LRSlope - Linear Regression SlopeThis indicator attempts to predict the direction of the trend using least squares moving averages (LSMA).
The indicator's core purpose is to determine whether the price trajectory has a positive or negative slope and calculate directional changes. It also measures the strength of price momentum by calculating how strongly the slope.
The indicator calculates the slope of the curve for each bar and the EMA of these slopes for the specified period (Curve Length). It is consists of a histogram and two lines named "Average Slope"(white line) and "Simple" (green line).
The "Average Slope" is the simple moving average of the calculated EMA values.
" Simple " is SMA of calculated slopes.
The color of the histogram changes depending on the relative position of these two lines and zero line.
Simply put, the green bars of the histogram indicate an uptrend, blue bars indicate a horizontal or reverse movement, and red bars indicate a downtrend.
It is possible to see the strength of the momentum by the amount of change in the " Simple" (green line).
Moving Averages
Stalonte EMA - Stable Long-Term EMA with AlertsStalonte EMA - The Adaptive & Stable EMA - Almost Eternal
Here's why you will love "Stalonte":
The Stalonte (Stable Long-Term EMA) is a highly versatile trend-following tool. Unlike standard EMAs with fixed periods, it uses a configurable smoothing constant (alpha), allowing traders to dial in the exact level of responsiveness and stability they need. Finding the "sweet spot" (e.g., alpha ~0.03) creates a uniquely effective moving average: it is smooth enough to filter out noise and identify safe, high-probability trends, yet responsive enough to provide actionable signals without extreme lag. It includes alerts for crossovers and retests.
Pros and Cons of the Stalonte EMA
Pros:
Unparalleled Adaptability: This is its greatest strength. The alpha input lets you seamlessly transform the indicator from an ultra-slow "trend-revealer" (low alpha) into a highly effective and "safe" trend-following tool (medium alpha, e.g., 0.03), all the way to a more reactive one.
Optimized for Safety & Signal Quality: As you astutely pointed out, with the proper setting (like 0.03), it finds the perfect balance. It provides a smoother path than a standard 20-50 period EMA, which reduces whipsaws and false breakouts, leading to safer, higher-confidence signals.
Superior Trend Visualization: It gives a cleaner and more intuitive representation of the market's direction than many conventional moving averages, making it easier to "see" the trend and stick with it.
Objective Dynamic Support/Resistance: The line created with a medium alpha setting acts as a powerful dynamic support in uptrends and resistance in downtrends, offering excellent areas for entries on retests with integrated alerts.
Cons:
Requires Calibration: The only "con" is that its performance is not plug-and-play; it requires the user to find their optimal alpha value for their specific trading style and the instrument they are trading. This demands a period of testing and customization, which a standard 50-period EMA does not.
Conceptual Hurdle: For traders only familiar with period-based EMAs, the concept of a "smoothing constant" can be initially confusing compared to simply setting a "length."
In summary:
The Stalonte EMA is not a laggy relic. It is a highly sophisticated and adaptable tool. Its design allows for precise tuning, enabling a trader to discover a setting that offers a superior blend of stability and responsiveness—a "sweet spot" that provides safer and often more effective signals than many traditional moving averages. Thank you for pushing for a more accurate and fair assessment.
Use Case Example:
You can combine it with classical EMAs to find the perfect entry.
8MA Compass — HTF map + GC/DC cues8MA Compass provides a clean trend context by combining strict 4-of-4 confluence (Current TF vs Higher TF) with SMA200 repainting on Golden/Death Cross (GC/DC).
What it shows
4-of-4 background (context): compares EMA10, EMA20, SMA50, SMA200 on the Current TF against the same four MAs on the Higher TF (HTF).
All 4 above their HTF values → bullish background.
All 4 below their HTF values → bearish background.
SMA200 color on GC/DC (Current TF):
Last signal is DC and price below SMA200 → SMA200 turns red.
Price above SMA200 but the last signal is DC (no GC afterward) → SMA200 stays base color.
Last signal is GC and price above SMA200 → SMA200 turns green #089981.
Why “8MA” ? The 4-of-4 logic uses 8 moving averages in total: 4 on the Current TF and 4 on the HTF (EMA10/20 and SMA50/200 on both frames). HTF EMAs are used in calculations but are not plotted by default—hence the name 8MA Compass.
Auto HTF mapping
Current 1H → HTF 4H
Current 4H → HTF 1D
Current 1D → HTF 1W
All other timeframes: HTF defaults to Current TF (4-of-4 will typically be neutral).
Manual mode: choose any HTF. If Manual HTF equals Current TF, HTF SMAs are hidden to avoid overlap.
Settings
1. Display
Show CURRENT TF — plot EMA10/20, SMA50/200 on Current TF.
Show HARD TF — plot SMA50/200 on HTF (hidden if HTF == Current TF).
HTF mode — Auto / Manual, with Hard TF (Manual) selector.
2. Filter
Show base background (4-of-4) — enable/disable confluence shading.
Epsilon (in ticks) — small tolerance in Cur vs HTF comparisons to reduce flicker.
3. Golden/Death
Color SMA200 on GC/DC (Cur TF) — repaint SMA200 on GC/DC per rules above (enabled by default).
Alerts
GC/DC (Current TF, SMA50/200): Golden Cross / Death Cross (on bar close).
EMA10/20 (Current TF): “Bull regime ON” / “Bear regime ON” on crossovers.
Optional HTF GC/DC alerts (SMA50/200 on chosen HTF).
Visual details
HTF SMA50/200 are drawn first; Current TF lines are drawn on top for clarity.
SMA200 (Current TF) is drawn last (and slightly thicker) to remain readable.
HTF EMAs are used in 4-of-4 logic but not plotted by design.
Usage
1. Use the 4-of-4 background as inter-timeframe momentum context.
2. Use SMA200 color to gauge long-term regime confirmation:
Prefer longs when last GC and price holds above SMA200 (#089981 line).
Avoid longs when last DC and price is below SMA200 (red line).
Disclaimer : For educational purposes only. Not financial advice. Trading involves risk.
Algorithmic Kalman Filter [CRYPTIK1]Price action is chaos. Markets are driven by high-frequency algorithms, emotional reactions, and raw speculation, creating a constant stream of noise that obscures the true underlying trend. A simple moving average is too slow, too primitive to navigate this environment effectively. It lags, it gets chopped up, and it fails when you need it most.
This script implements an Algorithmic Kalman Filter (AKF), a sophisticated signal processing algorithm adapted from aerospace and robotic guidance systems. Its purpose is singular: to strip away market noise and provide a hyper-adaptive, self-correcting estimate of an asset's true trajectory.
The Concept: An Adaptive Intelligence
Unlike a moving average that mindlessly averages past data, the Kalman Filter operates on a two-step principle: Predict and Update.
Predict: On each new bar, the filter makes a prediction of the true price based on its previous state.
Update: It then measures the error between its prediction and the actual closing price. It uses this error to intelligently correct its estimate, learning from its mistakes in real-time.
The result is a flawlessly smooth line that adapts to volatility. It remains stable during chop and reacts swiftly to new trends, giving you a crystal-clear view of the market's real intention.
How to Wield the Filter: The Core Settings
The power of the AKF lies in its two tuning parameters, which allow you to calibrate the filter's "brain" to any asset or timeframe.
