MoneyMakerz 💰MoneyMakerz 💰 — Simple SOP for Traders
📊 Understand Visuals
| Element Meaning
=================================================================
| 🟢 Green Trendline: EMA 5 & 8 are above the trendline → Bullish signal
| 🔴 Red Trendline: EMA 5 & 8 are below the trendline → Bearish signal
| 🔷 Blue Diamond: Bullish shift detected (trendline turns green)
| 🔶 Maroon Diamond: Bearish shift detected (trendline turns red)
| 🚀 Bull Div: RSI bullish divergence → Potential reversal up
| 💣 Bear Div: RSI bearish divergence → Potential reversal down
📐 Pivot Points (Standard Usage)
Enable ** Pivot Points Standard ** from TradingView’s built-in indicators.
| Level Meaning
====================================
| PP Central pivot — market bias
| R1–R3 Resistance zones
| S1–S3 Support zones
** Usage Tips: **
- Price above PP → bullish bias
- Price below PP → bearish bias
- Watch for potential reversals near support/resistance zones (S/R)
✅ Trading Workflow
- 🟢 Trendline turns green → Consider long
- 🔴 Trendline turns red → Consider short
- 🔷/🔶 Diamond appears → Signal confirmation
- Use RSI zones to gauge strength behind price moves and confirm trendline signals
- Confirm with Pivot Zones
- Watch for 🚀 Bull Div or 💣 Bear Div near S/R
- Exit when trendline flips or RSI exits zone
🧠 Trendline & Diamond Logic
- The ** Trendline ** is a dynamic EMA (default length: 20)
- When both EMA 5 and EMA 8 cross ** above ** the trendline → it turns 🟢 green
- When both EMA 5 and EMA 8 cross ** below ** the trendline → it turns 🔴 red
- Each time the trendline color changes, a ** diamond marker ** appears:
- 🔷 Blue Diamond = Bullish shift (green trendline starts)
- 🔶 Maroon Diamond = Bearish shift (red trendline starts)
These diamonds help you visually catch momentum shifts early — especially when paired with RSI and pivot zones.
Oscillators
gold scaling_V2.2 (Zone-Driven Entries + BB Entries) — Dual-Set
Short Description (for the “Description” box)
gold scaling_V2.2 (Zone-Driven Entries + BB Entries) — Dual-Set
Two coordinated entry engines. Set A (Zone-Driven): dynamic buy/sell zones with anti-chase (first-touch, flip-guard, hysteresis), TP1–TP5 ladder, and smart SL (BE/Follow/Chandelier). Set B (BB mini): fast Bollinger-based entries with HTF/BBW filters. Compact HUD, Heads-Up ETA, and full Text/JSON alerts (ENTRY/TP/SL). Built for disciplined entries, not FOMO.
Full Description
Overview
This indicator enforces disciplined entries by combining two complementary systems:
Set A — Zone-Driven Entries: builds adaptive buy/sell zones (ATR-aware), confirms entries in two steps (touch → confirm), and manages exits with a TP ladder and intelligent SL logic (move to Break-Even at TP1, follow by TP levels, or optional Chandelier trail). Includes zone lock/re-arm after real breakouts.
Set B — BB Entries (mini): lightweight Bollinger-based “mini” entries (Revert Cross or Cross Threshold) that respect HTF EMA slope and BB Width filters.
Timeframes:
Set A (Zone) works best on M15–H1; Set B (mini) is great for M5–M30 to catch tactical moves inside the bigger structure.
Quick Start
Add to chart → Entry Sets: enable Set A (Zone) and/or Set B (BB mini).
Alerts: turn on Enable Auto Alerts and create one alert with Any alert() function call → Once per bar close.
Webhook/automation: toggle Use JSON to emit machine-readable alerts.
Filters: enable HTF Trend Filter and/or BB Width filter to improve signal quality.
Stops: choose SL mode (ATR ×, Percent, Points). Configure SL→BE on TP1, Follow by TP, or Chandelier Trail.
Signal Architecture
Set A — Zone-Driven (primary entries)
Trigger: price touches/crosses zone edge → pending → confirm with hysteresis and minimum real body (ATR-scaled) aligned with side.
Anti-Chase: firstTouchOnly, max entries per zone, flipGuardBars, optional body-displacement (ATR×), and global lock after any entry.
Breakout Handling: lock zones after a meaningful break (close beyond edge ≥ ATR×). Re-arm by Retest / Time / Retest OR Time.
TP Ladder: TP1–TP5 lines with labels and fills.
Smart SL: move to BE at TP1, follow TP levels (rate-limited and ATR-buffered), or Chandelier.
Set B — BB Entries (mini)
Modes: Revert Cross (default) or Cross Threshold.
Honors HTF EMA slope and BB Width if enabled.
Separate per-side cooldown to reduce spam.
Heads-Up & HUD
Heads-Up ETA: estimates minutes to nearest band/basis or compression-to-expansion spike.
HUD: shows symbol/TF/side, Entry/SL, TP1–TP5 RR snapshot, W/L from Zone set, and HU/Vol lines.
Alerts
Auto alerts (recommended, via alert())
Create one alert: Any alert() function call → Once per bar close. It covers everything.
ENTRY (Zone):
Key Settings (what matters most)
Strategy Settings: tradeDirection (gate signals by side), entryStrategy for BB.
