始めましょう

"rsi divergence"に関するスクリプトを検索

Stochastic RSI OHLC StrategyThe script titled "Stochastic RSI High Low Close Bars" is a versatile trading strategy implemented in Pine Script, designed for TradingView. Here's an overview of its features: Description This strategy leverages the Stochastic RSI to determine entry and exit signals in the market, focusing on high, low, and close values of the indicator. It incorporates various trading styles, stop-loss mechanisms, and multi-timeframe analysis to adapt to different market conditions. Key Features Stochastic RSI Analysis: Uses the Stochastic RSI to identify potential entry points for long and short positions. Tracks high, low, and close values for more granular analysis. Multiple Trading Styles: Supports diverse trading styles like Volume Color Swing, RSI Divergence, RSI Pullback, and more. Allows switching between these styles to suit market dynamics. Session-Based Trading: Offers session control, limiting trades to specific hours (e.g., NY sessions). Can close all positions at the end of the trading day. Stop-Loss and Take-Profit Mechanisms: Includes both static and dynamic stop-losses, with options for time-based stops, trailing stops, and momentum-based exits. Customizable take-profit levels ensure efficient trade management. Volume Analysis: Integrates volume indicators to add a bias for trade entries and exits, enhancing signal reliability. Multi-Timeframe Integration: Employs multi-timeframe RSI analysis, allowing the strategy to capture broader trends and optimize entries. This script is designed to provide flexibility and adaptability, making it useful for different trading strategies and market conditions. It is suitable for traders looking to refine their entries and exits with a focus on the Stochastic RSI.
Pine Script® ストラテジー
gggoaaatの投稿
1
RSI Multi Strategies With Overlay SignalsHello everyone, In this indicator, you will find 6 different entry and exit signals based on the RSI : Entry into overbought and oversold zones Exit from overbought and oversold zones Crossing the 50 level RSI cross RSI MA below or above the 50 level RSI cross RSI MA in the overbought or oversold zones RSI Divergence With the signals identified, you can create your own strategy . (If you have any suggestions, please mention them in the comments). Beyond these signals, you can set SL (Stop Loss) and TP (Take Profit) levels to better manage your positions. SL Methods: Percentage: The stop loss is determined by the percentage you specify. ATR : The stop level is determined based on the Average True Range (ATR). TP Methods: Percentage: The take profit is determined by the percentage you specify. RR ( Risk Reward ): The take profit level is determined based on the distance from the stop level. You can mix and match these options as you like. What makes the indicator unique and effective is its ability to display the RSI in the bottom chart and the signals, SL (Stop Loss), and TP (Take Profit) levels in the overlay chart simultaneously. This feature allows you to manage your trading quickly and easily without the need for using two separate indicators. Let's try out a few strategies together. My entry signal: RSI Entered OS (Oversold) Zone My exit signal: RSI Entered OB (Overbought) Zone I'm not using a stoploss for this strategy ("Fortune favors the brave"). Let's keep ourselves safe by adding a stop loss. I'm adding an ATR-based stop loss. I think it's better now. If you have any questions or suggestions about the indicator, you can contact me. Cheers
Pine Script® インジケーター
Milvettiの投稿
BUY/SELL RSI FLIUX v1.0The "BUY/SELL RSI FLUX v1.0" indicator is designed to provide buy and sell signals based on the RSI (Relative Strength Index) and price action in relation to support and resistance levels. It overlays directly on the price chart and includes the following components: - Support and Resistance Levels: Determined over a specified number of bars (lengthSR), these levels represent potential barriers where price action may stall or reverse. - ATR (Average True Range): Used to measure market volatility. While it's calculated in the script, it's not visualized on the chart as per the latest modification. - RSI: The RSI is calculated over a defined period (lengthRSI) and is used to identify overbought or oversold conditions. Buy signals are generated when the RSI is below the oversold threshold (rsiOversold) and the price is above the support level. Conversely, sell signals occur when the RSI is above the overbought threshold (rsiOverbought), the price is below the resistance level, and additionally, the price is below a long-term moving average, which acts as a trend filter. - Long-Term Moving Average: This moving average is plotted to help identify the prevailing market trend. Sell signals are filtered based on the price's position in relation to this moving average. - Buy/Sell Signals: Visual representations in the form of shapes are plotted below (for buy) or above (for sell) the price bars to indicate potential entry points. By combining these elements, the indicator aims to provide high-probability trading signals that align with both the market's momentum and trend.
Pine Script® インジケーター
Fliuxの投稿
3
TDMACD Divergence Multi Timeframe and Alert [5ema]I reused some functions, made by (i believe that): @paaax: The table position function. @everget: The RSI divergence function. @QuantNomad: The function calculated value and array to show on table for input symbols. @ChaosTrader: The function calculated value TDMACD. ----- What to do? MACD divergence signal. The crossing of MACD and Signal line. The reversal of MACD. The reversal of Signal line. The screener follow 6 different timeframes. Set notification alert when signal appears. ----- How is it created? MACD line = fastMA - slowMA. Signal line = ta.ema(macd(), signalLength) Make function for pivot low & high point of MACD and price. Request.security that function for earch time frame. ----- How to use? Can be combined with many other indicators or candlestick patterns. Customize the input indicators to suit your strategy 1. MACD reversed: 2. Signal line reversed: 3. MACD Divergence : 4. MACD crossing Signal line: 5. Signal on Screener for multi time frame: Green ⦿: Buy. Red ⦿: Sell. Green 〇: Review Buy. Red 〇: Review Sell. ----- This indicator is for reference only, you need your own method and strategy. If you have any questions, please let me know in the comments.
Pine Script® インジケーター
vn5emaの投稿
1
TIGER ALERT RSI DIVThats our first RSI DIV indicator for free use. What is an RSI divergence? What Is the Relative Strength Index (RSI)? The relative strength index (RSI) is a momentum indicator used in technical analysis. RSI measures the speed and magnitude of a security's recent price changes to evaluate overvalued or undervalued conditions in the price of that security. The RSI can do more than point to overbought and oversold securities. It can also indicate securities that may be primed for a trend reversal or corrective pullback in price. It can signal when to buy and sell. T raditionally, an RSI reading of 70 or above indicates an overbought situation. A reading of 30 or below indicates an oversold condition.
Pine Script® インジケーター
PlamenTsonkovの投稿
Favorite Signals w/EMA FilterThe script combines my favorite signals then filters them with three EMAs. Via the Style tab, you can choose to either have the signals color the bar and/or plot a shape above/below. All signals can be turned off via the Inputs tab, which will remove the bar color and/or shape (if not already off in the Style tab) as well as remove the pattern from the alerts function. Remember when using TV alerts, if you change the script settngs, you must create a new alert if you wish to be alerted for the changes you've made. LONG/SHORT SIGNALS INCLUDED FOR: - TD8s - TD9s - Hammer - Shooting Star - Bullish Harami - Bearish Harami - RSI Divergences EMA FILTER LOGIC LONGS: - Price < Fast EMA & Med EMA > Slow EMA = Possible Long Entry - Price > Fast EMA & Med EMA > Slow EMA = Possible Reversal, Tighten Stop or Reduce Position EMA FILTER LOGIC SHORTS: - Price > Fast EMA & Med EMA < Slow EMA = Possible Short Entry - Price < Fast EMA & Med EMA < Slow EMA = Possible Reversal, Tighten Stop/Reduce Position Big up to @spdoinkal, @HPotter, @LonesomeTheBlue, for writing the originals scripts for the signals above. Enjoy!