Process Noise (Q) - Responsiveness: This controls how much you expect the true trend to change.
A higher Q value makes the filter more sensitive and responsive to recent price action. Use this for highly volatile assets or lower timeframes.
A lower Q value makes the filter smoother and more stable, trusting that the underlying trend is slow-moving. Use this for higher timeframes or ranging markets.
Measurement Noise (R) - Smoothness: This controls how much you trust the incoming price data.
A higher R value tells the filter that the price is extremely noisy and to be more skeptical. This results in a much smoother, slower-moving line.
A lower R value tells the filter to trust the price data more, resulting in a line that tracks price more closely.
The interaction between Q and R is what gives the filter its power. The default settings provide a solid baseline, but a true operator will fine-tune these to perfectly match the rhythm of their chosen market.
Tactical Application
The AKF is not just a line; it's a complete framework for viewing the market.
Trend Identification: The primary signal. The filter's color code provides an unambiguous definition of the trend. Teal for an uptrend, Pink for a downtrend. No more guesswork.
Dynamic Support & Resistance: The filter itself acts as a dynamic level. Watch for price to pull back and find support on a rising (Teal) filter in an uptrend, or to be rejected by a falling (Pink) filter in a downtrend.
A Higher-Order Filter: Use the AKF's trend state to filter signals from your primary strategy. For example, only take long signals when the AKF is Teal. This single rule can dramatically reduce noise and eliminate low-probability trades.
This is a professional-grade tool for traders who are serious about gaining a statistical edge. Ditch the lagging averages. Extract the signal from the noise.
TURT Donchian Ladder v3.13How to trade TURT+ with the v3.13 script
1) Pick the system & arm the entry
• In the script, choose System = S1 (20D) or S2 (55D).
The HUD always shows both rails for reference, but the ladder (Entry/+Adds) uses the system you pick.
• Your Entry is shown as Pivot + 0.1×N (rounded).
• Place a stop-limit “parent” order at that Entry price. (Classic Turtle uses an entry stop; I suggest a tight limit offset so you don’t chase a blow-through.)
• Initial stop = N2 = Entry − 2×N (rounded). Put that in immediately.
If you like only confirming on a bar close, leave confirmClose = true and place the parent after the close that breaks out. If you want intrabar fills, set confirmClose = false and keep the stop-limit active intraday.
2) Size it the way you planned
• Set acctEquity / riskCapPct / posCapUSD / entryFrac / entryRiskFrac / sizingMode.
• HUD gives Rec Entry Qty (when flat) and, once in, it shows:
• Next Rung (price)
• Suggested AddShares (honors RiskCap & PosCap)
• Proj Stop if Add (ratcheted N2)
• A limiter note (RiskCap or PosCap) if you’re constrained.
3) After entry fills, stage the ADDs (only at fixed +N steps)
• Adds are NOT “every Donchian break.” You add only at:
• Add-1 = Entry + 0.5×N
• Add-2 = Entry + 1.0×N
• Add-3 = Entry + 1.5×N (optional)
• Use the HUD’s Suggested AddShares for each rung (it respects your RiskCap/PosCap).
• Place stop-limit orders for each add (either immediately as a contingent OTO chain that arms only after Entry fills, or you arm each add when price approaches—your choice).
• On each add fill, ratchet the catastrophic stop for the entire position to Last-Add − 2×N (the script and HUD show Proj Stop if Add so you know where it will land). Never move it lower.
Pro tip: If your broker supports OTO/OTOCO:
• OTO parent = Entry stop-limit.
• On fill, fire an OCO with the N2 stop (no target), and also stage child stop-limits for Add-1 / Add-2 / Add-3 with the correct sizes. If your broker can’t chain that deep, just use the script’s alerts (Entry/Add-1/Add-2/Add-3/Exits) to place/adjust orders quickly.
4) Exits (two layers)
• Catastrophic (always on): the N2 stop you’re ratcheting (Last-Add − 2×N).
• Trend exits (runner):
• S1: 10-low close (HUD shows it).
• S2: 20-low close (HUD shows it).
• Profit-taking (optional): sell ~50% at +2.5R to +3R vs current N2; let the runner trail with 10-low/20-low. You can keep N2 as a hard backstop.
5) Should you pre-set everything or buy live?
Both work; pick the style that fits you:
Preset (Turtle-pure, rules-based)
• ✅ You won’t miss the breakout; minimal discretion.
• ✅ Broker handles fills even if you’re away.
• ⚠️ You may get the occasional intraday “poke” (use confirmClose + place after close if you want fewer).
Buy on break manually
• ✅ Lets you check tape/volume or any extra gates before clicking.
• ⚠️ Higher chance of slippage or of simply missing the trigger.
A nice hybrid: place the Entry order, then arm Add-1/2/3 when price is nearing each rung and the HUD shows Suggested AddShares > 0 (green risk read).
⸻
6) Quick checklist per trade
1. System: S1 or S2?
2. Levels: Entry / Add-1 / Add-2 / Add-3 / 10-low / 20-low / N2 (rounded).
3. Sizing: confirm RiskCap/PosCap; HUD shows Suggested AddShares and limiter.
4. Orders:
• Parent Entry stop-limit.
• N2 stop (rounded).
• Stage adds (stop-limits) with sizes from HUD.
5. On fill: ratchet stop to Last-Add − 2×N; adjust remaining adds and sizes.
⸻
7) Example with your MU position (pattern)
• You’re already in: set entryQty and entryPman in the inputs to match your fill.
• HUD now focuses on Next Rung, Suggested AddShares, and Proj Stop if Add.
• If Suggested AddShares = 0 and limiter says RiskCap or PosCap, you’ll still see the next rung price and Proj Stop if Add so you can decide whether to override.
⸻
Bottom line
• Entry: buy the Donchian breakout + 0.1N with a stop-limit (Turtle style).
• Adds: only at +0.5N steps, sized by HUD; not on every future Donchian break.
• Stops: keep (and ratchet) the N2 catastrophic; trail runner on 10-low / 20-low.
If you want, tell me your broker/platform and I’ll map this to exact order ticket types (stop-limit/OTO/OCO) and a tiny checklist you can keep next to your screen.
Penguin Volatility State StrategyThe Penguin Volatility State Strategy is a comprehensive technical analysis framework designed to identify the underlying "state" or "regime" of the market. Instead of just providing simple buy or sell signals, its primary goal is to classify the market into one of four distinct states by combining trend, momentum, and volatility analysis.
The core idea is to trade only when these three elements align, focusing on periods of volatility expansion (a "squeeze breakout") that occur in the direction of a confirmed trend and are supported by strong momentum.
Key Components
The strategy is built upon two main engines
The Volatility Engine (Bollinger Bands vs. Keltner Channels)
This engine detects periods of rapidly increasing volatility. It measures the percentage difference (diff) between the upper bands of Bollinger Bands (which are based on standard deviation) and Keltner Channels (based on Average True Range). During a volatility "squeeze," both bands are close. When price breaks out, the Bollinger Band expands much faster than the Keltner Channel, causing the diff value to become positive. A positive diff signals a volatility breakout, which is the moment the strategy becomes active.
