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KAMA Trend Flip - SightLing LabsBuckle up, traders—this open-source KAMA Trend Flip indicator is your ticket to sniping trend reversals with a Kaufman Adaptive Moving Average (KAMA) that’s sharper than a Wall Street shark’s tooth. No voodoo, no fluff—just raw, volatility-adaptive math that dances with the market’s rhythm. It zips through trending rockets and chills in choppy waters, slashing false signals like a samurai. Not laggy like the others - this thing is the real deal! Core Mechanics: • Efficiency Ratio (ER): Reads the market’s pulse (0-1). High ER = turbo-charged MA, low ER = smooth operator. • Adaptive Smoothing: Mixes fast (default power 2) and slow (default 30) constants to match market mood swings. • Trend Signals: KAMA climbs = blue uptrend (bulls run wild). KAMA dips = yellow downtrend (bears take over). Flat = gray snooze-fest. • Alerts: Instant pings on flips—“Trend Flip Up” for long plays, “Down” for shorts. Plug into bots for set-and-forget domination. Why It Crushes: • Smokes static MAs in volatile arenas (crypto, stocks, you name it). Backtests show 20-30% fewer fakeouts than SMA50. • Visual Pop: Overlays price with bold blue/yellow signals. Slap it on BTC 1D to see trends light up like Times Square. • Tweakable: Dial ER length (default 50) to your timeframe. Short for scalps, long for swing trades. Example Settings in Action: • 10s Chart (Hyper-Scalping): Set Source: Close, ER Length: 100, Fast Power: 1, Slow Power: 6. Catches micro-trends in crypto like a heat-seeking missile. Blue/yellow flips scream entry/exit on fast moves. • 2m Chart (Quick Trades): Set Source: Close, ER Length: 14, Fast Power: 1, Slow Power: 6. Perfect for rapid trend shifts in stocks or forex. Signals align with momentum bursts—check historical flips for proof. Deployment: • Drop it on any chart. Backtest settings to match your asset’s volatility—tweak until it sings. • Pair with RSI or volume spikes for killer confirmation. Pro move: Enter on flip + volume pop, exit on reverse. • Strategy-Ready: Slap long/short logic on alerts to build a lean, mean trading machine. Open source from SightLing Labs—grab it, hack it, profit from it. Share your tweaks in the comments and let’s outsmart the market together. Trade hard, win big!
Pine Script® göstergesi
SightLineLabs tarafından
FlowStateTrader FlowState Trader - Advanced Time-Filtered Strategy ## Overview FlowState Trader is a sophisticated algorithmic trading strategy that combines precision entry signals with intelligent time-based filtering and adaptive risk management. Built for traders seeking to achieve their optimal performance state, FlowState identifies high-probability trading opportunities within user-defined time windows while employing dynamic trailing stops and partial position management. ## Core Strategy Philosophy FlowState Trader operates on the principle that peak trading performance occurs when three elements align: **Focus** (precise entry signals), **Flow** (optimal time windows), and **State** (intelligent position management). This strategy excels at finding reversal opportunities at key support and resistance levels while filtering out suboptimal trading periods to keep traders in their optimal flow state. ## Key Features ### 🎯 Focus Entry System **Support/Resistance Zone Trading**: - Dynamic identification of key price levels using configurable lookback periods - Entry signals triggered when price interacts with these critical zones - Volume confirmation ensures genuine breakout/reversal momentum - Trend filter alignment prevents counter-trend disasters **Entry Conditions**: - **Long Signals**: Price closes above support buffer, touches support level, with above-average volume - **Short Signals**: Price closes below resistance buffer, touches resistance level, with above-average volume - Optional trend filter using EMA or SMA for directional bias confirmation ### ⏰ FlowState Time Filtering System **Comprehensive Time Controls**: - **12-Hour Format Trading Windows**: User-friendly AM/PM time selection - **Multi-Timezone Support**: UTC, EST, PST, CST with automatic conversion - **Day-of-Week Filtering**: Trade only weekdays, weekends, or both - **Lunch Hour Avoidance**: Automatically skips low-volume lunch periods (12-1 PM) - **Visual Time Indicators**: Background coloring shows active/inactive trading periods **Smart Time Features**: - Handles overnight trading sessions seamlessly - Prevents trades during historically poor performance periods - Customizable trading hours for different market sessions - Real-time trading window status in dashboard ### 🛡️ Adaptive Risk Management **Multi-Level Take Profit System**: - **TP1**: First profit target with optional partial position closure - **TP2**: Final profit target for remaining position - **Flexible Scaling**: Choose number of contracts to close at each level **Dynamic Trailing Stop Technology**: - **Three Operating Modes**: - **Conservative**: Earlier activation, tighter trailing (protect profits) - **Balanced**: Optimal risk/reward balance (recommended) - **Aggressive**: Later activation, wider trailing (let winners run) - **ATR-Based Calculations**: Adapts to current market volatility - **Automatic Activation**: Engages when position reaches profitability threshold ### 📊 Intelligent Position Sizing **Contract-Based Management**: - Configurable entry quantity (1-1000 contracts) - Partial close quantities for profit-taking - Clear position tracking and P&L monitoring - Real-time position status updates ### 🎨 Professional Visualization **Enhanced Chart Elements**: - **Entry Zone Highlighting**: Clear visual identification of trading opportunities - **Dynamic Risk/Reward Lines**: Real-time TP and SL levels with price labels - **Trailing Stop Visualization**: Live tracking of adaptive stop levels - **Support/Resistance Lines**: Key level identification - **Time Window Background**: Visual confirmation of active trading periods **Dual Dashboard System**: - **Strategy Dashboard**: Real-time position info, settings status, and current levels - **Performance Scorecard**: Live P&L tracking, win rates, and trade statistics - **Customizable Sizing**: Small, Medium, or Large display options ### ⚙️ Comprehensive Customization **Core Strategy Settings**: - **Lookback Period**: Support/resistance calculation period (5-100 bars) - **ATR Configuration**: Period and multipliers for stops/targets - **Reward-to-Risk Ratios**: Customizable profit target calculations - **Trend Filter Options**: EMA/SMA selection with adjustable periods **Time Filter Controls**: - **Trading Hours**: Start/end times in 12-hour format - **Timezone Selection**: Four major timezone options - **Day Restrictions**: Weekend-only, weekday-only, or unrestricted - **Session Management**: Lunch hour avoidance and custom periods **Risk Management Options**: - **Trailing Stop Modes**: Conservative/Balanced/Aggressive presets - **Partial Close Settings**: Enable/disable with custom quantities - **Alert System**: Comprehensive notifications for all trade events ### 📈 Performance Tracking **Real-Time Metrics**: - Net profit/loss calculation - Win rate percentage - Profit factor analysis - Maximum drawdown tracking - Total trade count and breakdown - Current position P&L **Trade Analytics**: - Winner/loser ratio tracking - Real-time performance scorecard - Strategy effectiveness monitoring - Risk-adjusted return metrics ### 🔔 Alert System **Comprehensive Notifications**: - Entry signal alerts with price and quantity - Take profit level hits (TP1 and TP2) - Stop loss activations - Trailing stop engagements - Position closure notifications ## Strategy Logic Deep Dive ### Entry Signal Generation The strategy identifies high-probability reversal points by combining multiple confirmation factors: 1. **Price Action**: Looks for price interaction with key support/resistance levels 2. **Volume Confirmation**: Ensures sufficient market interest and liquidity 3. **Trend Alignment**: Optional filter prevents counter-trend positions 4. **Time Validation**: Only trades during user-defined optimal periods 5. **Zone Analysis**: Entry occurs within calculated buffer zones around key levels ### Risk Management Philosophy FlowState Trader employs a three-tier risk management approach: 1. **Initial Protection**: ATR-based stop losses set at strategy entry 2. **Profit Preservation**: Trailing stops activate once position becomes profitable 3. **Scaled Exit**: Partial profit-taking allows for both security and potential ### Time-Based Edge The time filtering system recognizes that not all trading hours are equal: - Avoids low-volume, high-spread periods - Focuses on optimal liquidity windows - Prevents trading during news events (lunch hours) - Allows customization for different market sessions ## Best Practices and Optimization ### Recommended Settings **For Scalping (1-5 minute charts)**: - Lookback Period: 10-20 - ATR Period: 14 - Trailing Stop: Conservative mode - Time Filter: Major session hours only **For Day Trading (15-60 minute charts)**: - Lookback Period: 20-30 - ATR Period: 14-21 - Trailing Stop: Balanced mode - Time Filter: Extended trading hours **For Swing Trading (4H+ charts)**: - Lookback Period: 30-50 - ATR Period: 21+ - Trailing Stop: Aggressive mode - Time Filter: Disabled or very broad ### Market Compatibility - **Forex**: Excellent for major pairs during active sessions - **Stocks**: Ideal for liquid stocks during market hours - **Futures**: Perfect for index and commodity futures - **Crypto**: Effective on major cryptocurrencies (24/7 capability) ### Risk Considerations - **Market Conditions**: Performance varies with volatility regimes - **Timeframe Selection**: Lower timeframes require tighter risk management - **Position Sizing**: Never risk more than 1-2% of account per trade - **Backtesting**: Always test on historical data before live implementation ## Educational Value FlowState serves as an excellent learning tool for: - Understanding support/resistance trading - Learning proper time-based filtering - Mastering trailing stop techniques - Developing systematic trading approaches - Risk management best practices ## Disclaimer This strategy is for educational and informational purposes only. Past performance does not guarantee future results. Trading involves substantial risk of loss and is not suitable for all investors. Users should thoroughly backtest the strategy and understand all risks before live trading. Always use proper position sizing and never risk more than you can afford to lose. --- *FlowState Trader represents the evolution of systematic trading - combining classical technical analysis with modern risk management and intelligent time filtering to help traders achieve their optimal performance state through systematic, disciplined execution.*
Pine Script® stratejisi
TradeManager_PRO tarafından
1
Realized Volatility (StdDev of Returns, %)📌 Realized Volatility (StdDev of Returns, %) This indicator measures realized volatility directly from price returns, instead of the common but misleading approach of calculating standard deviation around a moving average. 🔹 How it works: Computes close-to-close log returns (the most common way volatility is measured in finance). Calculates the standard deviation of these returns over a chosen lookback period (default = 200 bars). Converts results into percentages for easier interpretation. Provides three key volatility measures: Daily Realized Vol (%) – raw standard deviation of returns. Annualized Vol (%) – scaled by √250 trading days (market convention). Horizon Vol (%) – volatility over a custom horizon (default = 5 days, i.e. weekly). 🔹 Why use this indicator? Shows true realized volatility from historical returns. More accurate than measuring deviation around a moving average. Useful for traders analyzing risk, position sizing, and comparing realized vs implied volatility. ⚠️ Note: It is best used on the Daily Chart! By default, this uses log returns (which are additive and standard in quant finance). If you prefer, you can easily switch to simple % returns in the code. Volatility estimates depend on your chosen lookback length and may vary across timeframes.
