length=signal)
• Histogram:
Histogram=MACD−SignalHistogram=MACD−Signal
Crossovers between MACD and Signal are used in studying bullish/bearish phases.
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6. Stochastic Oscillator
Stochastic compares the current close against a range of highs and lows.
%K=Close−LowestLowHighestHigh−LowestLow×100%K=HighestHigh−LowestLowClose−LowestLow×100
Where LowestLow and HighestHigh are the lowest and highest values over N periods.
The %D line is a smooth version of %K (using a moving average).
%D=SMA(%K,smooth)%D=SMA(%K,smooth)
• Values above 80 = overbought; below 20 = oversold.
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7. Trend and Momentum Classification
This dashboard generates simplified trend/momentum logic using RSI.
• Trend:
• RSI < 40 → Downtrend
• RSI > 60 → Uptrend
• In Between → Neutral
• Momentum Bias:
• RSI > 70 → Bullish Hold
• RSI < 30 → Bearish Hold
• Otherwise Neutral
This is not predictive, only a classification framework for educational use.
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8. Accumulation/Distribution Bias
Based on extreme RSI values:
• RSI < 25 → Accumulate Long Bias
• RSI > 80 → Accumulate Short Bias
• Else → Wait/No Action
This helps learners understand the idea of accumulation at lows (strength building) and distribution at highs (profit booking).
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9. Overall Market Status and Score
The tool adds up 5 bullish conditions:
1. Price above VWAP
2. RSI > 50
3. MACD > Signal
4. Stochastic > 50
5. Price above Daily Median
BullishScore=ConditionsMet5×100BullishScore=5ConditionsMet×100
Then it categorizes the market:
• RSI > 70 or Stoch > 80 → Overbought
• RSI < 30 or Stoch < 20 → Oversold
• Else → Normal
This encourages learners to think in terms of probabilistic conditions instead of single-indicator signals.
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⚠️ Warning:
• Trading financial markets involves substantial risk.
• You can lose more money than you invest.
• Past performance of indicators does not guarantee future results.
• This script must not be copied, resold, or republished without authorization from aiTrendview.
By using this material or the code, you agree to take full responsibility for your trading decisions and acknowledge that this is not financial advice.
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⚠️ Disclaimer and Warning (From aiTrendview)
This Dynamic Trading Dashboard is created strictly for educational and research purposes on the TradingView platform. It does not provide financial advice, buy/sell recommendations, or guaranteed returns. Any use of this tool in live trading is completely at the user’s own risk. Markets are inherently risky; losses can exceed initial investment.
The intellectual property of this script and its methodology belongs to aiTrendview. Unauthorized reproduction, modification, or redistribution of this code is strictly prohibited. By using this study material or the script, you acknowledge personal responsibility for any trading outcomes. Always consult professional financial advisors before making investment decisions.
Volume-Weighted Money Flow [sgbpulse]Overview
The VWMF indicator is an advanced technical analysis tool that combines and summarizes five leading momentum and volume indicators (OBV, PVT, A/D, CMF, MFI) into one clear oscillator. The indicator helps to provide a clear picture of market sentiment by measuring the pressure from buyers and sellers. Unlike single indicators, VWMF provides a comprehensive view of market money flow by weighting existing indicators and presenting them in a uniform and understandable format.
Indicator Components
VWMF combines the following indicators, each normalized to a range of 0 to 100 before being weighted:
On-Balance Volume (OBV): A cumulative indicator that measures positive and negative volume flow.
Price-Volume Trend (PVT): Similar to OBV, but incorporates relative price change for a more precise measure.
Accumulation/Distribution Line (A/D): Used to identify whether an asset is being bought (accumulated) or sold (distributed).
Chaikin Money Flow (CMF): Measures the money flow over a period based on the close price's position relative to the candle's range.
Money Flow Index (MFI): A momentum oscillator that combines price and volume to measure buying and selling pressure.