Pine Script® インジケーター
VolumeVigilanteの投稿
4
Rain On Me IndicatorFinally, we made it :D Rain On Me Indicator, As the name suggests this indicator will make money rain on you. More seriously, this indicator contains : This indicator contains: -Bullish and bearish RSI divergences showing on chart with alerts. -Parabolic SAR with Labels on chart with buying or selling alerts. -3 Moving Average (MA 1 : 7, MA 2 : 21 MA 3 HIDDEN : 50 (Cross alerts for Pullback) -Customizable Bollinger band -Fibonacci on 10 levels with the level 0 to the middle. This Fibonacci help a lot since it can let you find easily entry/exit point, trend and even where to place your Take Profit and Stop Loss. It have alerts for most important levels (0.382, 0.§, 0.618) for Crossunder and Crossover in Bullish or Bearish trend. -Fully Customizable Ichimoku Cloud. -Trend Buy/Sell Labels on chart with buying or selling signal alerts. -Trend color visible on candles. If an alert trigger of Buy/Sell Signal with the same alert based on PSAR, so you can be confident to enter in position. Alway checking fibs level that is the key thing with this indicator. the script has been set to have the best possible results on as many market as possible. But.best result for zfter backtesting is on Forex : EUR/USD, USDJPY, USDCAD. Indice : S&P500, NASDAQ, DOWJONES Commodities : OIL, WTI Everything work on following timeframe : 15MN, 1H, 4H, DAILY, WEEKLY. So that you can avoid having to set it again, whether it be in minutes, hours, days, months. So you can easily trade in the mode that suits you best. It works well on everything from indices to forex to commodities etc. I thank all those who allowed me to carry out this project. IF you feelt free to give your ideas, suggestions, for improve it by sending me messages. This is really a first version sp it may contain bugs / errors that will be fixed over time. A BIG THANK YOU TO QUANTNOMAD WHO GIVE ME HIS PERMISSION TO USE, MODIFY AND REPUBLISH HIS "Ultimate Pivot Points Alerts" Script Indicator : Good trade to all !
Pine Script® インジケーター
RickSimpsonの投稿
49
RSI Swing SignalThis indicator is a tool designed to be used with Steven Hart's RSI Exhaustion strategy. For more information google TheTradingChannel or look him up on YouTube :) The default RSI settings for this strategy are: RSI Overbought: 80 RSI Oversold: 20 Length: 7 When the RSI gets above 80, the line will turn red and the script will begin looking for a specific type of engulfing candle to go short. The same is true when the RSI gets below 20, but the line will turn green and look for longs. It is best used as a back-testing aid, but it can also be used to send emails or SMS alerts whenever the conditions are met. It can also be used as an alternative colored RSI indicator by removing the signals in the settings menu and changing the RSI parameters to whatever you normally use. This can aid in RSI divergence and overbought/sold strategies. Entries: The bright green and bright red lines represent the first type of engulfing candle. The dark green and red lines represent the second type of engulfing candle. Some pairs perform best with only one of these entries, while others work fine with both. This is a counter-trend or consolidation strategy, and is best used in combination with trend-continuation or trend-following strategies. As always, make sure you back-test it before you use it to trade as it works better on some pairs than others.
Pine Script® インジケーター
ZenAndTheArtOfTradingの投稿
22
Algorithm Predator - ML-liteAlgorithm Predator - ML-lite This indicator combines four specialized trading agents with an adaptive multi-armed bandit selection system to identify high-probability trade setups. It is designed for swing and intraday traders who want systematic signal generation based on institutional order flow patterns , momentum exhaustion , liquidity dynamics , and statistical mean reversion . Core Architecture Why These Components Are Combined: The script addresses a fundamental challenge in algorithmic trading: no single detection method works consistently across all market conditions. By deploying four independent agents and using reinforcement learning algorithms to select or blend their outputs, the system adapts to changing market regimes without manual intervention. The Four Trading Agents 1. Spoofing Detector Agent 🎭 Detects iceberg orders through persistent volume at similar price levels over 5 bars Identifies spoofing patterns via asymmetric wick analysis (wicks exceeding 60% of bar range with volume >1.8× average) Monitors order clustering using simplified Hawkes process intensity tracking (exponential decay model) Signal Logic: Contrarian—fades false breakouts caused by institutional manipulation Best Markets: Consolidations, institutional trading windows, low-liquidity hours 2. Exhaustion Detector Agent ⚡ Calculates RSI divergence between price movement and momentum indicator over 5-bar window Detects VWAP exhaustion (price at 2σ bands with declining volume) Uses VPIN reversals (volume-based toxic flow dissipation) to identify momentum failure Signal Logic: Counter-trend—enters when momentum extreme shows weakness Best Markets: Trending markets reaching climax points, over-extended moves 3. Liquidity Void Detector Agent 💧 Measures Bollinger Band squeeze (width <60% of 50-period average) Identifies stop hunts via 20-bar high/low penetration with immediate reversal and volume spike Detects hidden liquidity absorption (volume >2× average with range <0.3× ATR) Signal Logic: Breakout anticipation—enters after liquidity grab but before main move Best Markets: Range-bound pre-breakout, volatility compression zones 4. Mean Reversion Agent 📊 Calculates price z-scores relative to 50-period SMA and standard deviation (triggers at ±2σ) Implements Ornstein-Uhlenbeck process scoring (mean-reverting stochastic model) Uses entropy analysis to detect algorithmic trading patterns (low entropy <0.25 = high predictability) Signal Logic: Statistical reversion—enters when price deviates significantly from statistical equilibrium Best Markets: Range-bound, low-volatility, algorithmically-dominated instruments Adaptive Selection: Multi-Armed Bandit System The script implements four reinforcement learning algorithms to dynamically select or blend agents based on performance: Thompson Sampling (Default - Recommended): Uses Bayesian inference with beta distributions (tracks alpha/beta parameters per agent) Balances exploration (trying underused agents) vs. exploitation (using proven winners) Each agent's win/loss history informs its selection probability Lite Approximation: Uses pseudo-random sampling from price/volume noise instead of true random number generation UCB1 (Upper Confidence Bound): Calculates confidence intervals using: average_reward + sqrt(2 × ln(total_pulls) / agent_pulls) Deterministic algorithm favoring agents with high uncertainty (potential upside) More conservative than Thompson Sampling Epsilon-Greedy: Exploits best-performing agent (1-ε)% of the time Explores randomly ε% of the time (default 10%, configurable 1-50%) Simple, transparent, easily tuned via epsilon parameter Gradient Bandit: Uses softmax probability distribution over agent preference weights Updates weights via gradient ascent based on rewards Best for Blend mode where all agents contribute Selection Modes: Switch Mode: Uses only the selected agent's signal (clean, decisive) Blend Mode: Combines all agents using exponentially weighted confidence scores controlled by temperature parameter (smooth, diversified) Lock Agent Feature: Optional manual override to force one specific agent Useful after identifying which agent dominates your specific instrument Only applies in Switch mode Four choices: Spoofing Detector, Exhaustion Detector, Liquidity Void, Mean Reversion Memory System Dual-Layer Architecture: Short-Term Memory: Stores last 20 trade outcomes per agent (configurable 10-50) Long-Term Memory: Stores episode averages when short-term reaches transfer threshold (configurable 5-20 bars) Memory Boost Mechanism: Recent performance modulates agent scores by up to ±20% Episode Transfer: When an agent accumulates sufficient results, averages are condensed into long-term storage