Entry Sets: toggle Set A (Zone) and Set B (BB mini) independently.
Bollinger Bands Settings: bbLength, bbMult; if BB Width filter is on, define min/max width (% of price).
Alert Settings: Enable Auto Alerts, Use JSON, cooldownSeconds, maxOneTPPerBar.
Anti-Chase / Zone State: firstTouchOnly, maxEntriesPerZonePerSide, flipGuardBars, requireRetest, hysteresisAtrMult, confirmBodyAtrMult, globalLockBars, lockZonesOnBreakout, rearmMode.
Stop Loss: SL mode + SL→BE on TP1, Follow by TP (slMoveFraction, confirm/hold bars, ATR buffer), Chandelier.
TP Zones: mult_dist for step size, zoneExpireBars for auto-cleanup.
HUD/Labels: mini label colors, HUD theme/size.
Tuning Guide
Too few entries: reduce flipGuardBars, confirmBodyAtrMult, or hysteresisAtrMult; relax BB width bounds; increase maxEntriesPerZonePerSide.
Noisy/fake entries: raise flipGuardBars, enable requireFlipDisplacement (increase flipDispATRmult), tighten BB width bounds, enable alertsFollowTradeDirection.
SL moves too fast/slow: adjust slMinBarsBetweenMoves, slFollowConfirmBars, slMoveFraction, and slFollowAtrBufferMult.
Prefer retests after breaks: lockZonesOnBreakout = true + rearmMode = "Retest only".
Repaint & Transparency
Entries fire on bar close when alertsOnClose=true (default), with multi-layer confirmation to reduce hindsight changes.
Heads-Up/Spike are predictive helpers, not entry rules; they may update as new data comes in.
Visual overlays (divergence/oscillators) are supportive, not mandatory to the entry logic.
Volatility Cone Forecaster Lite [PhenLabs]📊 Volatility Cone Forecaster
Version: PineScript™v6
📌Description
The Volatility Cone Forecaster (VCF) is an advanced indicator designed to provide traders with a forward-looking perspective on market volatility. Instead of merely measuring past price fluctuations, the VCF analyzes historical volatility data to project a statistical “cone” that outlines a probable range for future price movements. Its core purpose is to contextualize the current market environment, helping traders to anticipate potential shifts from low to high volatility periods (and vice versa). By identifying whether volatility is expanding or contracting relative to historical norms, it solves the critical problem of preparing for significant market moves before they happen, offering a clear statistical edge in strategy development.
This indicator moves beyond lagging measures by employing percentile analysis to rank the current volatility state. This allows traders to understand not just what volatility is, but how significant it is compared to the recent past. The VCF is built for discretionary traders, system developers, and options strategists who need a sophisticated understanding of market dynamics to manage risk and identify high-probability opportunities.
🚀Points of Innovation
Forward-Looking Volatility Projection: Unlike standard indicators that only show historical data, the VCF projects a statistical cone of future volatility.
Percentile-Based Regime Analysis: Ranks current volatility against historical data (e.g., 90th, 75th percentiles) to provide objective context.
Automated Regime Detection: Automatically identifies and labels the market as being in a ‘High’, ‘Low’, or ‘Normal’ volatility regime.
Expansion & Contraction Signals: Clearly indicates whether volatility is currently increasing or decreasing, signaling shifts in market energy.
Integrated ATR Comparison: Plots an ATR-equivalent volatility measure to offer a familiar point of reference against the statistical model.
Dynamic Visual Modeling: The cone visualization directly on the price chart provides an intuitive guide for future expected price ranges.
🔧Core Components
Realized Volatility Engine: Calculates historical volatility using log returns over multiple user-defined lookback periods (short, medium, long) for a comprehensive view.
Percentile Analysis Module: A custom function calculates the 10th, 25th, 50th, 75th, and 90th percentiles of volatility over a long-term lookback (e.g., 252 days).
Forward Projection Calculator: Uses the calculated volatility percentiles to mathematically derive and draw the upper and lower bounds of the future volatility cone.
Volatility Regime Classifier: A logic-based system that compares current volatility to the historical percentile bands to classify the market state.
🔥Key Features
Customizable Lookback Periods: Adjust short, medium, and long-term lookbacks to fine-tune the indicator’s sensitivity to different market cycles.
Configurable Forward Projection: Set the number of days for the forward cone projection to align with your specific trading horizon.
Interactive Display Options: Toggle visibility for percentile labels, ATR levels, and regime coloring to customize the chart display.
Data-Rich Information Table: A clean, on-screen table displays all key metrics, including current volatility, percentile rank, regime, and trend.
Built-in Alert Conditions: Set alerts for critical events like volatility crossing the 90th percentile, dropping below the 10th, or switching between expansion and contraction.
🎨Visualization
Volatility Cone: Shaded bands projected onto the future price axis, representing the probable price range at different statistical confidence levels (e.g., 75th-90th percentile).
Color-Coded Volatility Line: The primary volatility plot dynamically changes color (e.g., red for high, green for low) to reflect the current volatility regime, providing instant context.
Historical Percentile Bands: Horizontal lines plotted across the indicator pane mark the key percentile levels, showing how current volatility compares to the past.
On-Chart Labels: Clear labels automatically display the current volatility reading, its percentile rank, the detected regime, and trend (Expanding/Contracting).