Understanding the Normalized Oscillators
The indicator combines the five different momentum indicators by normalizing each one to a uniform range of 0 to 100 .
Why is Normalization Important?
Indicators like OBV, PVT, and the A/D Line are cumulative indicators whose values can become very large. To assess their trend, we use a Moving Average as a dynamic reference line . The Moving Average allows us to understand whether the indicator is currently trending up or down relative to its average behavior over time.
How Does Normalization Work?
Our normalization fully preserves the original trend of each indicator.
For Cumulative Indicators (OBV, PVT, A/D): We calculate the difference between the current indicator value and its Moving Average. This difference is then passed to the normalization process.
- If the indicator is above its Moving Average, the difference will be positive, and the normalized value will be above 50.
- If the indicator is below its Moving Average, the difference will be negative, and the normalized value will be below 50.
Handling Extreme Values: To overcome the issue of extreme values in indicators like OBV, PVT, and the A/D Line , the function calculates the highest absolute value over the selected period. This value is used to prevent sharp spikes or drops in a single indicator from compromising the accuracy of the normalization over time. It's a sophisticated method that ensures the oscillators remain relevant and accurate.
For Bounded Indicators (CMF, MFI): These indicators already operate within a known range (for example, CMF is between -1 and 1, and MFI is between 0 and 100), so they are normalized directly without an additional reference line.
Reference Line Settings:
Moving Average Type: Allows the user to choose between a Simple Moving Average (SMA) and an Exponential Moving Average (EMA).
Volume Flow MA Length: Allows the user to set the lookback period for the Moving Average, which affects the indicator's sensitivity.
The 50 line serves as the new "center line." This ensures that, even after normalization, the determination of whether a specific indicator supports a bullish or bearish trend remains clear.
Settings and Visual Tools
The indicator offers several customization options to provide a rich analysis experience:
VWMF Oscillator (Blue Line): Represents the weighted average of all five indicators. Values above 50 indicate bullish momentum, and values below 50 indicate bearish momentum.
Strength Metrics (Bullish/Bearish Strength %): Two metrics that appear on the status line, showing the percentage of indicators supporting the current trend. They range from 0% to 100%, providing a quick view of the strength of the consensus.
Dynamic Background Colors: The background color of the chart automatically changes to bullish (a blue shade by default) or bearish (a default brown-gray shade) based on the trend. The transparency of the color shows the consensus strength—the more opaque the background, the more indicators support the trend.
Advanced Settings:
- Background Color Logic: Allows the user to choose the trigger for the background color: Weighted Value (based on the combined oscillator) or Strength (based on the majority of individual indicators).
- Weights: Provides full control over the weight of each of the five indicators in the final oscillator.
Using the Data Window
TradingView provides a useful Data Window that allows you to see the exact numerical values of each normalized oscillator separately, in addition to the trend strength data.
You can use this window to:
Get more detailed information on each indicator: Viewing the precise numerical data of each of the five indicators can help in making trading decisions.
Calibrate weights: If you want to manually adjust the indicator weights (in the settings menu), you can do so while tracking the impact of each indicator on the weighted oscillator in the Data Window.
The indicator's default setting is an equal weight of 20% for each of the five indicators.
Alert Conditions
The indicator comes with a variety of built-in alerts that can be configured through the TradingView alerts menu:
VWMF Cross Above 50: An alert when the VWMF oscillator crosses above the 50 line, indicating a potential bullish momentum shift.
VWMF Cross Below 50: An alert when the VWMF oscillator crosses below the 50 line, indicating a potential bearish momentum shift.
Bullish Strength: High But Not Absolute Consensus: An alert when the bullish trend strength reaches 60% or more but is less than 100%, indicating a high but not absolute consensus.
Bullish Strength at 100%: An alert when all five indicators (MFI, OBV, PVT, A/D, CMF) show bullish strength, indicating a full and absolute consensus.
Bearish Strength: High But Not Absolute Consensus: An alert when the bearish trend strength reaches 60% or more but is less than 100%, indicating a high but not absolute consensus.