Persistence: Manual restoration of learned parameters via input fields (alpha, beta, weights, microstructure thresholds) How Memory Works: Agent generates signal → outcome tracked after 8 bars (performance horizon) Result stored in short-term memory (win = 1.0, loss = 0.0) Short-term average influences agent's future scores (positive feedback loop) After threshold met (default 10 results), episode averaged into long-term storage Long-term patterns (weighted 30%) + short-term patterns (weighted 70%) = total memory boost Market Microstructure Analysis These advanced metrics quantify institutional order flow dynamics: Order Flow Toxicity (Simplified VPIN): Measures buy/sell volume imbalance over 20 bars: |buy_vol - sell_vol| / (buy_vol + sell_vol) Detects informed trading activity (institutional players with non-public information) Values >0.4 indicate "toxic flow" (informed traders active) Lite Approximation: Uses simple open/close heuristic instead of tick-by-tick trade classification Price Impact Analysis (Simplified Kyle's Lambda): Measures market impact efficiency: |price_change_10| / sqrt(volume_sum_10) Low values = large orders with minimal price impact ( stealth accumulation ) High values = retail-dominated moves with high slippage Lite Approximation: Uses simplified denominator instead of regression-based signed order flow Market Randomness (Entropy Analysis): Counts unique price changes over 20 bars / 20 Measures market predictability High entropy (>0.6) = human-driven, chaotic price action Low entropy (<0.25) = algorithmic trading dominance (predictable patterns) Lite Approximation: Simple ratio instead of true Shannon entropy H(X) = -Σ p(x)·log₂(p(x)) Order Clustering (Simplified Hawkes Process): Tracks self-exciting event intensity (coordinated order activity) Decays at 0.9× per bar, spikes +1.0 when volume >1.5× average High intensity (>0.7) indicates clustering (potential spoofing/accumulation) Lite Approximation: Simple exponential decay instead of full λ(t) = μ + Σ α·exp(-β(t-tᵢ)) with MLE Signal Generation Process Multi-Stage Validation: Stage 1: Agent Scoring Each agent calculates internal score based on its detection criteria Scores must exceed agent-specific threshold (adjusted by sensitivity multiplier) Agent outputs: Signal direction (+1/-1/0) and Confidence level (0.0-1.0) Stage 2: Memory Boost Agent scores multiplied by memory boost factor (0.8-1.2 based on recent performance) Successful agents get amplified, failing agents get dampened Stage 3: Bandit Selection/Blending If Adaptive Mode ON: Switch: Bandit selects single best agent, uses only its signal Blend: All agents combined using softmax-weighted confidence scores If Adaptive Mode OFF: Traditional consensus voting with confidence-squared weighting Signal fires when consensus exceeds threshold (default 70%) Stage 4: Confirmation Filter Raw signal must repeat for consecutive bars (default 3, configurable 2-4) Minimum confidence threshold: 0.25 (25%) enforced regardless of mode Trend alignment check: Long signals require trend_score ≥ -2, Short signals require trend_score ≤ 2 Stage 5: Cooldown Enforcement Minimum bars between signals (default 10, configurable 5-15) Prevents over-trading during choppy conditions Stage 6: Performance Tracking After 8 bars (performance horizon), signal outcome evaluated Win = price moved in signal direction, Loss = price moved against Results fed back into memory and bandit statistics Trading Modes (Presets) Pre-configured parameter sets: Conservative: 85% consensus, 4 confirmations, 15-bar cooldown Expected: 60-70% win rate, 3-8 signals/week Best for: Swing trading, capital preservation, beginners Balanced: 70% consensus, 3 confirmations, 10-bar cooldown Expected: 55-65% win rate, 8-15 signals/week Best for: Day trading, most traders, general use Aggressive: 60% consensus, 2 confirmations, 5-bar cooldown Expected: 50-58% win rate, 15-30 signals/week Best for: Scalping, high-frequency trading, active management Elite: 75% consensus, 3 confirmations, 12-bar cooldown Expected: 58-68% win rate, 5-12 signals/week Best for: Selective trading, high-conviction setups Adaptive: 65% consensus, 2 confirmations, 8-bar cooldown Expected: Varies based on learning Best for: Experienced users leveraging bandit system How to Use 1. Initial Setup (5 Minutes): Select Trading Mode matching your style (start with Balanced) Enable Adaptive Learning (recommended for automatic agent selection) Choose Thompson Sampling algorithm (best all-around performance) Keep Microstructure Metrics enabled for liquid instruments (>100k daily volume) 2. Agent Tuning (Optional): Adjust Agent Sensitivity multipliers (0.5-2.0): <0.8 = Highly selective (fewer signals, higher quality) 0.9-1.2 = Balanced (recommended starting point) 1.3 = Aggressive (more signals, lower individual quality) Monitor dashboard for 20-30 signals to identify dominant agent If one agent consistently outperforms, consider using Lock Agent feature 3. Bandit Configuration (Advanced): Blend Temperature (0.1-2.0): 0.3 = Sharp decisions (best agent dominates) 0.5 = Balanced (default) 1.0+ = Smooth (equal weighting, democratic) Memory Decay (0.8-0.99): 0.90 = Fast adaptation (volatile markets) 0.95 = Balanced (most instruments) 0.97+ = Long memory (stable trends) 4. Signal Interpretation: Green triangle (▲): Long signal confirmed Red triangle (▼): Short signal confirmed Dashboard shows: Active agent (highlighted row with ► marker) Win rate per agent (green >60%, yellow 40-60%, red <40%) Confidence bars (█████ = maximum confidence) Memory size (short-term buffer count) Colored zones display: Entry level (current close) Stop-loss (1.5× ATR) Take-profit 1 (2.0× ATR) Take-profit 2 (3.5× ATR) 5. Risk Management: Never risk >1-2% per signal (use ATR-based stops) Signals are entry triggers, not complete strategies Combine with your own market context analysis Consider fundamental catalysts and news events Use "Confirming" status to prepare entries (not to enter early) 6. Memory Persistence (Optional): After 50-100 trades, check Memory Export Panel Record displayed alpha/beta/weight values for each agent Record VPIN and Kyle threshold values Enable "Restore From Memory" and input saved values to continue learning Useful when switching timeframes or restarting indicator Visual Components On-Chart Elements: Spectral Layers: EMA8 ± 0.5 ATR bands (dynamic support/resistance, colored by trend) Energy Radiance: Multi-layer glow boxes at signal points (intensity scales with confidence, configurable 1-5 layers) Probability Cones: Projected price paths with uncertainty wedges (15-bar projection, width = confidence × ATR) Connection Lines: Links sequential signals (solid = same direction continuation, dotted = reversal) Kill Zones: Risk/reward boxes showing entry, stop-loss, and dual take-profit targets Signal Markers: Triangle up/down at validated entry points Dashboard (Configurable Position & Size): Regime Indicator: 4-level trend classification (Strong Bull/Bear, Weak Bull/Bear) Mode Status: Shows active system (Adaptive Blend, Locked Agent, or Consensus) Agent Performance Table: Real-time win%, confidence, and memory stats Order Flow Metrics: Toxicity and impact indicators (when microstructure enabled) Signal Status: Current state (Long/Short/Confirming/Waiting) with confirmation progress Memory Panel (Configurable Position & Size): Live Parameter Export: Alpha, beta, and weight values per agent Adaptive Thresholds: Current VPIN sensitivity and Kyle threshold Save Reminder: Visual indicator if parameters should be recorded What Makes This Original This script's originality lies in three key innovations: 1. Genuine Meta-Learning Framework: Unlike traditional indicator mashups that simply display multiple signals, this implements authentic reinforcement learning (multi-armed bandits) to learn which detection method works best in current conditions. The Thompson Sampling implementation with beta distribution tracking (alpha for successes, beta for failures) is statistically rigorous and adapts continuously. This is not post-hoc optimization—it's real-time learning. 