📖Usage Guidelines
Setting Categories
Short-term Lookback: Default: 10, Range: 5-50. Controls the most sensitive volatility calculation.
Medium-term Lookback: Default: 21, Range: 10-100. The primary input for the current volatility reading.
Long-term Lookback: Default: 63, Range: 30-252. Provides a baseline for long-term market character.
Percentile Lookback Period: Default: 252, Range: 100-1000. Defines the period for historical ranking; 252 represents one trading year.
Forward Projection Days: Default: 21, Range: 5-63. Determines how many bars into the future the cone is projected.
✅Best Use Cases
Breakout Trading: Identify periods of deep consolidation when volatility falls to low percentile ranks (e.g., below 25th) and begins to expand, signaling a potential breakout.
Mean Reversion Strategies: Target trades when volatility reaches extreme high percentile ranks (e.g., above 90th), as these periods are often unsustainable and lead to contraction.
Options Strategy: Use the cone’s projected upper and lower bounds to help select strike prices for strategies like iron condors or straddles.
Risk Management: Widen stop-losses and reduce position sizes when the indicator signals a transition into a ‘High’ volatility regime.
⚠️Limitations
Probabilistic, Not Predictive: The cone represents a statistical probability, not a guarantee of future price action. Extreme, unpredictable news events can drive prices outside the cone.
Lagging by Nature: All calculations are based on historical price data, meaning the indicator will always react to, not pre-empt, market changes.
Non-Directional: The indicator forecasts the *magnitude* of future moves, not the *direction*. It should be paired with a directional analysis tool.
💡What Makes This Unique
Forward Projection: Its primary distinction is projecting a data-driven, statistical forecast of future volatility, which standard oscillators do not do.
Contextual Analysis: It doesn’t just provide a number; it tells you what that number means through percentile ranking and automated regime classification.
🔬How It Works
1. Data Calculation:
The indicator first calculates the logarithmic returns of the asset’s price. It then computes the annualized standard deviation of these returns over short, medium, and long-term lookback periods to generate realized volatility readings.
2. Percentile Ranking:
Using a 252-day lookback, it analyzes the history of the medium-term volatility and determines the values that correspond to the 10th, 25th, 50th, 75th, and 90th percentiles. This builds a statistical map of the asset’s volatility behavior.
3. Cone Projection:
Finally, it takes these historical percentile values and projects them forward in time, calculating the potential upper and lower price bounds based on what would happen if volatility were to run at those levels over the next 21 days.
💡Note:
The Volatility Cone Forecaster is most effective on daily and weekly charts where statistical volatility models are more reliable. For lower timeframes, consider shortening the lookback periods. Always use this indicator as part of a comprehensive trading plan that includes other forms of analysis.
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.
MTF Stochastic Dashboard What you see:
Top-right table: TF | %K | %D | Signal.
Signal = Bullish (green) if K > D, Bearish (red) if K < D.
Row color: red if K & D ≥ 80, green if K & D ≤ 20.
Number color: ≤30 green, ≥70 red.
Settings
Signal mode:
Always (just K>D or K
Kerzen-Zähler über/unter EMADieses Skript zeigt die Anzahl an Zeitperioden ober/unterhalb eines individuellen EMAs an.
FX Strike — RSI Momentum PanelDescription:
The FX Strike RSI Panel provides a momentum filter for the FX Strike system, using the classic RSI with enhanced visuals.
RSI (14): Standard calculation with clear signals.
50 Midline: Momentum bias filter (above = bullish, below = bearish).
30/70 Zones: Overbought and oversold regions for context.
Colored RSI Line: Teal when bullish, orange when bearish.
Alert Conditions: Triggers when RSI crosses above or below the 50 mid-line.
How to Use:
In trend trading, only take longs if RSI is above 50 and shorts if RSI is below 50.
Use divergences (price vs RSI) to spot early signs of weakening momentum.
Combine with the FX Strike Overlay for a complete 4-pillar strategy (Trend, Volatility, Momentum, Volume).
DNSE VN301!, ADX Momentum StrategyDiscover the tailored Pine Script for trading VN30F1M Futures Contracts intraday.
This strategy applies the Statistical Method (IQR) to break down the components of the ADX, calculating the threshold of "normal" momentum fluctuations in price to identify potential breakouts for entry and exit signals. The script automatically closes all positions by 14:30 to avoid overnight holdings.
www.tradingview.com
Settings & Backtest Results:
- Chart: 30-minute timeframe
- Initial capital: VND 100 million
- Position size: 4 contracts per trade (includes trading fees, excludes tax)
- Backtest period: Sep-2021 to Sep-2025
- Return: over 270% (with 5 ticks slippage)
- Trades executed: 1,000+
- Win rate: ~40%
- Profit factor: 1.2
Default Script Settings:
Calculates the acceleration of changes in the +DI and -DI components of the ADX, using IQR to define "normal" momentum fluctuations (adjustable via Lookback period).
Calculates the difference between each bar’s Open and Close prices, using IQR to define "normal" gaps (adjustable via Lookback period).