Bearish Strength at 100%: An alert when all five indicators (MFI, OBV, PVT, A/D, CMF) show bearish strength, indicating a full and absolute consensus.
Summary
The VWMF indicator is a powerful, all-in-one tool for analyzing market momentum, money flow, and sentiment. By combining and normalizing five different indicators into a single oscillator, it offers a holistic and accurate view of the market's underlying trend. Its dynamic visual features and customizable settings, including the ability to adjust indicator weights, provide a flexible experience for both novice and experienced traders. The built-in alerts for momentum shifts and trend consensus make it an effective tool for spotting trading opportunities with confidence. In essence, VWMF distills complex market data into clear, actionable signals.
Important Note: Trading Risk
This indicator is intended for educational and informational purposes only and does not constitute investment advice or a recommendation for trading in any form whatsoever.
Trading in financial markets involves significant risk of capital loss. It is important to remember that past performance is not indicative of future results. All trading decisions are your sole responsibility. Never trade with money you cannot afford to lose.
RTH Levels: VWAP + PDH/PDL + ONH/ONL + IBAlgo Index — Levels Pro (ONH/ONL • PDH/PDL • VWAP±Bands • IB • Gaps)
Purpose. A session-aware, non-repainting levels tool for intraday decision-making. Designed for futures and indices, with clean visuals, alerts, and a one-click Minimal Mode for screenshot-ready charts.
What it plots
• PDH/PDL (RTH-only) – Prior Regular Trading Hours high/low, computed intraday and frozen at the RTH close (no 24h mix-ups, no repainting).
• ONH/ONL – Prior Overnight high/low, held throughout RTH.
• RTH VWAP with ±σ bands – Volume-weighted variance, reset each RTH.
• Initial Balance (IB) – First N minutes of RTH, plus 1.5× / 2.0× extensions after IB completes.
• Today’s RTH Open & Prior RTH Close – With gap detection and “gap filled” alert.
• Killzone shading – NY Open (09:30–10:30 ET) and Lunch (11:15–13:30 ET).
• Values panel (top-right) – Each level with live distance in points & ticks.
• Right-edge level tags – With anti-overlap (stagger + vertical jitter).
• Price-scale tags – Native trackprice markers that always “stick” to the axis.
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New in v6.4
• Minimal Mode: one click for a clean look (thinner lines, VWAP bands/IB extensions hidden, on-chart right-edge labels off; price-scale tags remain).
• Theme presets: Dark Hi-Contrast / Light Minimal / Futures Classic / Muted Dark.
• Anti-overlap controls: horizontal staggering, vertical jitter, and baseline offset to keep tags readable even when levels cluster.
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Quick start (2 minutes)
1. Add to chart → keep defaults.
2. Sessions (ET):
• RTH Session default: 09:30–16:00 (US equities cash hours).
• Overnight Session default: 18:00–09:29.
Adjust for your market if you use different “day” hours (e.g., many use 08:20–13:30 ET for COMEX Gold).
3. Theme & Minimal Mode: pick a Theme Preset; enable Minimal Mode for screenshots.
4. Visibility: toggle PD/ON/VWAP/IB/References/Panel to taste.
5. Right-edge labels: turn Show Right-Edge Labels on. If they crowd, tune:
• Anti-overlap: min separation (ticks)
• Horizontal offset per tag (bars)
• Vertical jitter per step (ticks)
• Right-edge baseline offset (bars)
6. Alerts: open Add alert → Condition: and pick the events you want.
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How levels are computed (no repainting)
• PDH/PDL: Intraday H/L are accumulated only while in RTH and saved at RTH close for “yesterday’s” values.
• ONH/ONL: Accumulated across the defined Overnight window and then held during RTH.
• RTH VWAP & ±σ: Volume-weighted mean and standard deviation, reset at the RTH open.
• IB: First N minutes of RTH (default 60). Extensions (1.5×/2.0×) appear after IB completes.