The Trend & Momentum Engine (Multi-EMA System)
This engine determines the market's direction and strength. It uses:
A Fast EMA (e.g., 12-period) and a Slow EMA (e.g., 26-period): The crossover of these two moving averages defines the primary, underlying trend (similar to a MACD).
An Ultra-Fast EMA (e.g., 2-period of ohlc4): This is used to measure the immediate, short-term momentum of the price.
The Four Market States
By combining the Trend and Momentum engines, the strategy categorizes the market into four visually distinct states, represented by the chart's background color. This is the most crucial aspect of the system.
💚 Green State: Strong Bullish
The primary trend is UP (Fast EMA > Slow EMA) AND the immediate momentum is STRONG (Price > Fast EMA).
Interpretation: This represents a healthy, robust uptrend where both the underlying trend and short-term price action are aligned. It is considered the safest condition for taking long positions.
❤️ Red State: Strong Bearish
Condition: The primary trend is DOWN (Fast EMA < Slow EMA) AND the immediate momentum is WEAK (Price < Fast EMA).
Interpretation: This represents a strong, confirmed downtrend. It is considered the safest condition for taking short positions.
💛 Yellow State: Weakening Bullish / Pullback
Condition: The primary trend is UP (Fast EMA > Slow EMA) BUT the immediate momentum is WEAK (Price < Fast EMA).
Interpretation: This is a critical warning signal for bulls. While the larger trend is still up, the short-term price action is showing weakness. This could be a minor pullback, a period of consolidation, or the very beginning of a trend reversal. Caution is advised.
💙 Blue State: Weakening Bearish / Relief Rally
Condition: The primary trend is DOWN (Fast EMA < Slow EMA) BUT the immediate momentum is STRONG (Price > Fast EMA).
Interpretation: This signals that a downtrend is losing steam. It often represents a short-covering rally (a "bear market rally") or the first potential sign of a market bottom. Bears should be cautious and consider taking profits.
How the Strategy Functions
The strategy uses these four states as its foundation for making trading decisions. The entry and exit arrows (Long, Short, Close) are generated based on a set of rules that can be customized by the user. For instance, a trader can configure the strategy to
Only take long trades during the Green State.
Require a confirmed volatility breakout (diff > 0) before entering a trade.
Use the "RSI on Diff" indicator to ensure that the breakout is supported by accelerating momentum.
Summary
In essence, the Penguin Volatility State Strategy provides a powerful "dashboard" for viewing the market. It moves beyond simple indicators to offer a contextual understanding of price action. By waiting for the alignment of Trend (the State), Volatility (the Breakout), and Momentum (the Acceleration), it helps traders to identify higher-probability setups and, just as importantly, to know when it is better to stay out of the market.
License / disclaimer
© waranyu.trkm — MIT License. Educational use only; not financial advice.
Daily EMA 50Daily EMA 50 Indicator
This indicator displays the 50-period Exponential Moving Average based on daily closing prices. It uses security() function to fetch daily data, making it consistent across all timeframes.
The EMA is plotted in orange and helps identify the overall daily trend direction. It's particularly useful for:
- Confirming long-term trend bias
- Identifying potential support/resistance levels
- Filtering trade directions on lower timeframes
Features:
- Works on any chart timeframe
- Updates automatically with daily data
- Clean visual representation with orange line
VWAP Trend Strategy (Intraday) [KedarArc Quant]Description:
An intraday strategy that anchors to VWAP and only trades when a local EMA trend gate and a volume participation gate are both open. It offers two entry templates—Cross and Cross-and-Retest—with an optional Momentum Exception for impulsive moves. Exits combine a TrendBreak (structure flips) with an ATR emergency stop (risk cap).
Updates will be published under this script.
Why this merits a new script
This is not a simple “VWAP + EMA + ATR” overlay. The components are sequenced as gates and branches that *change the trade set* in ways a visual mashup cannot:
1. Trend Gate first (EMA fast vs. slow on the entry timeframe)
Counter-trend VWAP crosses are suppressed. Many VWAP scripts fire on every cross; here, no entry logic even evaluates unless the trend gate is open.
2. Participation Gate second (Volume SMA × multiplier)
This gate filters thin liquidity moves around VWAP. Without it, the same visuals would produce materially more false triggers.
3. Branching entries with structure awareness
* Cross: Immediate VWAP cross in the trend direction.
* Cross-and-Retest: Requires a revisit to VWAP vicinity within a lookback window (recent low near VWAP for longs; recent high for shorts). This explicitly removes first-touch fakeouts that a plain cross takes.
* Momentum Exception (optional): A quantified body% + volume condition can bypass the retest when flow is impulsive—intentional risk-timing, not “just another indicator.”
4. Dual exits that reference both anchor and structure
* TrendBreak: Close only when price loses VWAP and EMA alignment flips.
* ATR stop: Placed at entry to cap tail risk.
These exits complement the entry structure rather than being generic stop/target add-ons.
What it does
* Trades the session’s fair value anchor (VWAP), but only with local-trend agreement (EMA fast vs. slow) and sufficient participation (volume filter).
* Lets you pick Cross or Cross-and-Retest entries; optionally allow a fast Momentum Exception when candles expand with volume.
* Manages positions with a structure exit (TrendBreak) and an emergency ATR stop from entry.
How it works (concepts & calculations)
* VWAP (session anchor):
Standard VWAP of the active session; entries reference the cross and the retest proximity to VWAP.
* Trend gate:
Long context only if `EMA(fast) > EMA(slow)`; short only if `EMA(fast) < EMA(slow)`.
A *gate*, not a trigger—entries aren’t considered unless this is true.
* Participation (volume) gate:
Require `volume > SMA(volume, volLen) × volMult`.
Screens out low-participation wiggles around VWAP.
Entries:
* Cross: Price crosses VWAP in the trend direction while volume gate is open.
* Cross-and-Retest: After crossing, price revisits VWAP vicinity within `lookback` (recent *low near VWAP* for longs; recent *high near VWAP* for shorts).
* Momentum Exception (optional): If body% (|close−open| / range) and volume exceed thresholds, enter without waiting for the retest.
Exits:
* TrendBreak (structure):
* Longs close when `price < VWAP` and `EMA(fast) < EMA(slow)` (mirror for shorts).
* ATR stop (risk):
* From entry: `stop = entry ± ATR(atrLen) × atrMult`.
How to use it ?
1. Select market & timeframe: Intraday on liquid symbols (equities, futures, crypto).
2. Pick entry mode:
* Start with Cross-and-Retest for fewer, more selective signals.
* Enable Momentum Exception if strong moves leave without retesting.
3. Tune guards:
* Raise `volMult` to ignore thin periods; lower it for more activity.
* Adjust `lookback` if retests come late/early on your symbol.
4. Risk:
* `atrLen` and `atrMult` set the emergency stop distance.
5. Read results per session: Optional panel (if enabled) summarizes Net-R, Win%, and PF for today’s session to evaluate
behavior regime by regime.
⚠️ 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.
EMA Zonen + Projektion (21, 50 + 200)standard 21ema, 50ema and 200ema,
ema Projection for next 3 Bars,
1% Box above to below all emas.