Entry & Exit Conditions:
Entry Long: Change in +DI or -DI > Avg IQR Value AND Close Price > Previous Close
Exit Long: (all 4 conditions must be met)
- Change in +DI or -DI > Avg IQR Value
- RSI < Previous RSI
- Close–Open Gap > Avg IQR Gap
- Close Price < Previous Close
Entry Short: Change in +DI or -DI > Avg IQR Value AND Close Price < Previous Close
Exit Short: (all 4 conditions must be met)
- Change in +DI or -DI > Avg IQR Value
- RSI > Previous RSI
- Close–Open Gap > Avg IQR Gap
- Close Price > Previous Close
Disclaimers:
Trading futures contracts carries a high degree of risk, and price movements can be highly volatile. This script is intended as a reference tool only. It should be used by individuals who fully understand futures trading, have assessed their own risk tolerance, and are knowledgeable about the strategy’s logic.
All investment decisions are the sole responsibility of the user. DNSE bears no liability for any potential losses incurred from applying this strategy in real trading. Past performance does not guarantee future results. Please contact us directly if you have specific questions about this script.
Combined Continuational Signal - RSI & KeltnerContinuational Signal Indicator
This technical indicator provides trend continuation signals through dual-methodology analysis, offering traders flexibility to choose between RSI-based or Keltner Channel-based signal generation, or utilize both simultaneously for enhanced confirmation.
Core Functionality:
Dual Signal Architecture: Toggle between RSI momentum analysis or Keltner Channel volatility breakout detection
Multi-Confirmation Framework: Incorporates moving average trend filters, slope analysis, and candle pattern validation
Cloud Interaction Filter: Signals activate only when price interacts with the moving average cloud zone
MA Closeness Filter: Uses ATR-based filtering to avoid signals during low-volatility consolidation periods
Signal Logic:
The indicator waits for overbought/oversold conditions (RSI) or band extremes (Keltner), confirms directional bias through slope analysis, validates trend alignment via moving average positioning, then triggers signals on specific candle formations with engulfing characteristics.
Customization Options:
Adjustable RSI parameters and threshold levels
Configurable Keltner Channel settings with multiple calculation methods
Multiple moving average lengths for trend and slope analysis
Various display modes (shapes, backgrounds, candle coloring, vertical lines)
Comprehensive alert system for all signal types
Risk Management Integration:
Built-in filters prevent signals during choppy market conditions and ensure alignment with higher-timeframe trend direction before activation.
Use in conjunction with other confluent variables for optimal results. The default settings are calibrated for specific market conditions, though experimentation with parameters is recommended for different trading styles and timeframes.
Liquidation Strategy💣 Liquidation Strategy (High-Level Overview + Usage)
This strategy is built to trade extreme liquidation events on crypto exchanges like Bybit or OKX, using TradingView’s Liquidations indicator as input.
🔧 Core Logic
Long entries: Triggered when long liquidation values spike above a set threshold.
Short entries: Triggered when short liquidation values drop below a negative threshold.
Optional EMA filter ensures liquidation values are significantly above/below their moving average.
RSI crossover logic is used to exit trades.
🛠️ Usage Instructions
Add the Liquidations Indicator: Go to TradingView → Indicators → Search for “Liquidations” under the Financials section.
Select the Correct Chart: Use a chart from Bybit or OKX, as these exchanges provide liquidation data.
Link the Data Sources: In the strategy settings, set: Long Liquidation Data to the long liquidation series from the indicator. Short Liquidation Data to the short liquidation series.
Overlay the Strategy: You can overlay this strategy directly on the Liquidations indicator for better visual alignment.
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.
W Bottom Reversal Strategy W Bottom Reversal Strategy (15m-close entries; intrabar TP; daily MACD exit; JSON alerts v49.3-expire2)
Overview
A precision reversal strategy designed for 15-minute charts on liquid symbols. It detects a capitulation-and-stabilization “W” base using 1-hour (1H) context, confirms momentum improvement, then enters only on bar close to avoid early/“ghost” signals. Exits combine a fast intrabar take-profit (~2.7%) with a daily MACD risk-off exit that closes positions when higher-timeframe momentum turns against the setup.
How it works (high-level, matching code)
1H volatility + oversold gate (arming)
Compute 1H Bollinger-style bands (basis = SMA(close, bbLength=20), stdev multiplier bbMult=2.0).
Arm the setup when a 1H bar closes with price < 1H lower band and 1H RSI( rsiLength=14 ) < rsiThreshold (default 20.0).
1H momentum flip → pending entry
When a new 1H bar closes and 1H MACD line (EMA12−EMA26) crosses above 0 while armed and flat, set an entryPending flag.
This does not enter yet—it prepares a confirmed, bar-close entry on the lower timeframe.
Bar-close execution on the chart timeframe (15m)
On the next 15m bar close (or within N bars, see below) and still flat, fire the entry using a limit order at close × (1 − 0.00001) (≈ 0.001% below close) to reduce slippage and maintain chart/alert alignment.
Anti-late filter (no stale triggers)
If the pending entry doesn’t trigger within N chart bars (input: “Pending entry valid for N chart bars”, default 1, range 1–8), it expires and the arm state resets. This prevents late fills long after the 1H confirmation.
Exit logic
Primary: Standing intrabar take-profit at +2.7% from the average entry price (managed via strategy.exit limit).
Risk-off: On daily bar close, if Daily MACD line (EMA12−EMA26) crosses under 0, close the position (flat on daily momentum flip).