• Gaps: Today’s RTH open vs prior RTH close; “Gap Filled” triggers when price trades back to prior close.
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Practical playbooks (how to trade around the levels)
1) PDH/PDL interactions
• Rejection: Price taps PDH/PDL then closes back inside → mean-reversion toward VWAP/IB.
• Acceptance: Close/hold beyond PDH/PDL with momentum → continuation to next HTF/IB target.
• Alert: PD Touch/Break.
2) ONH/ONL “taken”
• Often one ON extreme is taken during RTH. ONH Taken / ONL Taken → check if it’s a clean break or sweep & reclaim.
• Sweep + reclaim near VWAP can fuel rotations through the ON range.
3) VWAP ±σ framework
• Balanced: First tag of ±1σ often reverts toward VWAP.
• Trend: Persistent trade beyond ±1σ + IB break → target ±2σ/±3σ.
• Alerts: VWAP Cross and VWAP Reject (cross then immediate fail back).
4) IB breaks
• After IB completes, a clean IB break commonly targets 1.5× and sometimes 2.0×.
• Quick return inside IB = possible fade back to the opposite IB edge/VWAP.
• Alerts: IB Break Up / Down.
5) Gaps
• Gap-and-go: Opening drive away from prior close + VWAP support → trend until IB completion.
• Gap-fill: Weak open and VWAP overhead/underfoot → trade toward prior close; manage on Gap Filled alert.
Pro tip: Stack confluences (e.g., ONL sweep + VWAP reclaim + IB hold) and respect your execution rules (e.g., require a 5-minute close in direction, or your order-flow confirmation).
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Inputs you’ll actually touch
• Sessions (ET): Session Timezone, RTH Session, Overnight Session.
• Visibility: toggles for PD/ON/VWAP/IB/Ref/Panel.
• VWAP bands: set σ multipliers (±1/±2/±3).
• IB: duration (minutes) and extension multipliers (1.5× / 2.0×).
• Style & Theme: Theme Preset, Main Line Width, Trackprice, Minimal Mode, and anti-overlap controls.
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Alerts included
• PD Touch/Break — High ≥ PDH or Low ≤ PDL
• ONH Taken / ONL Taken — First in-RTH take of ONH/ONL
• VWAP Cross — Close crosses VWAP
• VWAP Reject — Cross then immediate fail back
• IB Break Up / Down — Break of IB High/Low after IB completes
• Gap Filled — Price trades back to prior RTH close
Setup: Add alert → Condition: Algo Index — Levels Pro → choose event → message → Notify on app/email.
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Panel guide
The top-right panel shows each level plus live distance from last price:
LevelValue (Δpoints | Δticks)
Coloring: green if level is below current price, red if above.
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Styling & screenshot tips
• Use Theme Preset that matches your chart.
• For dark charts, “Dark Hi-Contrast” with Main Line Width = 3 works well.
• Enable Trackprice for crisp axis tags that always stick to the right edge.
• Turn on Minimal Mode for cleaner screenshots (no VWAP bands or IB extensions, on-chart tags off; price-scale tags remain).
• If tags crowd, increase min separation (ticks) to 30–60 and horizontal offset to 3–5; add vertical jitter (4–12 ticks) and/or push tags farther right with baseline offset (bars).
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Behavior & limitations
• Levels are computed incrementally; tables refresh on the last bar for efficiency.
• Right-edge labels are placed at bar_index + offset and do not track extra right-margin scrolling (TradingView limitation). The price-scale tags (from trackprice) do track the axis.
• “RTH” is what you define in inputs. If your market uses different day hours, change the session strings so PDH/PDL reflect your definition of “yesterday’s session.”
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FAQ
Q: My PDH/PDL don’t match the daily chart.
A: By design this uses RTH-only highs/lows, not 24h daily bars. Adjust sessions if you want a different definition.
Q: Right-edge tags overlap or don’t sit at the far right.