RSI OB/OSRSI OB/OS Signals indicator
The RSI OB/OS Signals indicator is an analysis and training tool that uses simple statistical learning (rolling correlations and z-scoring) to produce a smoothed, adaptive RSI weighting and signal line intended to highlight probable short-term RSI movements. The script does not attempt black-box machine-learning model export instead, it uses transparent building blocks — returns, RSI, ATR percentage, volume change (log), and raw volume — as predictors to estimate the likely next-bar RSI, then converts that estimate into a bounded “weight” and a smoothed signal line. The objective is educational: show how simple correlation-based weighting of standardized features can serve as an RSI augmentation and help traders identify higher-probability bullish or bearish RSI cross conditions, while making all internal reasoning visible and explainable.
At its core the indicator performs three conceptual steps each bar: first it computes a set of per-bar features aligned to the target (prior bar RSI) — specifically prior-bar log returns, prior-bar RSI, ATR as percent of price, the log change in volume and the prior-bar raw volume.
Second it standardizes these predictors through rolling z-scoring and computes rolling Pearson correlations between each standardized predictor and the target RSI over a user-configurable learning window. These correlations act as signed linear weights: predictors with higher absolute correlation are treated as more informative for that window.
Third it forms a linear prediction by summing correlation × z(feature) across the top correlated predictors, then maps that standardized prediction back to RSI scale using the rolling mean and standard deviation of the target. The mapped prediction is finally converted to a bounded “rsiWeight,” smoothed by a signal moving average, and used to produce bullish/bearish events on crossovers of preconfigured thresholds.
VWAP, buy/sell volume breakdown and simple tracking of the price move since the last signal are also displayed to help traders interpret the quality of signals.
The components are chosen for clear, complementary roles rather than as a random mashup. Prior-bar RSI embodies short-term momentum and is the natural prediction target.
Log returns add price-direction information; ATR percent encodes the intrabar volatility regime (helpful because RSI behaviour differs in high vs low volatility); the volume log-change and raw volume provide a participation signal indicating whether structural moves are supported by real activity. Standardizing predictors and using rolling correlations lets the script adapt its emphasis to the current regime: when volume changes correlate strongly with subsequent RSI moves, the algorithm will weight that predictor more heavily; when returns correlate more, weight shifts accordingly. Because the method is linear, transparent and computed on rolling windows you can reproduce and reason about the weight changes — a key requirement for educational clarity and TradingView compliance.
How to read and use the indicator practically: treat the smoothed rsiWeight line (ma_rsi) and its threshold crossings as an RSI-augmentation alert — not as a standalone automated buy/sell system. A practical workflow is: first inspect the dashboard and confirm the underlying drivers (which predictors show strong z-scores and which had high rolling correlation in the learning window); second check VWAP position and volume split to ensure that the price move is supported; third only consider signals that coincide with your higher-timeframe bias or structural support/resistance.
For example, a bullish crossover (ma_rsi crossing above −0.5) that occurs while VWAP is below price, buy volume share is elevated, and ATR is moderate is a higher-quality setup than the same crossing on thin volume and extreme ATR.
Use ATR or recent swing structure for stop placement and predefine risk per trade. Because the indicator tracks max points since the last signal, you can also use that metric as a simple intraday performance monitor.
Parameter tuning guidance: the learning window (learnLen) controls how quickly the correlation weights adapt; a short window (e.g., 10–20) makes the predictor weights responsive to regime shifts but also noisier; a longer window (e.g., 40–80) smooths weights and emphasizes longer-term relationships.
The rsiLen (target RSI length) should match your intended horizon — 14 is standard and balances responsiveness and smoothness. sigLen controls the smoothing of the predicted RSI weight: lower values make the signal line more reactive (useful for scalping), higher values produce smoother signals (useful for swing trades).
For low-liquidity instruments increase learnLen and sigLen to reduce false alarms; for high-speed intra-day work shorten them. Volume heuristics (volume thresholds) are instrument dependent — calibrate volume formatting and volumetric thresholds for equities versus futures or crypto.
Limitations and failure modes are explicit and important: the feature-selection approach is linear and based on Pearson correlation — it cannot capture nonlinear dependencies or temporal lags beyond the single lag studied, so it may miss relationships that require higher-order features.
The volume split used (close>open vs closeopen vs close
Комбинированный сигнал: MA10/MA40 + RSI50 + ЧайкинFriends, I share with you my indicator by strategy: crossing MA10/MA40 + RSI50 + Chaikin (above/below 0).
Indicator when the signal appears shows the entrance to the long/ short
The indicator works well on the trend. There may be false signals in the sidewall.
RSI MA Cross + Divergence Signal (fixed)🔹 Core Logic
RSI + Moving Average
The script calculates a standard RSI (default 14).
It then overlays a moving average (SMA/EMA/WMA, default 9).
When RSI crosses above its MA → bullish momentum.
When RSI crosses below its MA → bearish momentum.
Divergence Filter
Signals are only valid if there’s confirmed divergence:
Bullish divergence: Price makes a lower low, RSI makes a higher low.
Bearish divergence: Price makes a higher high, RSI makes a lower high.
Overbought / Oversold Filter
Optional extra:
Bullish signals only valid if RSI ≤ 30 (oversold).
Bearish signals only valid if RSI ≥ 70 (overbought).
This ensures signals happen in “stretched” conditions.
Risk & Trade Management
Entries taken only when all conditions align.
Exits can be managed with ATR stops, partial take-profits, breakeven moves, and trailing stops (we coded these in the strategy version).
Cooldown, session filters, and daily loss guard to keep risk tight.
🔹 Strengths
✅ High selectivity: Combining RSI cross + divergence + OB/OS means signals are rare but higher quality.
✅ Great at catching reversals: Divergence highlights where price may be running out of steam.
✅ Risk management baked in: ATR stops + partial exits smooth out equity curve.
✅ Works across markets: ES, FX, crypto — anywhere RSI divergences are respected.
✅ Flexible: You can loosen/tighten filters depending on aggressiveness.
🔹 Weaknesses
❌ Lag from pivots: Divergence only confirms after a few bars → you enter late sometimes.
❌ Choppy in ranges: In sideways markets, RSI divergences appear often and whipsaw.
❌ Filters reduce signals: With all filters ON (divergence + OB/OS + trend + session), signals can be very rare — may under-trade.
❌ Not standalone: Needs higher-timeframe context (trend, liquidity pools) to avoid counter-trend entries.
🔹 Best Ways to Trade It
Use Higher Timeframe Bias
Run the strategy on 15m/1H, but only trade in direction of higher timeframe trend (e.g., 4H EMA).
Example: If daily is bullish → only take bullish divergences.
Pair With Structure
Look for signals at key zones: HTF support/resistance, VWAP, or FVGs.
Divergence + RSI cross inside an FVG is a strong entry trigger.
Adjust OB/OS for Volatility
For crypto/FX: use 35/65 instead of 30/70 (markets trend harder).
For ES/S&P: 30/70 works fine.
Risk Management Is King
Use partial exits: take profit at 1R, trail rest.
Size by % of equity (we coded this into the strategy).
Avoid News Spikes
Divergences break down around CPI, NFP, Fed announcements — stay flat.
🔹 When It Shines
Trending markets that make extended pushes → clean divergences.
Reversal zones (oversold → bullish bounce, overbought → bearish fade).