Default Properties (used for this publication)
Timeframe: 15m (with 1H and Daily higher-timeframe confirmations via request.security)
Initial capital: $10,000
Position sizing: Percent of equity = 10% per trade (enters only when flat; no stacking while in a position)
Commission: 0.05% per side
Slippage: Recommend 1 tick in Strategy Properties for realistic fills
Inputs exposed:
BB Length: 20 • BB Multiplier: 2.0
RSI Length: 14 • RSI Threshold: 20.0
MACD: Short 12, Long 26, Signal 9 (signal kept for compatibility; logic uses MACD line vs 0)
Pending entry valid for N chart bars: default 1 (1–8)
Execution behavior (per code):
calc_on_every_tick = false (evaluates on bar close)
process_orders_on_close = true (orders placed at bar close)
Limit entry at close −0.001%
Intrabar TP (2.7%)
Daily risk-off exit on MACD<0 at daily bar close
Alerts (exact behavior in code)
Uses alert() function calls with standardized JSON.
Set your alert to “Only alert() function calls” and “Once per bar close.”
Two events are emitted:
LONG_CONFIRMED on entry fire (15m bar close)
EXIT_CONFIRMED_DAILY_MACD on daily MACD<0 (daily bar close)
JSON fields include: event, version ("v49.3-expire2"), symbol, interval, price, and time.
How to use
Apply on liquid tickers (tight spreads, healthy volume).
Keep defaults initially; run across a broad, liquid watchlist to gather a proper sample.
For automation, route bar-close alerts to your executor; confirm broker lot/route settings and that limit orders at close −0.001% are acceptable.
Expect fewer signals in powerful trends; the daily risk-off helps cut failed bases.
Methodology & expectations (results transparency)
Evaluate on a dataset yielding 100+ trades before drawing conclusions.
Keep commission & slippage enabled (see defaults).
Risk sizing: With 10% of equity per trade and flat-to-flat entries, exposure aligns with typical 5–10% guidance.
No performance guarantees—outcomes depend on symbol selection, volatility regime, news, and execution quality.
Originality & value (vendor justification)
While it uses familiar building blocks (BB/RSI/MACD), the edge comes from the 1H volatility + oversold arming, 1H momentum flip, strict 15m bar-close limit execution, and the N-bar pending expiry that prevents stale triggers—paired with a dual-exit design (intrabar TP + daily risk-off). The focus is on reducing premature fills, keeping alerts 1:1 with chart marks, and capturing the first impulse out of a W-base.
Disclaimers
For educational purposes only; not financial advice. Paper-test first. Verify alerts, fills, and symbol liquidity with your broker before live use.
Changelog: v49.3-expire2 — Bar-close limit entries; anti-late pending window; standardized JSON alerts; intrabar 2.7% TP; daily MACD risk-off exit.
Chanpreet RSI(3) Extreme Rays (4H, Adjustable Style)Chanpreet RSI(3) Extreme Rays (4H)
This indicator applies a short-length RSI (3) on the 4-hour timeframe and highlights momentum extremes directly on the chart.
🔎 What it does
Detects when RSI(3) moves into overbought (>80) or oversold (<20) territory.
Groups consecutive candles inside these zones into one “event” instead of marking each bar individually.
For each event:
• In overbought → records the highest high of the stretch and marks it with a horizontal ray.
• In oversold → records the lowest low of the stretch and marks it with a horizontal ray.
Keeps only the most recent N rays (default 5, adjustable).
⚙️ Inputs
Max Rays to Keep → how many unique events are kept visible.
Ray Thickness → adjust line thickness.
Overbought Ray Color → default red.
Oversold Ray Color → default green.
📈 How to use
Apply on any chart; RSI(3) values are always calculated from 4H data (via request.security).
Use rays as reference levels that highlight recent momentum extremes or exhaustion zones.
This is not a buy/sell signal by itself — combine with your own analysis, confirmation tools, and risk management.
Best Recommended time frame is 5 mins, 10 mins & 15 mins for intraday trading.
🧩 Unique features
Groups multiple bars into a single clean ray, reducing clutter.
Uses 4H RSI(3) regardless of the chart’s active timeframe.
Fully customizable appearance (colors, thickness, max events).
⚠️ Disclaimer
This script is provided for educational and informational purposes only.
It does not constitute financial advice or guarantee performance.
Always test thoroughly and use proper risk management before trading live.
3X Sniper BotThe 3X Sniper Bot is built for traders who demand clarity, precision, and confidence in their decision-making. This tool isn’t just another crossover script—it’s a full multi-confirmation system that helps you spot momentum shifts, identify high-probability entries, and filter out the noise.
🔥 Why traders love it:
Triple confirmation engine: Only fires when multiple conditions align, reducing false signals.
Strong vs. Regular vs. Possible setups: Get nuanced alerts that distinguish between high-conviction moves and early opportunities.
Both Buy & Sell coverage: Stay prepared in any market environment.
Smart flexibility: Works across strict or sequenced signal modes, giving you control over how conservative or aggressive you want to trade.
Visual clarity: Clean chart markers and optional regime shading keep your screen easy to read at a glance.
Alert-ready: Set and forget—never miss a move with real-time TradingView alerts.
This indicator was designed to make complex multi-factor analysis simple, giving traders a clear visual edge without clutter or guesswork. Whether you scalp intraday or swing multi-day, the 3X Sniper Bot adapts to your style.