A: Increase min separation / horizontal offset / vertical jitter and/or push tags farther with baseline offset. If you want markers that always hug the axis, rely on Trackprice.
Q: Can I change killzones?
A: Yes—edit the session strings in settings or request a version with user inputs for custom windows.
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Disclaimer
Educational use only. This is not financial advice. Always apply your own risk management and confirmation rules.
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Malama's KAYCAP Pre-Market Box# Pre-Market Single Candle Range Box
## What Makes This Script Original
While many scripts plot entire pre-market session ranges, this indicator focuses specifically on **a single user-defined candle** within the pre-market period rather than the entire session. This targeted approach allows traders to isolate the most relevant price action from a specific time (default: 4:00 AM EST) that often establishes key levels for the trading day.
## Core Methodology & Technical Implementation
**Single Candle Isolation:**
- Captures OHLC data from one specific minute within pre-market hours (user configurable)
- Differentiates between the candle's body (open/close range) and wicks (high/low extremes)
- Creates four distinct reference levels instead of traditional session high/low boxes
**Dual Box Structure:**
- **Inner Box (Body):** Plots the range between open and close prices of the target candle
- **Outer Boundaries:** Separately plots the high and low of that same candle
- **Visual Differentiation:** Uses different colors and line weights to distinguish body vs. wick levels
**Time-Specific Logic:**
The script uses precise time matching (`hour == boxHour and minute == boxMinute`) to capture data from exactly one candle, rather than aggregating an entire session. This creates four specific price levels:
- Box Top: Higher of open/close (body boundary)
- Box Bottom: Lower of open/close (body boundary)
- Box High: Candle high (wick extreme)
- Box Low: Candle low (wick extreme)
## Why This Approach Differs from Standard Session Boxes
**vs. Full Session Ranges:** Focuses on a single critical minute rather than entire pre-market period
**vs. Traditional S/R:** Creates both body and wick levels from one specific candle
**vs. Opening Range:** Uses pre-market data rather than regular session opening minutes
## Practical Application
The 4:00 AM EST default targets a time when institutional pre-market activity often establishes initial sentiment and key levels. By isolating this specific candle's range:
- **Body levels** often act as initial support/resistance during regular hours
- **Wick extremes** provide broader range boundaries for breakout analysis
- **Precise timing** allows focus on the most statistically relevant pre-market moment
## Technical Considerations
- Requires intraday timeframes (1-minute recommended) to capture specific candle data
- Time settings should match your broker's timezone for accurate candle selection
- Works best on liquid instruments where pre-market activity is meaningful
- The selected candle must exist in your data feed for the levels to plot
## Customization Options
All timing parameters are adjustable:
- Target candle hour and minute
- Pre-market session definition (for context)
- Visual styling for all four level types
This focused approach provides more granular analysis than broad session ranges while maintaining simplicity in execution.
Machine Learning BBPct [BackQuant]Machine Learning BBPct
What this is (in one line)
A Bollinger Band %B oscillator enhanced with a simplified K-Nearest Neighbors (KNN) pattern matcher. The model compares today’s context (volatility, momentum, volume, and position inside the bands) to similar situations in recent history and blends that historical consensus back into the raw %B to reduce noise and improve context awareness. It is informational and diagnostic—designed to describe market state, not to sell a trading system.
Background: %B in plain terms
Bollinger %B measures where price sits inside its dynamic envelope: 0 at the lower band, 1 at the upper band, ~ 0.5 near the basis (the moving average). Readings toward 1 indicate pressure near the envelope’s upper edge (often strength or stretch), while readings toward 0 indicate pressure near the lower edge (often weakness or stretch). Because bands adapt to volatility, %B is naturally comparable across regimes.
Why add (simplified) KNN?
Classic %B is reactive and can be whippy in fast regimes. The simplified KNN layer builds a “nearest-neighbor memory” of recent market states and asks: “When the market looked like this before, where did %B tend to be next bar?” It then blends that estimate with the current %B. Key ideas:
• Feature vector . Each bar is summarized by up to five normalized features:
– %B itself (normalized)
– Band width (volatility proxy)
– Price momentum (ROC)
– Volume momentum (ROC of volume)
– Price position within the bands
• Distance metric . Euclidean distance ranks the most similar recent bars.