2. Episodic Memory Architecture with Transfer Learning: The dual-layer memory system mimics human learning patterns: Short-term memory captures recent performance (recency bias) Long-term memory preserves historical patterns (experience) Automatic transfer mechanism consolidates knowledge Memory boost creates positive feedback loops (successful strategies become stronger) This architecture allows the system to adapt without retraining , unlike static ML models that require batch updates. 3. Institutional Microstructure Integration: Combines retail-focused technical analysis (RSI, Bollinger Bands, VWAP) with institutional-grade microstructure metrics (VPIN, Kyle's Lambda, Hawkes processes) typically found in academic finance literature and professional trading systems, not standard retail platforms. While simplified for Pine Script constraints, these metrics provide insight into informed vs. uninformed trading , a dimension entirely absent from traditional technical analysis. Mashup Justification: The four agents are combined specifically for risk diversification across failure modes: Spoofing Detector: Prevents false breakout losses from manipulation Exhaustion Detector: Prevents chasing extended trends into reversals Liquidity Void: Exploits volatility compression (different regime than trending) Mean Reversion: Provides mathematical anchoring when patterns fail The bandit system ensures the optimal tool is automatically selected for each market situation, rather than requiring manual interpretation of conflicting signals. Why "ML-lite"? Simplifications and Approximations This is the "lite" version due to necessary simplifications for Pine Script execution: 1. Simplified VPIN Calculation: Academic Implementation: True VPIN uses volume bucketing (fixed-volume bars) and tick-by-tick buy/sell classification via Lee-Ready algorithm or exchange-provided trade direction flags This Implementation: 20-bar rolling window with simple open/close heuristic (close > open = buy volume) Impact: May misclassify volume during ranging/choppy markets; works best in directional moves 2. Pseudo-Random Sampling: Academic Implementation: Thompson Sampling requires true random number generation from beta distributions using inverse transform sampling or acceptance-rejection methods This Implementation: Deterministic pseudo-randomness derived from price and volume decimal digits: (close × 100 - floor(close × 100)) + (volume % 100) / 100 Impact: Not cryptographically random; may have subtle biases in specific price ranges; provides sufficient variation for agent selection 3. Hawkes Process Approximation: Academic Implementation: Full Hawkes process uses maximum likelihood estimation with exponential kernels: λ(t) = μ + Σ α·exp(-β(t-tᵢ)) fitted via iterative optimization This Implementation: Simple exponential decay (0.9 multiplier) with binary event triggers (volume spike = event) Impact: Captures self-exciting property but lacks parameter optimization; fixed decay rate may not suit all instruments 4. Kyle's Lambda Simplification: Academic Implementation: Estimated via regression of price impact on signed order flow over multiple time intervals: Δp = λ × Δv + ε This Implementation: Simplified ratio: price_change / sqrt(volume_sum) without proper signed order flow or regression Impact: Provides directional indicator of impact but not true market depth measurement; no statistical confidence intervals 5. Entropy Calculation: Academic Implementation: True Shannon entropy requires probability distribution: H(X) = -Σ p(x)·log₂(p(x)) where p(x) is probability of each price change magnitude This Implementation: Simple ratio of unique price changes to total observations (variety measure) Impact: Measures diversity but not true information entropy with probability weighting; less sensitive to distribution shape 6. Memory System Constraints: Full ML Implementation: Neural networks with backpropagation, experience replay buffers (storing state-action-reward tuples), gradient descent optimization, and eligibility traces This Implementation: Fixed-size array queues with simple averaging; no gradient-based learning, no state representation beyond raw scores Impact: Cannot learn complex non-linear patterns; limited to linear performance tracking 7. Limited Feature Engineering: Advanced Implementation: Dozens of engineered features, polynomial interactions (x², x³), dimensionality reduction (PCA, autoencoders), feature selection algorithms This Implementation: Raw agent scores and basic market metrics (RSI, ATR, volume ratio); minimal transformation Impact: May miss subtle cross-feature interactions; relies on agent-level intelligence rather than feature combinations 8. Single-Instrument Data: Full Implementation: Multi-asset correlation analysis (sector ETFs, currency pairs, volatility indices like VIX), lead-lag relationships, risk-on/risk-off regimes This Implementation: Only OHLCV data from displayed instrument Impact: Cannot incorporate broader market context; vulnerable to correlated moves across assets 9. Fixed Performance Horizon: Full Implementation: Adaptive horizon based on trade duration, volatility regime, or profit target achievement This Implementation: Fixed 8-bar evaluation window Impact: May evaluate too early in slow markets or too late in fast markets; one-size-fits-all approach Performance Impact Summary: These simplifications make the script: ✅ Faster: Executes in milliseconds vs. seconds (or minutes) for full academic implementations ✅ More Accessible: Runs on any TradingView plan without external data feeds, APIs, or compute servers ✅ More Transparent: All calculations visible in Pine Script (no black-box compiled models) ✅ Lower Resource Usage: <500 bars lookback, minimal memory footprint ⚠️ Less Precise: Approximations may reduce statistical edge by 5-15% vs. academic implementations ⚠️ Limited Scope: Cannot capture tick-level dynamics, multi-order-book interactions, or cross-asset flows ⚠️ Fixed Parameters: Some thresholds hardcoded rather than dynamically optimized When to Upgrade to Full Implementation: Consider professional Python/C++ versions with institutional data feeds if: Trading with >$100K capital where precision differences materially impact returns Operating in microsecond-competitive environments (HFT, market making) Requiring regulatory-grade audit trails and reproducibility Backtesting with tick-level precision for strategy validation Need true real-time adaptation with neural network-based learning For retail swing/day trading and position management, these approximations provide sufficient signal quality while maintaining usability, transparency, and accessibility. The core logic—multi-agent detection with adaptive selection—remains intact. Technical Notes All calculations use standard Pine Script built-in functions ( ta.ema, ta.atr, ta.rsi, ta.bb, ta.sma, ta.stdev, ta.vwap ) VPIN and Kyle's Lambda use simplified formulas optimized for OHLCV data (see "Lite" section above) Thompson Sampling uses pseudo-random noise from price/volume decimal digits for beta distribution sampling No repainting: All calculations use confirmed bar data (no forward-looking) Maximum lookback: 500 bars (set via max_bars_back parameter) Performance evaluation: 8-bar forward-looking window for reward calculation (clearly disclosed) Confidence threshold: Minimum 0.25 (25%) enforced on all signals Memory arrays: Dynamic sizing with FIFO queue management Limitations and Disclaimers Not Predictive: This indicator identifies patterns in historical data. It cannot predict future price movements with certainty. Requires Human Judgment: Signals are entry triggers, not complete trading strategies. Must be confirmed with your own analysis, risk management rules, and market context. Learning Period Required: The adaptive system requires 50-100 bars minimum to build statistically meaningful performance data for bandit algorithms. Overfitting Risk: Restoring memory parameters from one market regime to a drastically different regime (e.g., low volatility to high volatility) may cause poor initial performance until system re-adapts. Approximation Limitations: Simplified calculations (see "Lite" section) may underperform academic implementations by 5-15% in highly efficient markets. No Guarantee of Profit: Past performance, whether backtested or live-traded, does