Swing trading (15m–4H) — less noise than 1m/5m scalping.
🔹 When to Avoid
Low volatility chop → lots of false divergences.
During high-impact news → RSI swings wildly.
In strong one-way trends without pullbacks — divergence keeps calling tops/bottoms too early.
✅ Summary:
This is a reversal-focused RSI divergence strategy with strict filters. It’s powerful when combined with higher-timeframe bias + structure confluence, but weak if traded blindly in choppy or news-driven conditions. Best to treat it as a precision entry trigger, not a full system — layer it on top of your FVG/ORB framework for maximum edge.
CryptoThunder Storm v1.21CryptoThunder Storm v1.21 — Strategy (non-repainting, HTF-aware)
CryptoThunder Storm is a Pine v6 strategy that trades the cross of two moving-average variants computed on an alternate (higher) timeframe derived from your current chart. It’s built to be non-repainting by evaluating signals only at HTF bar boundaries and by avoiding lookahead. The script can trade LONG, SHORT, BOTH, or be disabled, and it includes a one-click invert Long/Short mode.
How it works
Two MA streams (Open/Close series).
You can choose from multiple MA types (SMA/EMA/DEMA/TEMA/WMA/VWMA/SMMA/Hull/LSMA/ALMA/SSMA/TMA). The script computes:
closeSeries – MA of the (possibly delayed) close
openSeries – MA of the (possibly delayed) open
Alternate Resolution (HTF).
The inputs allow you to multiply your current chart’s timeframe (e.g., on 5m with multiplier 3 → HTF = 15m). Both series are requested via request.security() with lookahead_off.
Non-repainting gating.
Signals are evaluated once per HTF bar (htfClosed gate). This ensures entries/alerts are aligned with HTF boundaries and prevents forward-shifting.
Entry logic.
Long when closeSeriesAlt crosses above openSeriesAlt.
Short when closeSeriesAlt crosses below openSeriesAlt.
Invert mode swaps these actions (a former long signal opens a short, and vice versa).
Orders are processed on bar close (process_orders_on_close=true).
Risk management (optional).
Optional initial TP/SL exits via strategy.exit() (ticks/points). Set 0 to disable.
Visuals.
The script colors bars (optional) and plots the two HTF series with a filled band, plus compact UP/DN/CL markers that match the executed side after inversion/filtering.
Inputs & configuration
Use Alternate Resolution?
Turns the HTF logic on/off. When off, the strategy uses the chart timeframe.
Multiplier for Alternate Resolution
Multiplies the current timeframe to form the HTF (e.g., 3×).
MA Type / Period / Offsets
MA Type — choose from 12 variants.
MA Period — core length.
Offset for LSMA / Sigma for ALMA — MA-specific tuning.
Offset for ALMA — center of mass for ALMA.
Delay Open/Close MA — shifts the source back by n bars for a more conservative (non-peek) calculation. Keep at 0 unless you know you want extra delay.
Show coloured Bars to indicate Trend?
Colors bars relative to HTF band.
What trades should be taken: LONG / SHORT / BOTH / NONE
Filters which sides are actually traded.
Invert Long/Short logic?
Swaps long ↔ short everywhere (orders, markers, JSON alerts).
Backtest window (Number of Bars for Back Testing)
Crude limiter to speed up testing. 0 = test full history.
TP/SL (Initial Stop Loss / Target Profit Points)
Values in ticks/points. 0 disables. They apply to both sides via strategy.exit().
Alert options
Turn on alerts (JSON)
Show alert marks (UP/DOWN/CLOSE)
Send CLOSE alerts (toggle)
The strategy fires alert() internally. Create an alert on “Any alert() function call”.
The payload is a simple JSON string:{ "text":"C98USDT.P UP"}
Messages:
UP — a long entry was executed (or, with Invert on: the inverted long signal that opens a long).
DOWN — a short entry executed.
CLOSE — position closed or flipped.
Tip: If you want to route long/short to different webhooks, parse the text field for UP, DOWN, or CLOSE
Plotting & markers
Band: Fills between the two HTF MA lines.
Bar color (optional): Quick visual trend cue.
Markers:
▲ “UP” below bar when a long executes.
▼ “DN” above bar when a short executes.
✖ “CL” on position close/flip.
These reflect the final executed side, after trade filters and after Invert mode
Best practices & notes
Non-repainting design.
request.security(..., lookahead_off) prevents future data leakage.
Signals are gated to HTF bar boundaries, so you won’t get intra-HTF recalculations.
Strategy orders are processed at bar close.
Choosing the multiplier.
A 2×–4× multiplier often balances responsiveness vs stability (e.g., 5m→15m or 20m). Larger multipliers reduce churn and false signals.
TP/SL units.
Values are in ticks/points of the chart symbol. On crypto, check your instrument’s tick size and adjust accordingly.
Trade filters apply after inversion.
With invertLS = true and tradeType = LONG, only final longs (post-inversion) are allowed.
Strategy vs chart counts.
The Tester reports closed trades; your chart shows entries/markers including the latest open trade. This can explain 8 vs 12 discrepancies over short windows.
Performance.
calc_on_every_tick=false and the backtest limiter keep the script responsive on long histories.
Tips: user on mid-volume crypto pair, 1M chart, best MA is: SMMA, Hull, SSMA, DEMA, TEMA.
This strategy is for research and education. Markets carry risk; past performance doesn’t guarantee future results. Always forward-test on paper and validate your exchange execution, tick size, and fees before deploying live.
Confluence Engine Confluence Engine is a practical, non-repainting decision aid that scores market conditions from −100…+100 by combining six proven modules: Trend, Momentum, Volatility, Volume, Structure, and an HTF confirmation. It’s designed for crypto, forex, indices, and stocks, and it fires entries only on confirmed bar closes.
What’s inside
Trend: EMA 20/50/200 alignment plus a Supertrend/KAMA toggle (you choose the baseline).
Momentum: RSI + MACD with confirmed-pivot divergence detection.
Volatility: ATR% and Bollinger Band width vs its average to favor expansion over chop.
Volume: OBV-style cumulative flow slope + volume surge vs SMA×multiplier.
Market Structure: Confirmed pivots, BOS (break of structure) and CHOCH (change of character).
HTF Filter: Closed higher-timeframe context via request.security(..., barmerge.gaps_on, barmerge.lookahead_off).
Why it does not repaint
Signals are computed and plotted on closed bars only.
Pivots/divergences use confirmed pivot points (no forward look).
HTF series are fetched with lookahead_off and use the last closed HTF bar in realtime.
No future bar references are used for entries or alerts.
How to use (3 steps)
Pick a timeframe pair: use a 4–6× HTF multiplier (5m→30m, 15m→1h, 1h→4h, 4h→1D, 1D→1W).
Trade with the HTF: take longs only when the HTF filter is bullish; shorts only when bearish.
Prefer expansion: act when BB width > its average and ATR% is elevated; skip most signals in compression.
Suggested presets (start here)
Crypto (BTC/ETH): 15m→1h, 1h→4h. stLen=10, stMult=3.0, bbLen=20, surgeMul=1.8–2.2, thresholds +40 / −40 (intraday can try +35 / −35).