• Prediction . Average the neighbors’ prior %B (lagged to avoid lookahead), inverse-weighted by distance.
• Blend . Linearly combine raw %B and KNN-predicted %B with a configurable weight; optional filtering then adapts to confidence.
This remains “simplified” KNN: no training/validation split, no KD-trees, no scaling beyond windowed min-max, and no probabilistic calibration.
How the script is organized (by input groups)
1) BBPct Settings
• Price Source – Which price to evaluate (%B is computed from this).
• Calculation Period – Lookback for SMA basis and standard deviation.
• Multiplier – Standard deviation width (e.g., 2.0).
• Apply Smoothing / Type / Length – Optional smoothing of the %B stream before ML (EMA, RMA, DEMA, TEMA, LINREG, HMA, etc.). Turning this off gives you the raw %B.
2) Thresholds
• Overbought/Oversold – Default 0.8 / 0.2 (inside ).
• Extreme OB/OS – Stricter zones (e.g., 0.95 / 0.05) to flag stretch conditions.
3) KNN Machine Learning
• Enable KNN – Switch between pure %B and hybrid.
• K (neighbors) – How many historical analogs to blend (default 8).
• Historical Period – Size of the search window for neighbors.
• ML Weight – Blend between raw %B and KNN estimate.
• Number of Features – Use 2–5 features; higher counts add context but raise the risk of overfitting in short windows.
4) Filtering
• Method – None, Adaptive, Kalman-style (first-order),
or Hull smoothing.
• Strength – How aggressively to smooth. “Adaptive” uses model confidence to modulate its alpha: higher confidence → stronger reliance on the ML estimate.
5) Performance Tracking
• Win-rate Period – Simple running score of past signal outcomes based on target/stop/time-out logic (informational, not a robust backtest).
• Early Entry Lookback – Horizon for forecasting a potential threshold cross.
• Profit Target / Stop Loss – Used only by the internal win-rate heuristic.
6) Self-Optimization
• Enable Self-Optimization – Lightweight, rolling comparison of a few canned settings (K = 8/14/21 via simple rules on %B extremes).
• Optimization Window & Stability Threshold – Governs how quickly preferred K changes and how sensitive the overfitting alarm is.
• Adaptive Thresholds – Adjust the OB/OS lines with volatility regime (ATR ratio), widening in calm markets and tightening in turbulent ones (bounded 0.7–0.9 and 0.1–0.3).
7) UI Settings
• Show Table / Zones / ML Prediction / Early Signals – Toggle informational overlays.
• Signal Line Width, Candle Painting, Colors – Visual preferences.
Step-by-step logic
A) Compute %B
Basis = SMA(source, len); dev = stdev(source, len) × multiplier; Upper/Lower = Basis ± dev.
%B = (price − Lower) / (Upper − Lower). Optional smoothing yields standardBB .
B) Build the feature vector
All features are min-max normalized over the KNN window so distances are in comparable units. Features include normalized %B, normalized band width, normalized price ROC, normalized volume ROC, and normalized position within bands. You can limit to the first N features (2–5).
C) Find nearest neighbors
For each bar inside the lookback window, compute the Euclidean distance between current features and that bar’s features. Sort by distance, keep the top K .
D) Predict and blend
Use inverse-distance weights (with a strong cap for near-zero distances) to average neighbors’ prior %B (lagged by one bar). This becomes the KNN estimate. Blend it with raw %B via the ML weight. A variance of neighbor %B around the prediction becomes an uncertainty proxy ; combined with a stability score (how long parameters remain unchanged), it forms mlConfidence ∈ . The Adaptive filter optionally transforms that confidence into a smoothing coefficient.