Machine Learning Gaussian Mixture Model | AlphaNattMachine Learning Gaussian Mixture Model | AlphaNatt
A revolutionary oscillator that uses Gaussian Mixture Models (GMM) with unsupervised machine learning to identify market regimes and automatically adapt momentum calculations - bringing statistical pattern recognition techniques to trading.
"Markets don't follow a single distribution - they're a mixture of different regimes. This oscillator identifies which regime we're in and adapts accordingly."
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🤖 THE MACHINE LEARNING
Gaussian Mixture Models (GMM):
Unlike K-means clustering which assigns hard boundaries, GMM uses probabilistic clustering :
Models data as coming from multiple Gaussian distributions
Each market regime is a different Gaussian component
Provides probability of belonging to each regime
More sophisticated than simple clustering
Expectation-Maximization Algorithm:
The indicator continuously learns and adapts using the E-M algorithm:
E-step: Calculate probability of current market belonging to each regime
M-step: Update regime parameters based on new data
Continuous learning without repainting
Adapts to changing market conditions
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🎯 THREE MARKET REGIMES
The GMM identifies three distinct market states:
Regime 1 - Low Volatility:
Quiet, ranging markets
Uses RSI-based momentum calculation
Reduces false signals in choppy conditions
Background: Pink tint
Regime 2 - Normal Market:
Standard trending conditions
Uses Rate of Change momentum
Balanced sensitivity
Background: Gray tint
Regime 3 - High Volatility:
Strong trends or volatility events
Uses Z-score based momentum
Captures extreme moves
Background: Cyan tint
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💡 KEY INNOVATIONS
1. Probabilistic Regime Detection:
Instead of binary regime assignment, provides probabilities:
30% Regime 1, 60% Regime 2, 10% Regime 3
Smooth transitions between regimes
No sudden indicator jumps
2. Weighted Momentum Calculation:
Combines three different momentum formulas
Weights based on regime probabilities
Automatically adapts to market conditions
3. Confidence Indicator:
Shows how certain the model is (white line)
High confidence = strong regime identification
Low confidence = transitional market state
Line transparency changes with confidence
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⚙️ PARAMETER OPTIMIZATION
Training Period (50-500):
50-100: Quick adaptation to recent conditions
100: Balanced (default)
200-500: Stable regime identification
Number of Components (2-5):
2: Simple bull/bear regimes
3: Low/Normal/High volatility (default)
4-5: More granular regime detection
Learning Rate (0.1-1.0):
0.1-0.3: Slow, stable learning
0.3: Balanced (default)
0.5-1.0: Fast adaptation
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📊 TRADING STRATEGIES
Visual Signals:
Cyan gradient: Bullish momentum
Magenta gradient: Bearish momentum
Background color: Current regime
Confidence line: Model certainty
1. Regime-Based Trading:
Regime 1 (pink): Expect mean reversion
Regime 2 (gray): Standard trend following
Regime 3 (cyan): Strong momentum trades
2. Confidence-Filtered Signals:
Only trade when confidence > 70%
High confidence = clearer market state
Avoid transitions (low confidence)
3. Adaptive Position Sizing:
Regime 1: Smaller positions (choppy)
Regime 2: Normal positions
Regime 3: Larger positions (trending)
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🚀 ADVANTAGES OVER OTHER ML INDICATORS
vs K-Means Clustering:
Soft clustering (probabilities) vs hard boundaries
Captures uncertainty and transitions
More mathematically robust
vs KNN (K-Nearest Neighbors):
Unsupervised learning (no historical labels needed)
Continuous adaptation
Lower computational complexity
vs Neural Networks:
Interpretable (know what each regime means)
No overfitting issues
Works with limited data
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📈 PERFORMANCE CHARACTERISTICS
Best Market Conditions:
Markets with clear regime shifts
Volatile to trending transitions
Multi-timeframe analysis
Cryptocurrency markets (high regime variation)
Key Strengths:
Automatically adapts to market changes
No manual parameter adjustment needed
Smooth transitions between regimes
Probabilistic confidence measure
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🔬 TECHNICAL BACKGROUND
Gaussian Mixture Models are used extensively in:
Speech recognition (Google Assistant)
Computer vision (facial recognition)
Astronomy (galaxy classification)
Genomics (gene expression analysis)
Finance (risk modeling at investment banks)
The E-M algorithm was developed at Stanford in 1977 and is one of the most important algorithms in unsupervised machine learning.
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💡 PRO TIPS
Watch regime transitions: Best opportunities often occur when regimes change
Combine with volume: High volume + regime change = strong signal
Use confidence filter: Avoid low confidence periods
Multi-timeframe: Compare regimes across timeframes
Adjust position size: Scale based on identified regime
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⚠️ IMPORTANT NOTES
Machine learning adapts but doesn't predict the future
Best used with other confirmation indicators
Allow time for model to learn (100+ bars)
Not financial advice - educational purposes
Backtest thoroughly on your instruments
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🏆 CONCLUSION
The GMM Momentum Oscillator brings institutional-grade machine learning to retail trading. By identifying market regimes probabilistically and adapting momentum calculations accordingly, it provides:
Automatic adaptation to market conditions
Clear regime identification with confidence levels
Smooth, professional signal generation
True unsupervised machine learning
This isn't just another indicator with "ML" in the name - it's a genuine implementation of Gaussian Mixture Models with the Expectation-Maximization algorithm, the same technology used in:
Google's speech recognition
Tesla's computer vision
NASA's data analysis
Wall Street risk models
"Let the machine learn the market regimes. Trade with statistical confidence."