Pine Script® göstergesi
risk_alpha tarafından
Range Percent Histogram📌 Range Percent Histogram – Indicator Description The Range Percent Histogram is a custom indicator that behaves like a traditional volume histogram, but instead of showing traded volume it displays the percentage range of each candle. In other words, the height of each bar represents how much the price moved (in percentage terms) within that candle, from its low to its high. 🔧 What it shows The indicator has two main components: Component Description Histogram Bars Columns plotted in red or green depending on the candle direction (green = bullish candle, red = bearish). The height of each bar = (high - low) / low * 100. That means a candle that moved, for example, 1 % from its lowest point to its highest point will show a bar with 1 % height. Moving Average (optional) A 20-period Simple Moving Average applied directly to the bar values. It can be turned ON/OFF via a checkbox and helps you detect whether current range activity is above or below the average range of the past candles. ⚙️ How it works Every time a new candle closes, the indicator calculates its range and converts it into a percentage. This value is drawn as a column under the chart. If the closing price is above the opening price → the bar is green (bullish range). If the closing price is below the opening price → the bar is red (bearish range). When the Show Moving Average option is enabled, a smooth line is plotted on top of the histogram representing the average percentage range of the last 20 candles. 📈 How to use it This indicator is very helpful for detecting moments of range expansion or contraction. One powerful way to use it is similar to a volume exhaustion / low-volume pattern: Situation Interpretation Consecutive bars with very low height Price is in a period of low volatility → possible accumulation or "pause" phase. A sudden large bar after a series of small ones Indicates a strong pickup in volatility → often marks the start of a new impulse in the direction of the breakout.
Pine Script® göstergesi
BullBearSR tarafından
Machine Learning BBPct [BackQuant]Machine Learning BBPct What this is (in one line) A Bollinger Band %B oscillator enhanced with a simplified K-Nearest Neighbors (KNN) pattern matcher. The model compares today’s context (volatility, momentum, volume, and position inside the bands) to similar situations in recent history and blends that historical consensus back into the raw %B to reduce noise and improve context awareness. It is informational and diagnostic—designed to describe market state, not to sell a trading system. Background: %B in plain terms Bollinger %B measures where price sits inside its dynamic envelope: 0 at the lower band, 1 at the upper band, ~ 0.5 near the basis (the moving average). Readings toward 1 indicate pressure near the envelope’s upper edge (often strength or stretch), while readings toward 0 indicate pressure near the lower edge (often weakness or stretch). Because bands adapt to volatility, %B is naturally comparable across regimes. Why add (simplified) KNN? Classic %B is reactive and can be whippy in fast regimes. The simplified KNN layer builds a “nearest-neighbor memory” of recent market states and asks: “When the market looked like this before, where did %B tend to be next bar?” It then blends that estimate with the current %B. Key ideas: • Feature vector . Each bar is summarized by up to five normalized features:   – %B itself (normalized)   – Band width (volatility proxy)   – Price momentum (ROC)   – Volume momentum (ROC of volume)   – Price position within the bands • Distance metric . Euclidean distance ranks the most similar recent bars. • Prediction . Average the neighbors’ prior %B (lagged to avoid lookahead), inverse-weighted by distance. • Blend . Linearly combine raw %B and KNN-predicted %B with a configurable weight; optional filtering then adapts to confidence. This remains “simplified” KNN: no training/validation split, no KD-trees, no scaling beyond windowed min-max, and no probabilistic calibration. How the script is organized (by input groups) 1) BBPct Settings • Price Source – Which price to evaluate (%B is computed from this). • Calculation Period – Lookback for SMA basis and standard deviation. • Multiplier – Standard deviation width (e.g., 2.0). • Apply Smoothing / Type / Length – Optional smoothing of the %B stream before ML (EMA, RMA, DEMA, TEMA, LINREG, HMA, etc.). Turning this off gives you the raw %B. 2) Thresholds • Overbought/Oversold – Default 0.8 / 0.2 (inside ). • Extreme OB/OS – Stricter zones (e.g., 0.95 / 0.05) to flag stretch conditions. 