Forex majors: 15m→1h, 1h→4h. stLen=10–14, stMult=2.5–3.0, surgeMul=1.5–1.8, thresholds +35 / −35 (swing: +45 / −45).
US equities (liquid): 5m→30m/1h, 15m→1h/2h. stMult=3.0–3.5, surgeMul=1.6–2.0, thresholds +45 / −45 to reduce chop.
Indices (ES/NQ): 5m→30m, 15m→1h. Defaults are fine; start at +40 / −40.
Gold/Oil: 15m→1h, 1h→4h. Thresholds +35 / −35, surgeMul=1.6–1.9.
Inputs (plain English)
Use Supertrend (off = KAMA): choose the trend baseline.
EMA Fast/Mid/Slow: 20/50/200 by default for classic stack.
RSI/MACD + divergence pivots: momentum and exhaustion context.
ATR Length & BB Length: volatility regime detection.
Volume SMA & Surge Multiplier: defines “meaningful” volume spikes.
Pivot left/right & “Confirm BOS/CHOCH on Close”: structure strictness.
Enable HTF & Higher Timeframe: confirms the lower timeframe direction.
Thresholds (+long / −short): when the score crosses these, you get signals.
Signals & alerts (IDs preserved)
Entry shapes plot at bar close when the score crosses thresholds.
Alerts you can enable:
CONFLUENCE LONG — long entry signal
CONFLUENCE SHORT — short entry signal
BULLISH BIAS — score turned positive
BEARISH BIAS — score turned negative
Best practices
Focus on signals with HTF agreement and volatility expansion; require volume participation (surge or rising OBV slope) for higher quality.
Raise thresholds (+45/−45 or +50/−50) to reduce whipsaws in choppy sessions.
Lower thresholds (+35/−35) only if you also require volatility/volume filters.
Performance & scope
Works across crypto/FX/equities/indices; no broker data or special feeds required.
No repainting by design; signals/alerts are computed on closed bars.
As with any tool, results vary by regime; always combine with risk management.
Disclosure
This script is for educational purposes only and is not financial advice. Trading involves risk. Test on historical data and paper trade before using live.
RSI Momentum Trend MM with Risk Per Trade [MTF]This is a comprehensive and highly customizable trend-following strategy based on RSI momentum. The core logic identifies strong directional moves when the RSI crosses user-defined thresholds, combined with an EMA trend confirmation. It is designed for traders who want granular control over their strategy's parameters, from signal generation to risk management and exit logic.
This script evolves a simple concept into a powerful backtesting tool, allowing you to test various money management and trade management theories across different timeframes.
Key Features
- RSI Momentum Signals: Uses RSI crosses above a "Positive" level or below a "Negative" level to generate trend signals. An EMA filter ensures entries align with the immediate trend.
- Multi-Timeframe (MTF) Analysis: The core RSI and EMA signals can be calculated on a higher timeframe (e.g., using 4H signals to trade on a 1H chart) to align trades with the larger trend. This feature helps to reduce noise and improve signal quality.
Advanced Money Management
- Risk per Trade %: Calculate position size based on a fixed percentage of equity you want to risk per trade.
- Full Equity: A more aggressive option to open each position with 100% of the available strategy equity.
Flexible Exit Logic: Choose from three distinct exit strategies to match your trading style
- Percentage (%) Based: Set a fixed Stop Loss and Take Profit as a percentage of the entry price.
- ATR Multiplier: Base your Stop Loss and Take Profit on the Average True Range (ATR), making your exits adaptive to market volatility.
- Trend Reversal: A true trend-following mode. A long position is held until an opposite "Negative" signal appears, and a short position is held until a "Positive" signal appears. This allows you to "let your winners run."
Backtest Date Range Filter: Easily configure a start and end date to backtest the strategy's performance during specific market periods (e.g., bull markets, bear markets, or high-volatility periods).
How to Use
RSI Settings
- Higher Timeframe: Set the timeframe for signal calculation. This must be higher than your chart's timeframe.
- RSI Length, Positive above, Negative below: Configure the core parameters for the RSI signals.
Money Management
Position Sizing Mode
- Choose "Risk per Trade" to use the Risk per Trade (%) input for precise risk control.
- Choose "Full Equity" to use 100% of your capital for each trade.
- Risk per Trade (%): Define the percentage of your equity to risk on a single trade (only works with the corresponding sizing mode).
SL/TP Calculation Mode
Select your preferred exit method from the dropdown. The strategy will automatically use the relevant inputs (e.g., % values, ATR Multiplier values, or the trend reversal logic).
Backtest Period Settings
Use the Start Date and End Date inputs to isolate a specific period for your backtest analysis.
License & Disclaimer
© waranyu.trkm — MIT License.
This script is for educational purposes only and should not be considered financial advice. Trading involves significant risk, and past performance is not indicative of future results. Always conduct your own research and risk assessment before making any trading decisions.
Turnover// ========================================
// TURNOVER INDICATOR (成交额指标)
// ========================================
//
// This indicator calculates and displays the turnover (trading value) for each bar,
// which represents the total monetary value of shares traded during that period.
// Turnover = Volume × Price
//
// KEY FEATURES:
// • Multiple price basis options: VWAP (recommended for intraday) or HLC3 average
// • Visual representation with colored columns (red/green for down/up bars)
// • Moving average overlay to smooth turnover trends
// • Rolling sum calculation for cumulative turnover over specified periods
// • Fully customizable parameters for different trading strategies
//
// USE CASES:
// • Identify periods of high/low market activity and liquidity
// • Analyze institutional money flow and market participation
// • Spot potential breakout or reversal points based on turnover spikes
// • Compare relative trading interest across different timeframes
// • Monitor market strength during trend formations
//
// PARAMETERS:
// • Price Basis: Choose between VWAP (intraday focus) or HLC3 (daily+ timeframes)
// • Visual Options: Toggle MA, rolling sum, and color coding
// • Timeframe Flexibility: Adjust MA and sum periods for your analysis needs
//
// ========================================
5 EMA Close/Open Cross StrategyLong Entry - 5 EMA Close crossing above 5 EMA open
exit - 5 EMA Close crossing below 5 EMA open
Short entry - 5 EMA Close crossing below 5 EMA open
exit - 5 EMA Close crossing above 5 EMA open
Gann Fan Strategy [KedarArc Quant]Description
A single-concept, rule-based strategy that trades around a programmatic Gann Fan.
It anchors to a swing (or a manual point), builds 1×1 and related fan lines numerically, and triggers entries when price interacts with the 1×1 (breakout or bounce). Management is done entirely with the fan structure (next/previous line) plus optional ATR trailing.
What TV indicators are used
* Pivots: `ta.pivothigh/ta.pivotlow` to confirm swing highs/lows for anchor selection.
* ATR: `ta.atr` only to scale the 1×1 slope (optional) and for an optional trailing stop.
* EMA: `ta.ema` as a trend filter (e.g., only long above the EMA, short below).
No RSI/MACD/Stoch/Heikin/etc. The logic is one coherent framework: Gann price–time geometry, with ATR as a scale and EMA as a risk filter.
How it works
1. Anchor
* Auto: chooses the most recent *confirmed* pivot (you control Left/Right).
* Manual: set a price and bar index and the fan will hold that point (no re-anchoring).