not guarantee future performance. All trading involves risk of loss. Forward-Looking Bias: Performance evaluation uses 8-bar forward window—this creates slight look-ahead for learning (though not for signals). Real-time performance may differ from indicator's internal statistics. Single-Instrument Limitation: Does not account for correlations with related assets or broader market regime changes. Recommended Settings Timeframe: 15-minute to 4-hour charts (sufficient volatility for ATR-based stops; adequate bar volume for learning) Assets: Liquid instruments with >100k daily volume (forex majors, large-cap stocks, BTC/ETH, major indices) Not Recommended: Illiquid small-caps, penny stocks, low-volume altcoins (microstructure metrics unreliable) Complementary Tools: Volume profile, order book depth, market breadth indicators, fundamental catalysts Position Sizing: Risk no more than 1-2% of capital per signal using ATR-based stop-loss Signal Filtering: Consider external confluence (support/resistance, trendlines, round numbers, session opens) Start With: Balanced mode, Thompson Sampling, Blend mode, default agent sensitivities (1.0) After 30+ Signals: Review agent win rates, consider increasing sensitivity of top performers or locking to dominant agent Alert Configuration The script includes built-in alert conditions: Long Signal: Fires when validated long entry confirmed Short Signal: Fires when validated short entry confirmed Alerts fire once per bar (after confirmation requirements met) Set alert to "Once Per Bar Close" for reliability Taking you to school. — Dskyz, Trade with insight. Trade with anticipation.
Pine Script® インジケーター
DskyzInvestmentsの投稿
5
Order Blocks Zones with Signals█ OVERVIEW “Order Blocks Zones with Signals” is a technical analysis tool that automatically identifies Order Blocks (OB) and optionally Fair Value Gaps (FVG) on the chart. The script visualizes these zones as colored rectangles, offering full customization of style, transparency, and signal display. It also generates entry and exit signals (Break & Exit) that can serve as confirmations in strategies based on price action and market structure. Thanks to flexible candle size filters and rich visual options, the indicator maintains chart clarity and readability. █ CONCEPTS Order Blocks (OB) are key zones on the chart where significant price movements previously occurred — areas where large market participants (institutions, so-called smart money) initiated or closed positions. An OB is the last candle that followed the prior trend before the market reversed (e.g., for a Bullish OB: the last bearish candle before a pivot low and a strong upward impulse). The script detects these levels using local price pivots, analyzing candle direction to filter out less significant movements. FVG (Fair Value Gaps) represent areas of imbalance between buyers and sellers — price gaps formed by a sharp impulse where full trading did not occur due to one-sided order dominance (e.g., excess buy or sell orders). Why combine OB and FVG in one indicator? Combining OB and FVG analysis is essential because these phenomena often occur sequentially in the institutional market cycle: 1. Order Block — institutions enter the market in the OB zone, absorbing orders and building positions. 2. Strong impulse — after smart money entry, a rapid price move creates an FVG (imbalance gap). 3. Retest — price naturally returns to these zones (OB or FVG), drawn by unfilled orders and the search for equilibrium. Such areas strongly attract price, as they represent not only historical institutional levels but also open “holes” in the order book. Retests of OB and FVG are ideal entry opportunities with high reaction probability (rebound or breakout). The indicator combines these two interconnected elements, enabling comprehensive market structure analysis in a single tool. Order Blocks are labeled as: Bullish OB – demand zones, often accumulation areas before an upmove. Bearish OB – supply zones, signaling potential impulse end or correction start. █ FEATURES Order Block Detection (OB Detection): - Automatic identification of demand and supply zones based on pivots. - OB is the last candle aligned with the prior trend, just before the market reversal — precisely identified through candle sequence analysis around the pivot. - OB zones appear with a delay equal to Pivot Length (default 10 bars). - Break signals trigger when a candle’s body (close) fully pierces the zone, causing the zone to disappear immediately (e.g., close < low of Bullish OB → Break Down and zone deletion). - Minimum size filtering via OB Size Multiplier. - Option to create OB without wicks (Include Wicks in OB): when disabled, OB zones are based solely on candle bodies (open/close), ignoring wicks (high/low). Fair Value Gap Detection (FVG Detection): - Optional, with enable/disable capability. - FVG are detected without delay — immediately upon gap occurrence. - Size filtering via Candle Size Period and FVG Size Multiplier. Customizable Styling: - Separate colors and border styles (Solid / Dashed / Dotted) for each zone type. - Adjustable transparency and border thickness. - Unified color for box, border, and signal of the same type. Breakout and Exit Signals: - Break Up – triggered when a candle’s close breaks above a Bearish OB, causing the zone to disappear. - Break Down – triggered when a candle’s close breaks below a Bullish OB, causing the zone to disappear. - Exit Up / Exit Down – temporary exit from the zone without full breakout (price leaves the zone but doesn’t close beyond it). Signal type selection: Break, Exit, or Both. - Alerts: built-in alerts for all signal types — triggered automatically on candle close confirming breakout or exit from OB. █ HOW TO USE Adding to chart: import the code into Pine Editor and run the script on TradingView. Settings configuration: - Pivot Length: controls swing detection sensitivity and OB display delay (default 10). - Include Wicks in OB: enabled (default) – OB includes wicks; disabled – OB uses bodies only. - Size Filter: adjust Candle Size Period and OB/FVG Size Multiplier to filter out small zones. - Colors & Styles: set colors, styles, and transparency for each zone type. - Signal Type: choose which signals to display (Break, Exit, or Both). Signal interpretation: - OB Break Up: price closes above Bearish OB → zone disappears → potential bullish continuation. - OB Break Down: price closes below Bullish OB → zone disappears → potential bearish continuation. - Exit Signals: price leaves the zone temporarily without breakout — often signals impending reversal or pullback. Tips: - Use OB signals alongside other indicators like RSI, MACD, SMI, or trend filters. - Order Blocks from higher timeframes (e.g., 4H, 1D) carry greater significance and reaction strength. - Remember: FVG are detected immediately, OB with delay — a complementary approach! █ APPLICATIONS - Smart Money Concepts (SMC): use OB zones as dynamic support and resistance levels. In an uptrend, look for buy opportunities in bullish OBs, which price often retests before further gains. Combining with RSI, MACD, or Fibonacci levels enhances zone significance, confirming institutional demand. - Breakout Trading: trade based on OB breakout signals. A buy signal after breaking a bearish OB may indicate a strong upward impulse, especially if supported by rising MACD or RSI above 50. Similarly for sell signals after Break Down. - Reversal Zones: Exit signals may indicate the end of a move or correction. Safest to use in alignment with higher-timeframe trend and confirmed by another indicator (e.g., RSI divergence, Fibonacci levels). - Confluence Analysis: combine OB and FVG for deeper market structure and equilibrium insight. When an Order Block overlaps or borders an FVG, we get confluence of two institutional phenomena — OB (smart money entry) + FVG (imbalance) — making these areas particularly strong price magnets, increasing retest and reaction probability. █ NOTES - FVG can be fully disabled for a cleaner chart view. - In consolidation periods, signals may appear more frequently — always confirm with additional trend filters. - Works on all markets and timeframes (crypto, forex, indices, stocks).