E) Adaptive thresholds
Volatility regime (ATR(14) divided by its 50-bar SMA) nudges OB/OS thresholds wider or narrower within fixed bounds. The aim: comparable extremeness across regimes.
F) Early entry heuristic
A tiny two-step slope/acceleration probe extrapolates finalBB forward a few bars. If it is on track to cross OB/OS soon (and slope/acceleration agree), it flags an EARLY_BUY/SELL candidate with an internal confidence score. This is explicitly a heuristic—use as an attention cue, not a signal by itself.
G) Informational win-rate
The script keeps a rolling array of trade outcomes derived from signal transitions + rudimentary exits (target/stop/time). The percentage shown is a rough diagnostic , not a validated backtest.
Outputs and visual language
• ML Bollinger %B (finalBB) – The main line after KNN blending and optional filtering.
• Gradient fill – Greenish tones above 0.5, reddish below, with intensity following distance from the midline.
• Adaptive zones – Overbought/oversold and extreme bands; shaded backgrounds appear at extremes.
• ML Prediction (dots) – The KNN estimate plotted as faint circles; becomes bright white when confidence > 0.7.
• Early arrows – Optional small triangles for approaching OB/OS.
• Candle painting – Light green above the midline, light red below (optional).
• Info panel – Current value, signal classification, ML confidence, optimized K, stability, volatility regime, adaptive thresholds, overfitting flag, early-entry status, and total signals processed.
Signal classification (informational)
The indicator does not fire trade commands; it labels state:
• STRONG_BUY / STRONG_SELL – finalBB beyond extreme OS/OB thresholds.
• BUY / SELL – finalBB beyond adaptive OS/OB.
• EARLY_BUY / EARLY_SELL – forecast suggests a near-term cross with decent internal confidence.
• NEUTRAL – between adaptive bands.
Alerts (what you can automate)
• Entering adaptive OB/OS and extreme OB/OS.
• Midline cross (0.5).
• Overfitting detected (frequent parameter flipping).
• Early signals when early confidence > 0.7.
These are purely descriptive triggers around the indicator’s state.
Practical interpretation
• Mean-reversion context – In range markets, adaptive OS/OB with ML smoothing can reduce whipsaws relative to raw %B.
• Trend context – In persistent trends, the KNN blend can keep finalBB nearer the mid/upper region during healthy pullbacks if history supports similar contexts.
• Regime awareness – Watch the volatility regime and adaptive thresholds. If thresholds compress (high vol), “OB/OS” comes sooner; if thresholds widen (calm), it takes more stretch to flag.
• Confidence as a weight – High mlConfidence implies neighbors agree; you may rely more on the ML curve. Low confidence argues for de-emphasizing ML and leaning on raw %B or other tools.
• Stability score – Rising stability indicates consistent parameter selection and fewer flips; dropping stability hints at a shifting backdrop.
Methodological notes
• Normalization uses rolling min-max over the KNN window. This is simple and scale-agnostic but sensitive to outliers; the distance metric will reflect that.
• Distance is unweighted Euclidean. If you raise featureCount, you increase dimensionality; consider keeping K larger and lookback ample to avoid sparse-neighbor artifacts.
• Lag handling intentionally uses neighbors’ previous %B for prediction to avoid lookahead bias.
• Self-optimization is deliberately modest: it only compares a few canned K/threshold choices using simple “did an extreme anticipate movement?” scoring, then enforces a stability regime and an overfitting guard. It is not a grid search or GA.
• Kalman option is a first-order recursive filter (fixed gain), not a full state-space estimator.
• Hull option derives a dynamic length from 1/strength; it is a convenience smoothing alternative.
Limitations and cautions
• Non-stationarity – Nearest neighbors from the recent window may not represent the future under structural breaks (policy shifts, liquidity shocks).
• Curse of dimensionality – Adding features without sufficient lookback can make genuine neighbors rare.
• Overfitting risk – The script includes a crude overfitting detector (frequent parameter flips) and will fall back to defaults when triggered, but this is only a guardrail.