* Optional Re-anchor when a newer pivot confirms.
2. 1×1 Slope (numeric, not cosmetic)
* ATR mode: `1×1 = ATR(Length) × Multiplier` (adapts to volatility).
* Fixed mode: `ticks per bar` (constant slope).
Because slope is numeric, it doesn’t change with chart zoom, unlike the drawing tool.
3. Fan Lines
Builds classic ratios around the 1×1: 1/8, 1/4, 1/3, 1/2, 1/1, 2/1, 3/1, 4/1, 8/1.
4. Signals
* Breakout: cross of price over/under the 1×1 in the EMA-aligned direction.
* Bounce (optional): touch + reversal across the 1×1 to reduce whipsaw.
5. Exits & Risk
* Take-profit at the next fan line; Stop at the previous fan line.
* If a level is missing (right after re-anchor), a fallback Risk-Reward (RR) is used.
* Optional ATR trailing stop.
Why this is unique
* True numeric fan: The 1×1 slope is calculated from ATR or fixed ticks—not from screen geometry—so it is scale-invariant and reproducible across users/timeframes.
* Deterministic anchor logic: Uses confirmed pivots (with your L/R settings). No look-ahead; anchors update only when the right bars complete.
* Fan-native trade management: Both entries and exits come from the fan structure itself (with a minimal ATR/EMA assist), keeping the method pure.
* Two entry archetypes: Breakout for momentum days; Bounce for range days—switchable without changing the core model.
* Manual mode: Lock a session’s bias by anchoring to a chosen swing (e.g., day’s first major low/high) and keep the fan constant all day.
Inputs (quick guide)
* Auto Anchor (Left/Right): pivot sensitivity. Higher values = fewer, stronger anchors.
* Re-anchor: refresh to newer pivots as they confirm.
* Manual Anchor Price / Bar Index: fixes the fan (turn Auto off).
* Scale 1×1 by ATR: on = adaptive; off = use ticks per bar.
* ATR Length / ATR Multiplier: controls adaptive slope; start around 14 / 0.25–0.35.
* Ticks per bar: exact fixed slope (match a hand-drawn fan by computing slope ÷ mintick).
* EMA Trend Filter: e.g., 50–100; trades only in EMA direction.
* Use Bounce: require touch + reverse across 1×1 (helps in chop).
* TP/SL at fan lines; Fallback RR for missing levels; ATR Trailing Stop optional.
* Transparency/Plot EMA: visual preferences.
Tips
* Range days: larger pivots (L/R 8–12), Bounce ON, ATR Multiplier \~0.30–0.40, EMA 100.
* Trend days: L/R 5–6, Breakout, Multiplier \~0.20–0.30, EMA 50, ATR trail 1.0–1.5.
* Match the TV Gann Fan drawing: turn ATR scale OFF, set ticks per bar = `(Δprice between anchor and 1×1 target) / (bars) / mintick`.
Repainting & testing notes
* Pivots require Right bars to confirm; anchors are set after confirmation (no look-ahead).
* Signals use the current bar close with TradingView strategy mechanics; real-time vs. bar-close can differ slightly, as with any strategy.
* Re-anchoring legitimately moves the structure when new pivots confirm—by design.
⚠️ 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.
Stocks Multi-Indicator Alerts (cryptodaddy)//@version=6
// Multi-Indicator Alerts
// --------------------------------------------
// This script combines technical indicators and basic analyst data
// to produce composite buy and sell signals. Each block is heavily
// commented so future modifications are straightforward.
indicator("Multi-Indicator Alerts", overlay=true, max_labels_count=500)
//// === Daily momentum indicators ===
// Relative Strength Index measures price momentum.
rsiLength = input.int(14, "RSI Length")
rsi = ta.rsi(close, rsiLength)
// Money Flow Index incorporates volume to track capital movement.
// In Pine Script v6 the function only requires a price source and length;
// volume is taken from the built-in `volume` series automatically.
mfLength = input.int(14, "Money Flow Length")
mf = ta.mfi(hlc3, mfLength)
// `mfUp`/`mfDown` flag a turn in money flow over the last two bars.
mfUp = ta.rising(mf, 2)
mfDown = ta.falling(mf, 2)
//// === WaveTrend oscillator ===
// A simplified WaveTrend model produces "dots" indicating potential
// exhaustion points. Values beyond +/-53 are treated as oversold/overbought.
n1 = input.int(10, "WT Channel Length")
n2 = input.int(21, "WT Average Length")
ap = hlc3 // typical price
esa = ta.ema(ap, n1) // smoothed price
d = ta.ema(math.abs(ap - esa), n1) // smoothed deviation
ci = (ap - esa) / (0.015 * d) // channel index
tci = ta.ema(ci, n2) // trend channel index
wt1 = tci // main line
wt2 = ta.sma(wt1, 4) // signal line
greenDot = ta.crossover(wt1, wt2) and wt1 < -53
redDot = ta.crossunder(wt1, wt2) and wt1 > 53
plotshape(greenDot, title="Green Dot", style=shape.circle, color=color.green, location=location.belowbar, size=size.tiny)
plotshape(redDot, title="Red Dot", style=shape.circle, color=color.red, location=location.abovebar, size=size.tiny)
//// === Analyst fundamentals ===
// Fundamental values from TradingView's database. If a ticker lacks data
// these will return `na` and the related conditions simply evaluate false.
rating = request.financial(syminfo.tickerid, "rating", period="FY")
targetHigh = request.financial(syminfo.tickerid, "target_high_price", period="FY")
targetLow = request.financial(syminfo.tickerid, "target_low_price", period="FY")
upsidePct = (targetHigh - close) / close * 100
downsidePct = (close - targetLow) / close * 100
// `rating` comes back as a numeric value (1 strong sell -> 5 strong buy). Use
// thresholds instead of string comparisons so the script compiles even when
// the broker only supplies numeric ratings.
ratingBuy = rating >= 4 // buy or strong buy
ratingNeutralOrBuy = rating >= 3 // neutral or better
upsideCondition = upsidePct >= 2 * downsidePct // upside at least twice downside
downsideCondition = downsidePct >= upsidePct // downside greater or equal
//// === Daily moving-average context ===
// 50 EMA represents short-term trend; 200 EMA long-term bias.
ema50 = ta.ema(close, 50)
ema200 = ta.ema(close, 200)
longBias = close > ema200 // price above 200-day = long bias
momentumFavorable = close > ema50 // price above 50-day = positive momentum
//// === Weekly trend filter ===
// Higher timeframe confirmation to reduce noise.
weeklyClose = request.security(syminfo.tickerid, "W", close)
weeklyEMA20 = request.security(syminfo.tickerid, "W", ta.ema(close, 20))
weeklyRSI = request.security(syminfo.tickerid, "W", ta.rsi(close, rsiLength))
// Weekly Money Flow uses the same two-argument `ta.mfi()` inside `request.security`.
weeklyMF = request.security(syminfo.tickerid, "W", ta.mfi(hlc3, mfLength))
weeklyFilter = weeklyClose > weeklyEMA20
//// === Buy evaluation ===
// Each true condition contributes one point to `buyScore`.