Pine Script® インジケーター
Uncle_the_shooterの投稿
Soul Button Scalping (1 min chart) V 1.0Indicator Description - P Signal: The foundational buy signal. It should be confirmed by observing RSI divergence on the 1-minute chart. - Green, Orange, and Blue Signals: Three buy signals generated through the combination of multiple oscillators. These signals should also be cross-referenced with the RSI on the 1-minute chart. - Big White and Big Yellow Signals: These represent strong buy signals, triggered in extreme oversold conditions. - BEST BUY Signal: The most reliable and powerful buy signal available in this indicator. ____________ Red Sell Signal: A straightforward sell signal indicating potential overbought conditions. ____________ Usage Guidance This scalping indicator is specifically designed for use on the 1-minute chart, incorporating data from the 5-minute chart for added context. It is most effective when used in conjunction with: • VWAP (Volume Weighted Average Price), already included in the indicator. • RSI on the 1-minute chart, which should be opened as a separate indicator. • Trendlines, structure breakouts, and price action analysis to confirm signals. Intended for Crypto Scalping: The indicator is optimized for scalping cryptocurrency markets. ____________ Future Enhancements: • Integration of price action and candlestick patterns. • A refined version tailored for trading futures contracts, specifically ES and MES in the stock market.
Pine Script® インジケーター
legno23の投稿
Smart Money Precision Structure [BullByte]Smart Money Precision Structure Advanced Market Structure Analysis Using Institutional Order Flow Concepts --- OVERVIEW Smart Money Precision Structure (SMPS) is a comprehensive market analysis indicator that combines six analytical frameworks to identify high-probability market structure patterns. The indicator uses multi-dimensional scoring algorithms to evaluate market conditions through institutional order flow concepts, providing traders with professional-grade market analysis. --- PURPOSE AND ORIGINALITY Why This Indicator Was Developed • Addresses the gap between retail and institutional analysis methods • Consolidates multiple analysis techniques that professionals use separately • Automates complex market structure evaluation into actionable insights • Eliminates the need for multiple indicators by providing comprehensive analysis What Makes SMPS Original • Six-Layer Confluence System - Unique combination of market regime, structure, volume flow, momentum, price action, and adaptive filtering • Institutional Pattern Recognition - Identifies smart money accumulation and distribution patterns • Adaptive Intelligence - Parameters automatically adjust based on detected market conditions • Real-Time Market Scoring - Proprietary algorithm rates market quality from 0-100% • Structure Break Detection - Advanced pivot analysis identifies trend reversals early --- HOW IT WORKS - TECHNICAL METHODOLOGY 1. Market Regime Analysis Engine The indicator evaluates five core market dimensions: • Volatility Score - Measures current volatility against 50-period historical baseline • Trend Score - Analyzes alignment between 8, 21, and 50-period EMAs • Momentum Score - Combines RSI divergence with MACD signal alignment • Structure Score - Evaluates pivot point formation clarity • Efficiency Score - Calculates directional movement efficiency ratio These scores combine to classify markets into five regimes: • TRENDING - Strong directional movement with aligned indicators • RANGING - Sideways movement with mixed directional signals • VOLATILE - Elevated volatility with unpredictable price swings • QUIET - Low volatility consolidation periods • TRANSITIONAL - Market shifting between different regimes 2. Market Structure Analysis Advanced pivot point analysis identifies: • Higher Highs and Higher Lows for bullish structure • Lower Highs and Lower Lows for bearish structure • Structure breaks when established patterns fail • Dynamic support and resistance from recent pivot points • Key level proximity detection using ATR-based buffers 3. Volume Flow Decoding Institutional activity detection through: • Volume surge identification when volume exceeds 2x average • Buy versus sell pressure analysis using price-volume correlation • Flow strength measurement through directional volume consistency • Divergence detection between volume and price movements • Institutional threshold alerts when unusual volume patterns emerge 4. Multi-Period Momentum Synthesis Weighted momentum calculation across four timeframes: • 1-period momentum weighted at 40% • 3-period momentum weighted at 30% • 5-period momentum weighted at 20% • 8-period momentum weighted at 10% Result smoothed with 6-period EMA for noise reduction. 5. Price Action Quality Assessment Each bar evaluated for: • Range quality relative to 20-period average • Body-to-range ratio for directional conviction • Wick analysis for rejection pattern identification • Pattern recognition including engulfing and hammer formations • Sequential price movement analysis 6. Adaptive Parameter System Parameters automatically adjust based on detected regime: • Trending markets reduce sensitivity and confirmation requirements • Volatile markets increase filtering and require additional confirmations • Ranging markets maintain neutral settings • Transitional markets use moderate adjustments --- COMPLETE SETTINGS GUIDE Section 1: Core Analysis Settings Analysis Sensitivity (0.3-2.0) • Default: 1.0 • Lower values require stronger price movements • Higher values detect more subtle patterns • Scalpers use 0.8-1.2, swing traders use 1.5-2.0 Noise Reduction Level (2-7) • Default: 4 • Controls filtering of false patterns • Higher values reduce pattern frequency • Increase in volatile markets Minimum Move % (0.05-0.50) • Default: 0.15% • Sets minimum price movement threshold • Adjust based on instrument volatility • Forex: 0.05-0.10%, Stocks: 0.15-0.25%, Crypto: 0.20-0.50% High Confirmation Mode • Default: True (Enabled) • Requires all technical conditions to align • Reduces frequency but increases reliability • Disable for more aggressive pattern detection Section 2: Market Regime Detection Enable Regime Analysis • Default: True (Enabled) • Activates market environment evaluation • Essential for adaptive features • Keep enabled for best results Regime Analysis Period (20-100) • Default: 50 bars • Determines regime calculation lookback • Shorter for responsive, longer for stable • Scalping: 20-30, Swing: 75-100 Minimum Market Clarity (0.2-0.8) • Default: 0.4 • Quality threshold for pattern generation • Higher values require clearer conditions • Lower for more patterns, higher for quality Adaptive Parameter Adjustment • Default: True (Enabled) • Enables automatic parameter optimization • Adjusts based on market regime • Highly recommended to keep enabled Section 3: Market Structure Analysis Enable Structure Validation • Default: True (Enabled) • Validates patterns against support/resistance • Confirms trend structure alignment • Essential for reliability Structure Analysis Period (15-50) • Default: 30 bars • Period for structure pattern analysis • Affects support/resistance calculation • Match to your trading timeframe Minimum Structure