3) KNN Machine Learning • Enable KNN – Switch between pure %B and hybrid. • K (neighbors) – How many historical analogs to blend (default 8). • Historical Period – Size of the search window for neighbors. • ML Weight – Blend between raw %B and KNN estimate. • Number of Features – Use 2–5 features; higher counts add context but raise the risk of overfitting in short windows. 4) Filtering • Method – None, Adaptive, Kalman-style (first-order), or Hull smoothing. • Strength – How aggressively to smooth. “Adaptive” uses model confidence to modulate its alpha: higher confidence → stronger reliance on the ML estimate. 5) Performance Tracking • Win-rate Period – Simple running score of past signal outcomes based on target/stop/time-out logic (informational, not a robust backtest). • Early Entry Lookback – Horizon for forecasting a potential threshold cross. • Profit Target / Stop Loss – Used only by the internal win-rate heuristic. 6) Self-Optimization • Enable Self-Optimization – Lightweight, rolling comparison of a few canned settings (K = 8/14/21 via simple rules on %B extremes). • Optimization Window & Stability Threshold – Governs how quickly preferred K changes and how sensitive the overfitting alarm is. • Adaptive Thresholds – Adjust the OB/OS lines with volatility regime (ATR ratio), widening in calm markets and tightening in turbulent ones (bounded 0.7–0.9 and 0.1–0.3). 7) UI Settings • Show Table / Zones / ML Prediction / Early Signals – Toggle informational overlays. • Signal Line Width, Candle Painting, Colors – Visual preferences. Step-by-step logic A) Compute %B Basis = SMA(source, len); dev = stdev(source, len) × multiplier; Upper/Lower = Basis ± dev. %B = (price − Lower) / (Upper − Lower). Optional smoothing yields standardBB . B) Build the feature vector All features are min-max normalized over the KNN window so distances are in comparable units. Features include normalized %B, normalized band width, normalized price ROC, normalized volume ROC, and normalized position within bands. You can limit to the first N features (2–5). C) Find nearest neighbors For each bar inside the lookback window, compute the Euclidean distance between current features and that bar’s features. Sort by distance, keep the top K . D) Predict and blend Use inverse-distance weights (with a strong cap for near-zero distances) to average neighbors’ prior %B (lagged by one bar). This becomes the KNN estimate. Blend it with raw %B via the ML weight. A variance of neighbor %B around the prediction becomes an uncertainty proxy ; combined with a stability score (how long parameters remain unchanged), it forms mlConfidence ∈ . The Adaptive filter optionally transforms that confidence into a smoothing coefficient. E) Adaptive thresholds Volatility regime (ATR(14) divided by its 50-bar SMA) nudges OB/OS thresholds wider or narrower within fixed bounds. The aim: comparable extremeness across regimes. F) Early entry heuristic A tiny two-step slope/acceleration probe extrapolates finalBB forward a few bars. If it is on track to cross OB/OS soon (and slope/acceleration agree), it flags an EARLY_BUY/SELL candidate with an internal confidence score. This is explicitly a heuristic—use as an attention cue, not a signal by itself. G) Informational win-rate The script keeps a rolling array of trade outcomes derived from signal transitions + rudimentary exits (target/stop/time). The percentage shown is a rough diagnostic , not a validated backtest. Outputs and visual language • ML Bollinger %B (finalBB) – The main line after KNN blending and optional filtering. • Gradient fill – Greenish tones above 0.5, reddish below, with intensity following distance from the midline. • Adaptive zones – Overbought/oversold and extreme bands; shaded backgrounds appear at extremes. • ML Prediction (dots) – The KNN estimate plotted as faint circles; becomes bright white when confidence > 0.7. • Early arrows – Optional small triangles for approaching OB/OS. • Candle painting – Light green above the midline, light red below (optional). • Info panel – Current value, signal classification, ML confidence, optimized