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Developed by AlphaNatt | Machine Learning Trading Systems
Version: 1.0
Algorithm: Gaussian Mixture Model with E-M
Classification: Unsupervised Learning Oscillator
Not financial advice. Always DYOR.
MatrixScalper Tablo + 3 Bant Osilatör
MatrixScalper “Table + 3-Band Oscillator” is a lightweight, multi-timeframe trend-momentum filter that stacks three histograms (TF1/TF2/TF3—default 5m/15m/1h) and a compact table showing EMA trend, Supertrend, RSI and MACD direction for each timeframe. Green bars/✓ mean bullish alignment, red bars/✗ bearish; mixed or gray implies neutrality. Use it to trade with the higher-timeframe bias (e.g., look for longs when 15m & 60m are bullish and the 5m band flips back to green after a pullback). It’s a filter—not a standalone signal—so combine with price action/S&R/volume; optional alerts can be added for “all-bull” or “all-bear” alignment.
AI-Weighted RSI (Zeiierman)█ Overview
AI-Weighted RSI (Zeiierman) is an adaptive oscillator that enhances classic RSI by applying a correlation-weighted prediction layer. Instead of looking only at RSI values directly, this indicator continuously evaluates how other price- and volume-based features (returns, volatility, volume shifts) correlate with RSI, and then weights them accordingly to project the next RSI state.
The result is a smoother, forward-looking RSI framework that adapts to market conditions in real time.
By leveraging feature correlation instead of static formulas, AI-Weighted RSI behaves like a lightweight learning model, adjusting its emphasis depending on which features are most aligned with RSI behavior during the current regime.
█ How It Works
⚪ Feature Extraction
Each bar, the script computes features: log returns, RSI itself, ATR% (volatility), volume, and volume log-change.
⚪ Correlation Screening
Over a rolling learning window, it measures the correlation of each feature against RSI. The strongest relationships are ranked and selected.
⚪ Adaptive Weighting
Features are standardized (z-scored), then combined using their signed correlations as weights, building a rolling, adaptive prediction of RSI.
⚪ Prediction to RSI Weight
The predicted RSI is mapped back into a “weight” scale (±2 by default). Above 0 = bullish bias, below 0 = bearish bias, with color-graded fills to visualize overbought/oversold pressure.
⚪ Signal Line
A smoothing option (signal length) overlays a moving average of the AI-Weighted RSI for clearer trend confirmation.
█ Why AI-Weighted RSI
⚪ Adaptive to Market Regime
Because the model re-evaluates correlations continuously, it naturally shifts which features dominate, sometimes volatility explains RSI best, sometimes volume, sometimes returns.
⚪ Forward-Looking Bias
Instead of simply reflecting RSI, the model provides a projection, helping anticipate shifts in momentum before RSI itself flips.
█ How to Use
⚪ Directional Bias
Read the RSI relative to 0. Above = bullish momentum bias, below = bearish.
⚪ Overbought / Oversold Zones
Shaded fills beyond +0.5 or -0.5 highlight extremes where RSI pressure often exhausts.
⚪ Divergences
When price makes new highs/lows but AI-Weighted RSI fails to confirm, it often signals weakening momentum.
█ Settings
RSI Length: Lookback for the core RSI calculation.
Signal Length: Smoothing applied to the AI-Weighted RSI output.
Learning Window: Bars used for correlation learning and z-scoring.
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Disclaimer
The content provided in my scripts, indicators, ideas, algorithms, and systems is for educational and informational purposes only. It does not constitute financial advice, investment recommendations, or a solicitation to buy or sell any financial instruments. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
BUY & SELL Probability (M5..D1) - MTFMTF Probability Indicator (M5 to D1)
Indicator — Dual Histogram with Buy/Sell Labels
This indicator is designed to provide a probabilistic bias for bullish or bearish conditions by combining three different analytical components across multiple timeframes. The goal is to reduce noise from single-indicator signals and instead highlight confluence where trend, momentum, and strength agree.
Why this combination is useful
- EMA(200) Trend Filter: Identifies whether price is trading above or below a widely used long-term moving average.
- MACD Momentum: Detects short-term directional momentum through line crossovers.
- ADX Strength: Measures how strong the trend is, preventing signals in weak or flat markets.
By combining these, the indicator avoids situations where one tool signals a trade but others do not, helping to filter out low-probability setups.
How it works
- Each timeframe (M5, M15, H1, H4, D1) generates its own trend, momentum, and strength score.
- Scores are weighted according to user-defined importance and then aggregated into a single probability.
- Proximity to recent support and resistance levels can adjust the final score, accounting for nearby barriers.
- The final probability is displayed as:
- Histogram (subwindow): Green bars for bullish probability >50%, red bars for bearish <50%.
- On-chart labels: Showing exact buy/sell percentages on the last bar for quick reference.
Inputs
- EMA length (default 200), MACD settings, ADX period.
- Weights for each timeframe and component (trend, momentum, strength).
- Optional boost for the chart’s current timeframe.
- Smoothing length for probability values.
- Lookback period for support/resistance adjustment.
How to use it
- A green histogram above zero indicates bullish probability >50%.
- A red histogram below zero indicates bearish probability >50%.
- Neutral readings near 50% show low confluence and may be best avoided.