Alignment (0.3-0.8) • Default: 0.5 • Required structure score for valid patterns • Higher values need stronger structure • Balance with desired frequency Section 4: Analysis Configuration Minimum Strength Level (3-5) • Default: 4 • Minimum confirmations for pattern display • 5 = Maximum reliability, 3 = More patterns • Beginners should use 4-5 Required Technical Confirmations (4-6) • Default: 5 • Number of aligned technical factors • Higher = fewer but better patterns • Works with High Confirmation Mode Pattern Separation (3-20 bars) • Default: 8 bars • Minimum bars between patterns • Prevents clustering and overtrading • Increase for cleaner charts Section 5: Technical Filters Momentum Validation • Default: True (Enabled) • Requires momentum alignment • Filters counter-trend patterns • Essential for trend following Volume Confluence Analysis • Default: True (Enabled) • Requires volume confirmation • Identifies institutional participation • Critical for reliability Trend Direction Filter • Default: True (Enabled) • Only shows patterns with trend • Reduces counter-trend signals • Disable for reversal hunting Section 6: Volume Flow Analysis Institutional Activity Threshold (1.2-3.5) • Default: 2.0 • Multiplier for unusual volume detection • Lower finds more institutional activity • Stock: 2.0-2.5, Forex: 1.5-2.0, Crypto: 2.5-3.5 Volume Surge Multiplier (1.8-4.5) • Default: 2.5 • Defines significant volume increases • Adjust per instrument characteristics • Higher for stocks, lower for forex Volume Flow Period (12-35) • Default: 18 bars • Smoothing for volume analysis • Shorter = responsive, longer = smooth • Match to timeframe used Section 7: Analysis Frequency Control Maximum Analysis Points Per Hour (1-5) • Default: 3 • Limits pattern frequency • Prevents overtrading • Scalpers: 4-5, Swing traders: 1-2 Section 8: Target Level Configuration Target Calculation Method • Default: Market Adaptive • Three modes available: - Fixed: Uses set point distances - Dynamic: ATR-based calculations - Market Adaptive: Structure-based levels Minimum Target/Risk Ratio (1.0-3.0) • Default: 1.5 • Minimum acceptable reward vs risk • Higher filters lower probability setups • Professional standard: 1.5-2.0 Fixed Mode Settings: • Fixed Target Distance: 50 points default • Fixed Invalidation Distance: 30 points default • Use for consistent instruments Dynamic Mode Settings: • Dynamic Target Multiplier: 1.8x ATR default • Dynamic Invalidation Multiplier: 1.0x ATR default • Adapts to volatility automatically Market Adaptive Settings: • Use Structure Levels: True (default) • Structure Level Buffer: 0.1% default • Places levels at actual support/resistance Section 9: Visual Display Settings Color Theme Options • Professional (Teal/Red) - Bullish: Teal (#26a69a) - Bearish: Red (#ef5350) - Neutral: Gray (#78909c) - Best for: Traditional traders, clean appearance • Dark (Neon Green/Pink) - Bullish: Neon Green (#00ff88) - Bearish: Hot Pink (#ff0044) - Neutral: Dark Gray (#333333) - Best for: Dark theme users, high contrast • Light (Green/Red Classic) - Bullish: Green (#4caf50) - Bearish: Red (#f44336) - Neutral: Light Gray (#9e9e9e) - Best for: Light backgrounds, traditional colors • Vibrant (Cyan/Magenta) - Bullish: Cyan (#00ffff) - Bearish: Magenta (#ff00ff) - Neutral: Medium Gray (#888888) - Best for: High visibility, modern appearance Dashboard Position • Options: Top Left, Top Right, Bottom Left, Bottom Right, Middle Left, Middle Right • Default: Top Right • Choose based on chart layout preference Dashboard Size • Full: Complete information display (desktop) • Mobile: Compact view for small screens • Default: Full Analysis Display Style • Arrows : Simple directional markers • Labels : Detailed text information • Zones : Colored areas showing pattern regions • Default: Labels (most informative) Display Options: • Display Analysis Strength: Shows star rating • Display Target Levels: Shows target/invalidation lines • Display Market Regime: Shows regime in pattern labels --- HOW TO USE SMPS - DETAILED GUIDE Understanding the Dashboard Top Row - Header • SMPS Dashboard title • VALUE column: Current readings • STATUS column: Condition assessments Market Regime Row • Shows: TRENDING, RANGING, VOLATILE, QUIET, or TRANSITIONAL • Color coding: Green = Favorable, Red = Caution • Status: FAVORABLE or CAUTION trading conditions Market Score Row • Percentage from 0-100% • Above 60% = Strong conditions • 40-60% = Moderate conditions • Below 40% = Weak conditions Structure Row • Direction: BULLISH, BEARISH, or NEUTRAL • Status: INTACT or BREAK • Orange BREAK indicates structure failure Volume Flow Row • Direction: BUYING or SELLING • Intensity: STRONG or WEAK • Color indicates dominant pressure Momentum Row • Numerical momentum value • Positive = Upward pressure • Negative = Downward pressure Volume Status Row • INST = Institutional activity detected • HIGH = Above average volume • NORM = Normal volume levels Adaptive Mode Row • ACTIVE = Parameters adjusting • STATIC = Fixed parameters • Shows required confirmations Analysis Level Row • Minimum strength level setting • Pattern separation in bars Market State Row • Current analysis: BULLISH, BEARISH, NEUTRAL • Shows analysis price level when active T:R Ratio Row • Current target to risk ratio • GOOD = Meets minimum requirement • LOW = Below minimum threshold Strength Row • BULL or BEAR dominance • Numerical strength value 0-100 Price Row • Current price • Percentage change Last Analysis Row • Previous pattern direction • Bars since last pattern Reading Pattern Signals Bullish Structure Pattern • Upward triangle or "Bullish Structure" label • Star rating shows strength (★★★★★ = strongest) • Green line = potential target level • Red dashed line = invalidation level • Appears below price bars Bearish Structure Pattern • Downward triangle or "Bearish Structure" label • Star rating indicates reliability • Green line = potential target level • Red dashed line = invalidation level • Appears above price bars Pattern Strength Interpretation • ★★★★★ = 6 confirmations (exceptional) • ★★★★☆ = 5 confirmations (strong) • ★★★☆☆ = 4 confirmations (moderate) • ★★☆☆☆ = 3 confirmations (minimum) • Below minimum = filtered out Visual Elements on Chart Lines and Levels: • Gray Line = 21 EMA trend reference • Green Stepline = Dynamic support level • Red Stepline = Dynamic resistance level • Green Solid Line = Active target level • Red Dashed Line = Active invalidation level Pattern Markers: • Triangles = Arrow display mode • Text Labels = Label display mode • Colored Boxes = Zone display mode Target Completion Labels: • "Target" = Price reached target level • "Invalid" = Pattern invalidated by price --- RECOMMENDED USAGE BY TIMEFRAME 1-Minute Charts (Scalping) • Sensitivity: 0.8-1.2 • Noise Reduction: 3-4 • Pattern Separation: 3-5 bars • High Confirmation: Optional • Best for: Quick intraday moves 5-Minute Charts (Precision Intraday) • Sensitivity: 1.0 (default) • Noise Reduction: 4 (default) • Pattern Separation: 8 bars • High Confirmation: Enabled • Best for: Day trading 15-Minute Charts (Short Swing) • Sensitivity: 1.0-1.5 • Noise Reduction: 4-5 • Pattern Separation: 10-12 bars • High Confirmation: Enabled • Best for: Intraday swings 30-Minute to 1-Hour (Position