K, stability, volatility regime, adaptive thresholds, overfitting flag, early-entry status, and total signals processed. Signal classification (informational) The indicator does not fire trade commands; it labels state: • STRONG_BUY / STRONG_SELL – finalBB beyond extreme OS/OB thresholds. • BUY / SELL – finalBB beyond adaptive OS/OB. • EARLY_BUY / EARLY_SELL – forecast suggests a near-term cross with decent internal confidence. • NEUTRAL – between adaptive bands. Alerts (what you can automate) • Entering adaptive OB/OS and extreme OB/OS. • Midline cross (0.5). • Overfitting detected (frequent parameter flipping). • Early signals when early confidence > 0.7. These are purely descriptive triggers around the indicator’s state. Practical interpretation • Mean-reversion context – In range markets, adaptive OS/OB with ML smoothing can reduce whipsaws relative to raw %B. • Trend context – In persistent trends, the KNN blend can keep finalBB nearer the mid/upper region during healthy pullbacks if history supports similar contexts. • Regime awareness – Watch the volatility regime and adaptive thresholds. If thresholds compress (high vol), “OB/OS” comes sooner; if thresholds widen (calm), it takes more stretch to flag. • Confidence as a weight – High mlConfidence implies neighbors agree; you may rely more on the ML curve. Low confidence argues for de-emphasizing ML and leaning on raw %B or other tools. • Stability score – Rising stability indicates consistent parameter selection and fewer flips; dropping stability hints at a shifting backdrop. Methodological notes • Normalization uses rolling min-max over the KNN window. This is simple and scale-agnostic but sensitive to outliers; the distance metric will reflect that. • Distance is unweighted Euclidean. If you raise featureCount, you increase dimensionality; consider keeping K larger and lookback ample to avoid sparse-neighbor artifacts. • Lag handling intentionally uses neighbors’ previous %B for prediction to avoid lookahead bias. • Self-optimization is deliberately modest: it only compares a few canned K/threshold choices using simple “did an extreme anticipate movement?” scoring, then enforces a stability regime and an overfitting guard. It is not a grid search or GA. • Kalman option is a first-order recursive filter (fixed gain), not a full state-space estimator. • Hull option derives a dynamic length from 1/strength; it is a convenience smoothing alternative. Limitations and cautions • Non-stationarity – Nearest neighbors from the recent window may not represent the future under structural breaks (policy shifts, liquidity shocks). • Curse of dimensionality – Adding features without sufficient lookback can make genuine neighbors rare. • Overfitting risk – The script includes a crude overfitting detector (frequent parameter flips) and will fall back to defaults when triggered, but this is only a guardrail. • Win-rate display – The internal score is illustrative; it does not constitute a tradable backtest. • Latency vs. smoothness – Smoothing and ML blending reduce noise but add lag; tune to your timeframe and objectives. Tuning guide • Short-term scalping – Lower len (10–14), slightly lower multiplier (1.8–2.0), small K (5–8), featureCount 3–4, Adaptive filter ON, moderate strength. • Swing trading – len (20–30), multiplier ~2.0, K (8–14), featureCount 4–5, Adaptive thresholds ON, filter modest. • Strong trends – Consider higher adaptive_upper/lower bounds (or let volatility regime do it), keep ML weight moderate so raw %B still reflects surges. • Chop – Higher ML weight and stronger Adaptive filtering; accept lag in exchange for fewer false extremes. How to use it responsibly Treat this as a state descriptor and context filter. Pair it with your execution signals (structure breaks, volume footprints, higher-timeframe bias) and risk management. If mlConfidence is low or stability is falling, lean less on the ML line and more on raw %B or external confirmation. Summary Machine Learning BBPct augments a familiar oscillator with a transparent, simplified KNN memory of recent conditions. By blending neighbors’ behavior into %B and adapting thresholds to volatility regime—while exposing confidence, stability, and a plain early-entry heuristic—it provides an informational, probability-minded view of stretch and reversion that you can interpret alongside your own process.