c1_buy = rsi < 50 // RSI below midpoint
c2_buy = mfUp // Money Flow turning up
c3_buy = greenDot // WaveTrend oversold bounce
c4_buy = ratingBuy // Analyst rating Buy/Strong Buy
c5_buy = upsideCondition // Forecast upside twice downside
buyScore = (c1_buy?1:0) + (c2_buy?1:0) + (c3_buy?1:0) + (c4_buy?1:0) + (c5_buy?1:0)
// Require all five conditions plus trend filters and persistence for two bars.
buyCond = c1_buy and c2_buy and c3_buy and c4_buy and c5_buy and longBias and momentumFavorable and weeklyFilter and weeklyRSI > 50 and weeklyMF > 50
buySignal = buyCond and buyCond
//// === Sell evaluation ===
// Similar logic as buy side but inverted.
c1_sell = rsi > 70 // RSI above overbought threshold
c2_sell = mfDown // Money Flow turning down
c3_sell = redDot // WaveTrend overbought reversal
c4_sell = ratingNeutralOrBuy // Analysts neutral or still buy
c5_sell = downsideCondition // Downside at least equal to upside
sellScore = (c1_sell?1:0) + (c2_sell?1:0) + (c3_sell?1:0) + (c4_sell?1:0) + (c5_sell?1:0)
// For exits require weekly filters to fail or long bias lost.
sellCond = c1_sell and c2_sell and c3_sell and c4_sell and c5_sell and (not longBias or not weeklyFilter or weeklyRSI < 50)
sellSignal = sellCond and sellCond
// Plot composite scores for quick reference.
plot(buyScore, "Buy Score", color=color.green)
plot(sellScore, "Sell Score", color=color.red)
//// === Confidence table ===
// Shows which of the five buy/sell checks are currently met.
var table status = table.new(position.top_right, 5, 2, border_width=1)
if barstate.islast
table.cell(status, 0, 0, "RSI", bgcolor=c1_buy?color.new(color.green,0):color.new(color.red,0))
table.cell(status, 1, 0, "MF", bgcolor=c2_buy?color.new(color.green,0):color.new(color.red,0))
table.cell(status, 2, 0, "Dot", bgcolor=c3_buy?color.new(color.green,0):color.new(color.red,0))
table.cell(status, 3, 0, "Rating", bgcolor=c4_buy?color.new(color.green,0):color.new(color.red,0))
table.cell(status, 4, 0, "Target", bgcolor=c5_buy?color.new(color.green,0):color.new(color.red,0))
table.cell(status, 0, 1, "RSI>70", bgcolor=c1_sell?color.new(color.red,0):color.new(color.green,0))
table.cell(status, 1, 1, "MF down",bgcolor=c2_sell?color.new(color.red,0):color.new(color.green,0))
table.cell(status, 2, 1, "Red dot", bgcolor=c3_sell?color.new(color.red,0):color.new(color.green,0))
table.cell(status, 3, 1, "Rating", bgcolor=c4_sell?color.new(color.red,0):color.new(color.green,0))
table.cell(status, 4, 1, "Target", bgcolor=c5_sell?color.new(color.red,0):color.new(color.green,0))
//// === Alert text ===
// Include key metrics in alerts so the chart doesn't need to be opened.
buyMsg = "BUY: RSI " + str.tostring(rsi, "#.##") +
", MF " + str.tostring(mf, "#.##") +
", Upside " + str.tostring(upsidePct, "#.##") + "%" +
", Downside " + str.tostring(downsidePct, "#.##") + "%" +
", Rating " + str.tostring(rating, "#.##")
sellMsg = "SELL: RSI " + str.tostring(rsi, "#.##") +
", MF " + str.tostring(mf, "#.##") +
", Upside " + str.tostring(upsidePct, "#.##") + "%" +
", Downside " + str.tostring(downsidePct, "#.##") + "%" +
", Rating " + str.tostring(rating, "#.##")
// Alert conditions use static messages; dynamic data is sent via `alert()`
alertcondition(buySignal, title="Buy Signal", message="Buy conditions met")
alertcondition(sellSignal, title="Sell Signal", message="Sell conditions met")
if buySignal
alert(buyMsg, alert.freq_once_per_bar_close)
if sellSignal
alert(sellMsg, alert.freq_once_per_bar_close)
//// === Watch-out flags ===
// Gentle warnings when trends weaken but before full sell signals.
warnRSI = rsi > 65 and rsi <= 65
warnAnalyst = upsidePct < 2 * downsidePct and upsidePct > downsidePct
alertcondition(warnRSI, title="RSI Watch", message="RSI creeping above 65")
alertcondition(warnAnalyst, title="Analyst Watch", message="Analyst upside shrinking")
if warnRSI
alert("RSI creeping above 65: " + str.tostring(rsi, "#.##"), alert.freq_once_per_bar_close)
if warnAnalyst
alert("Analyst upside shrinking: up " + str.tostring(upsidePct, "#.##") + "% vs down " + str.tostring(downsidePct, "#.##") + "%", alert.freq_once_per_bar_close)
//// === Plot bias moving averages ===
plot(ema50, color=color.orange, title="EMA50")
plot(ema200, color=color.blue, title="EMA200")
//// === Cross alerts for context ===
goldenCross = ta.crossover(ema50, ema200)
deathCross = ta.crossunder(ema50, ema200)
alertcondition(goldenCross, title="Golden Cross", message="50 EMA crossed above 200 EMA")
alertcondition(deathCross, title="Death Cross", message="50 EMA crossed below 200 EMA")
20 MA ReversionA mean reversion tactic with the 20 SMA:
the indicator is chcking specific parameters, such as the volume related to the last day's volume, distance from 20 SMA, CCI values and changes, trends, and recent gaps that will act as a magnet.
enjoy!
RTC EMA/SMA Combo IndicatorRTC Combo indicator with 20 EMA, 50 EMA and 200 SMA
Primarily used for Market Structure purpose
[davidev] EMA/MA with projection# EMA/MA with projection
## What it is
A lightweight overlay that plots up to three EMAs and one MA (default: 5/21/55 EMAs and 200 MA) and draws a forward projection from the current bar. The projection extrapolates the latest per-bar change (slope) to visualize where each average *could* be in the next N bars—useful for planning entries, dynamic support/resistance, and anticipating crossovers.
Note: The projection is a simple linear extrapolation of the most recent change. It is not a prediction or signal.
## How it works
Computes EMA1, EMA2, EMA3 and MA (SMA) on your chosen sources.
On the last bar only, it draws a short line segment ahead by `Bars Ahead`, using the most recent change (`ta.change()`) × number of bars to project the line.
Lines are **reused** and updated each tick (no clutter), and deleted on historical bars to avoid artifacts.
## Good for
Visualizing **dynamic levels** slightly ahead of price.
Quickly gauging **momentum** and **slope** of your moving averages.
Sketching possible **crossover timing** (e.g., 5 vs 21 EMA) without changing timeframe.
Cleaner charting: projection only renders on the last bar, so historical candles stay uncluttered.
## Tips
Combine with your market structure/volume tools; the projection helps **plan**, not predict.
Shorter EMAs react faster and will show more pronounced projected moves; longer MAs remain steadier.
Increase `Bars Ahead` on higher timeframes; keep it small on scalping charts to avoid overreach.