Trading) • Sensitivity: 1.5-2.0 • Noise Reduction: 5-7 • Pattern Separation: 15-20 bars • Regime Period: 75-100 • Best for: Multi-day positions Daily Charts (Swing Trading) • Sensitivity: 1.8-2.0 • Noise Reduction: 6-7 • Pattern Separation: 20 bars • All filters enabled • Best for: Long-term analysis --- MARKET-SPECIFIC SETTINGS Forex Pairs • Minimum Move: 0.05-0.10% • Institutional Threshold: 1.5-2.0 • Volume Surge: 1.8-2.2 • Target Mode: Dynamic or Market Adaptive Stock Indices (ES, NQ, YM) • Minimum Move: 0.10-0.15% • Institutional Threshold: 2.0-2.5 • Volume Surge: 2.5-3.0 • Target Mode: Market Adaptive Individual Stocks • Minimum Move: 0.15-0.25% • Institutional Threshold: 2.0-2.5 • Volume Surge: 2.5-3.5 • Target Mode: Dynamic Cryptocurrency • Minimum Move: 0.20-0.50% • Institutional Threshold: 2.5-3.5 • Volume Surge: 3.0-4.5 • Target Mode: Dynamic • Increase noise reduction --- PRACTICAL APPLICATION EXAMPLES Example 1: Strong Trending Market Dashboard Reading: • Market Regime: TRENDING • Market Score: 75% • Structure: BULLISH, INTACT • Volume Flow: BUYING, STRONG • Momentum: +0.45 Interpretation: • Strong uptrend environment • Institutional buying present • Look for bullish patterns as continuation • Higher probability of success • Consider using lower sensitivity Example 2: Range-Bound Conditions Dashboard Reading: • Market Regime: RANGING • Market Score: 35% • Structure: NEUTRAL • Volume Flow: SELLING, WEAK • Momentum: -0.05 Interpretation: • No clear direction • Low opportunity environment • Patterns are less reliable • Consider waiting for regime change • Or switch to a range-trading approach Example 3: Structure Break Alert Dashboard Reading: • Previous: BULLISH structure • Current: Structure BREAK • Volume: INST flag active • Momentum: Shifting negative Interpretation: • Trend reversal potentially beginning • Institutional participation detected • Watch for bearish pattern confirmation • Adjust bias accordingly • Increase caution on long positions Example 4: Volatile Market Dashboard Reading: • Market Regime: VOLATILE • Market Score: 45% • Adaptive Mode: ACTIVE • Confirmations: Increased to 6 Interpretation: • Choppy conditions • Parameters auto-adjusted • Fewer but higher quality patterns • Wider stops may be needed • Consider reducing position size Below are a few chart examples of the Smart Money Precision Structure (SMPS) indicator in action. • Example 1 – Bullish Structure Detection on SOLUSD 5m • Example 2 – Bearish Structure Detected with Strong Confluence on SOLUSD 5m --- TROUBLESHOOTING GUIDE No Patterns Appearing Check these settings: • High Confirmation Mode may be too restrictive • Minimum Strength Level may be too high • Market Clarity threshold may be too high • Regime filter may be blocking patterns • Try increasing sensitivity Too Many Patterns Adjust these settings: • Enable High Confirmation Mode • Increase Minimum Strength Level to 5 • Increase Pattern Separation • Reduce Sensitivity below 1.0 • Enable all technical filters Dashboard Shows "CAUTION" This indicates: • Market conditions are unfavorable • Regime is RANGING or QUIET • Market score is low • Consider waiting for better conditions • Or adjust expectations accordingly Patterns Not Reaching Targets Consider: • Market may be choppy • Volatility may have changed • Try Dynamic target mode • Reduce target/risk ratio requirement • Check if regime is VOLATILE --- ALERTS CONFIGURATION Alert Message Format Alerts include: • Pattern type (Bullish/Bearish) • Strength rating • Market regime • Analysis price level • Target and invalidation levels • Strength percentage • Target/Risk ratio • Educational disclaimer Setting Up Alerts • Click Alert button on TradingView • Select SMPS indicator • Choose alert frequency • Customize message if desired • Alerts fire on pattern detection --- DATA WINDOW INFORMATION The Data Window displays: • Market Regime Score (0-100) • Market Structure Bias (-1 to +1) • Bullish Strength (0-100) • Bearish Strength (0-100) • Bull Target/Risk Ratio • Bear Target/Risk Ratio • Relative Volume • Momentum Value • Volume Flow Strength • Bull Confirmations Count • Bear Confirmations Count --- BEST PRACTICES AND TIPS For Beginners • Start with default settings • Use High Confirmation Mode • Focus on TRENDING regime only • Paper trade first • Learn one timeframe thoroughly For Intermediate Users • Experiment with sensitivity settings • Try different target modes • Use multiple timeframes • Combine with price action analysis • Track pattern success rate For Advanced Users • Customize per instrument • Create setting templates • Use regime information for bias • Combine with other indicators • Develop systematic rules --- IMPORTANT DISCLAIMERS • This indicator is for educational and informational purposes only • Not financial advice or a trading system • Past performance does not guarantee future results • Trading involves substantial risk of loss • Always use appropriate risk management • Verify patterns with additional analysis • The author is not a registered investment advisor • No liability accepted for trading losses --- VERSION NOTES Version 1.0.0 - Initial Release • Six-layer confluence system • Adaptive parameter technology • Institutional volume detection • Market regime classification • Structure break identification • Real-time dashboard • Multiple display modes • Comprehensive settings ## My Final Thoughts Smart Money Precision Structure represents an advanced approach to market analysis, bringing institutional-grade techniques to retail traders through intelligent automation and multi-dimensional evaluation. By combining six analytical frameworks with adaptive parameter adjustment, SMPS provides comprehensive market intelligence that single indicators cannot achieve. The indicator serves as an educational tool for understanding how professional traders analyze markets, while providing practical pattern detection for those seeking to improve their technical analysis. Remember that all trading involves risk, and this tool should be used as part of a complete analysis approach, not as a standalone trading system. - BullByte
Pine Script® インジケーター
BullByteの投稿
6
Red Pill VWAP/RSI DivergenceI created this indicator to identify moments in time VWAP and RSI are diverging. Ideally useful in strong trend, bullish or bearish, as a potential entry point on a pull back for continuation. Not to be used as a stand alone signal, but rather in conjunction with any possible trend/momentum strategy. VWAP is identified as the blue line. Green label(blue pill) is your potential entry on a pull back when price is above, stacked EMAS & VWAP for a long position. Red label(red pill) is your potential entry on a pull back when price is below inversely stacked EMAS & VWAP for a short position. These are the 2 ideal scenarios I have found. Please back test for yourself I have had great results but must emphasis this is not a stand alone buy/sell. I use it in confluence to add conviction to my current A+ setups. ***Pivot ribbon in chart created by Saty Mahajan set to 3/10 time warp works ideal in conjunction. ***please note false positive and false negative signals can occur, particularly in chop I hope you find this helpful . TRADE SAFE!
Pine Script® インジケーター
Morpheus835の投稿
10