• Win-rate display – The internal score is illustrative; it does not constitute a tradable backtest.
• Latency vs. smoothness – Smoothing and ML blending reduce noise but add lag; tune to your timeframe and objectives.
Tuning guide
• Short-term scalping – Lower len (10–14), slightly lower multiplier (1.8–2.0), small K (5–8), featureCount 3–4, Adaptive filter ON, moderate strength.
• Swing trading – len (20–30), multiplier ~2.0, K (8–14), featureCount 4–5, Adaptive thresholds ON, filter modest.
• Strong trends – Consider higher adaptive_upper/lower bounds (or let volatility regime do it), keep ML weight moderate so raw %B still reflects surges.
• Chop – Higher ML weight and stronger Adaptive filtering; accept lag in exchange for fewer false extremes.
How to use it responsibly
Treat this as a state descriptor and context filter. Pair it with your execution signals (structure breaks, volume footprints, higher-timeframe bias) and risk management. If mlConfidence is low or stability is falling, lean less on the ML line and more on raw %B or external confirmation.
Summary
Machine Learning BBPct augments a familiar oscillator with a transparent, simplified KNN memory of recent conditions. By blending neighbors’ behavior into %B and adapting thresholds to volatility regime—while exposing confidence, stability, and a plain early-entry heuristic—it provides an informational, probability-minded view of stretch and reversion that you can interpret alongside your own process.
Capiba Custom RSI with Divergences v2
🇬🇧 English
Summary
This indicator is an enhanced and customizable version of the classic RSI, designed to provide clearer and more powerful trading signals. It combines an alternative, more price-sensitive RSI calculation with an automatic divergence detection, which is one of the most effective tools for predicting trend reversals and finding high-probability entry and exit points.
Built upon the compilation of knowledge and open-source codes from the community, this script has been refined to be an all-in-one tool for traders who base their strategies on momentum and trend exhaustion.
Key Features and How to Use
Ultimate RSI and Signal Line (Momentum)
What it is: The main indicator (white line) is an RSI variation that reacts more dynamically to changes in price volatility. It is accompanied by a signal line (orange, by default), which is a moving average of the RSI itself, serving to smooth the indicator and generate crossover signals.
How to use for Entries/Exits:
Buy Signal (Short-Term): Crossover of the RSI line (white) above the signal line (orange).
Sell Signal (Short-Term): Crossover of the RSI line (white) below the signal line (orange). These are momentum signals, ideal for confirming a trend or for scalping.
Automatic Divergence Detection (Reversal Signals) This is the most powerful feature of the indicator. A divergence occurs when the price moves in one direction and the momentum indicator moves in the opposite direction, signaling a likely exhaustion of the current trend.
Bullish Divergence (Green Line):
What it is: The price makes a lower low, but the RSI makes a higher low.
Meaning: Selling pressure is decreasing. It is a strong signal of a potential market bottom and an excellent entry opportunity for a long position.
Bearish Divergence (Red Line):
What it is: The price makes a higher high, but the RSI makes a lower high.
Meaning: Buying pressure is losing strength. It is a strong signal of a potential market top and an excellent exit opportunity for a long position or an entry for a short position.
Customizable Overbought & Oversold Levels
The horizontal lines (default 80 and 20) and the colored areas show when the asset is overextended to the upside (overbought) or downside (oversold), helping to contextualize the divergence and crossover signals.
Recommended Strategy
For maximum effectiveness, combine the signals:
High-Probability Entry (Buy): Look for a Bullish Divergence (green line) forming in the oversold zone. Confirm the entry when the RSI line crosses above its signal line.
High-Probability Exit (Sell): Look for a Bearish Divergence (red line) forming in the overbought zone. Confirm the exit or new short entry when the RSI line crosses below its signal line.
Acknowledgements
This indicator was developed by compiling and customizing excellent open-source ideas and codes shared by the TradingView community. Special thanks to everyone who contributes to the advancement of technical analysis.