- Users can adjust weights to emphasize higher or lower timeframes, depending on their trading style.
Notes
- This script does not guarantee profitable trades.
- Best used together with price action, volume, or additional confirmation tools.
- Signals are calculated only on closed bars to avoid repainting.
- For testing and learning purposes — not financial advice.
RSI Pivots with Divergence Overlay█ OVERVIEW
The RSI Pivots with Divergence Overlay indicator is an advanced tool based on RSI, displaying dynamic bands on the price chart to simplify the identification of overbought and oversold conditions. Pivot points and divergences between them are derived from these bands, providing a comprehensive view of the market and enabling the creation of various trading strategies based on this single indicator.
█ CONCEPTS
Areas where RSI exits the bands are often reversal points in the market. The concept of this indicator is to highlight places where the probability of a trend reversal increases. Therefore, pivots and divergences have been added to better identify these key moments. Additionally, the bands allow viewing the market context in relation to the RSI indicator, facilitating analysis of momentum and volatility.
█ KEY FEATURES
Dynamic Bands and RSI Signals: The bands are calculated based on the closing price and RSI value, with dynamic scaling adjusted to market volatility. The upper band corresponds to overbought levels, the lower to oversold, and the midline is their average. The price level relative to the bands serves as a visual RSI signal, indicating potential overbought or oversold conditions.
Pivot Points: The indicator identifies local price highs and lows in relation to RSI levels. The pivot level is taken from the high/low of the candle. A high pivot is detected when the high of the candle reaches a local maximum after crossing the upper RSI level (overbought), signaling a potential reversal. A low pivot appears after a local price minimum following a drop below the lower RSI level (oversold), indicating a possible uptrend reversal. The pivot length (default 2 bars) defines the search range for these extremes, meaning that with a length of 2, a potential divergence signal will appear with a 2-candle delay, as this is the minimum time required to confirm a local pivot. Pivot lines are drawn on the chart, and labels display the RSI value (from the close of the candle) and price at the detection moment. Pivot lines disappear after the detection of the next low pivot for lower lines and high pivot for upper lines, but unbreached lines or those with high volume may still serve as support or resistance levels.
Divergence Detection: The indicator automatically detects divergences to predict trend changes. Bearish divergence occurs when the price forms a higher high pivot, but the RSI (from the close of the candle) is lower than in the previous pivot, indicating weakening upward momentum and a potential bearish reversal. Bullish divergence appears when the price forms a lower low pivot, but the RSI is higher, suggesting building momentum and a possible bullish reversal. Divergences are marked in pivot labels (e.g., "Bear Div" or "Bull Div") and supported by alerts upon detection.
Return Signals: The indicator generates buy and sell signals based on RSI (price) returning to the bands after extreme conditions, independently of pivots and divergences. A buy signal is triggered when RSI (price) crosses above the lower level (exiting oversold), suggesting a potential price rise toward the midline or upper band. A sell signal occurs when RSI (price) falls below the upper level (exiting overbought), indicating a possible price drop toward the lower band. Signals are visualized as arrows (up/down triangles) on the chart, with customizable colors.
█ CONFIGURATION
The indicator offers extensive customization options:
RSI Length (rsiLength): Sets the number of periods used to calculate RSI (default 14).
RSI Upper Level (rsiUpper): Defines the overbought threshold (default 70).
RSI Lower Level (rsiLower): Defines the oversold threshold (default 30).
Band Scaling (scale): Determines the scaling multiplier for bands based on market volatility (default 15.0).
SMA Length for Candle Midpoint (length): Number of periods for calculating the moving average of candle midpoints (default 200). This parameter is used to smooth price data, enabling more accurate volatility assessment and band width adjustment to market dynamics.
Pivot Length (pivotLength): Sets the range (in bars) for detecting local price extremes (default 2).
Pivot Label Offset (pivotLabelOffset): Multiplier for the candle range to position pivot labels (default 0.3).
Show Bands (showBands): Enables/disables the display of bands on the chart.
Show Fill (showFill): Enables/disables the fill between bands and the midline.
Show Pivot Lines (showPivotLines): Enables/disables pivot lines on the chart.
Show Pivot Labels (showPivotLabels): Enables/disables labels with RSI and price values at pivots.
Show Return Signals (showReturnSignals): Enables/disables the display of buy and sell signals.
Colors and Style: Customizable colors for bands, fills, pivot lines, labels, and line widths (default 1).
█ USAGE
The indicator performs best when combined with other technical analysis tools, such as Fibonacci levels, moving averages, or trendlines, to confirm pivot, divergence, and return signals. It enables traders to identify key reversal points, detect hidden trend weaknesses through divergences, and confirm trade entries with return signals.
Usage Examples:
Price bounces off a previous pivot with high volume – this increases the probability of a trend change or correction.
A similar situation when RSI is outside the bands strengthens the signal.
If divergence occurs in addition, we have further confirmation.
This can be combined with Fibonacci levels to check if Fibo zones overlap with pivot lines – this may increase the chance of a strong price reaction.
█ ALERTS
The indicator supports alerts for:
Buy and sell signals (RSI returning to bands).
Detection of bearish and bullish divergences.
RSI ALL INOverbought and Oversold with Candle Pattern Confluences
1. Overbought / Oversold signal only
2. RSI + Engulfing Candle
3. RSI + Hammer/Shooting Star