Pine Script® göstergesi
BackQuant tarafından
2
VSA - The Volume HUDVSA Volume HUD: Your At-a-Glance Volume Dashboard Tired of cluttered charts with multiple indicators taking up screen space? The VSA Volume HUD is a clean, powerful, and fully customisable Heads-Up Display that puts all the critical volume and price action data you need into one compact box, right on your chart. Designed for traders who rely on Volume Spread Analysis (VSA), this tool helps you instantly gauge the strength, conviction, and context behind every price move as it happens. Key Features This indicator isn't just about showing the current volume; it provides a comprehensive, real-time analysis of the market's activity. Real-time VSA Dashboard: A persistent on-screen table that updates with every tick, giving you instant feedback without needing to look away from the price. The HUD is fully draggable (hold Ctrl/Cmd + click and drag) to place it anywhere you like. Essential Volume Metrics: Current Volume: Displayed in a clean, abbreviated format (e.g., 1.25M for millions, 54.3K for thousands). % Change (vs. Previous Bar): Instantly see if volume is expanding or contracting. Vs Short-Term Average: Compare the current bar's volume to a moving average to spot unusual spikes. Volume Velocity: Measures the rate of change in volume over a short period, helping you spot acceleration or deceleration in market interest. Relative Volume (RVOL): See how the current volume compares to the average for that specific time of day, perfect for identifying abnormally high or low activity. Price Action & Volatility Context: Range vs. ATR: Quickly determine if the current bar's volatility is expanding or contracting compared to the recent average. Price vs. VWAP: See how far the current price has deviated from the session's Volume-Weighted Average Price, a key level for institutional traders. Deep Customization is Key Tailor the HUD to perfectly match your trading style and chart aesthetic. Display & Layout: Compact Mode: Remove the metric labels for a sleek, minimalist view that saves screen space. Bar Meters: Enable optional visual bars next to key metrics for a quick, graphical representation of strength. Total Control: Toggle every single metric on or off to build the exact dashboard you need. Adjust text size, position, and background opacity with ease. Smart Coloring & Visual Alerts: Advanced VSA Coloring: This isn't just about up/down candles. The script intelligently colors volume based on confluence. It highlights increasing volume on a strong up-bar (bullish confirmation) or increasing volume on a down-bar (potential climax or distribution), giving you a deeper VSA context. High Volume Highlight: Make standout bars impossible to miss! The entire HUD background can change color automatically when volume surges past a custom threshold (e.g., over 150% of the average), instantly drawing your attention to critical moments. Full Color Customization: Change every color to match your chart's theme, including separate colors for bullish/bearish moves, the background, and the border. How to Use It The VSA Volume HUD is a powerful confirmation tool. Use it to: Confirm Breakouts: Look for a spike in Volume vs. Average and RVOL as price breaks a key level. Spot Exhaustion: Notice high volume on a narrow-range candle after a long trend, visible through the Range/ATR metric. Gauge Conviction: Use the Advanced Coloring to see if volume is supporting the price move (e.g., green volume on a green candle) or diverging from it.
Pine Script® göstergesi
MrPhipps tarafından
Transfer Function Filter [theUltimator5]The Transfer Function Filter is an engineering style approach to transform the price action on a chart into a frequency, then filter out unwanted signals using Butterworth-style filter approach. This indicator allows you to analyze market structure by isolating or removing different frequency components of price movement—similar to how engineers filter signals in control systems and electrical circuits. 🔎 Features Four Filter Types 1) Low Pass Filter – Smooths price data, highlighting long-term trends while filtering out short-term noise. This filter acts similar to an EMA, removing noisy signals, resulting in a smooth curve that follows the price of the stock relative to the filter cutoff settings. Real world application for low pass filter - Used in power supplies to provide a clean, stable power level. 2) High Pass Filter – Removes slow-moving trends to emphasize short-term volatility and rapid fluctuations. The high pass filter removes the "DC" level of the chart, removing the average price moves and only outputting volatility. Real world application for high pass filter - Used in audio equalizers to remove low-frequency noise (like rumble) while allowing higher frequencies to pass through, improving sound clarity. 3) Band Pass Filter – Allows signals to plot only within a band of bar ranges. This filter removes the low pass "DC" level and the high pass "high frequency noise spikes" and shows a signal that is effectively a smoothed volatility curve. This acts like a moving average for volatility. Real world application for band pass filter - Radio stations only allow certain frequency bands so you can change your radio channel by switching which frequency band your filter is set to. 4) Band Stop Filter – Suppresses specific frequency bands (cycles between two cutoffs). This filter allows through the base price moving average, but keeps the high frequency volatility spikes. It allows you to filter out specific time interval price action. Real world application for band stop filter - If there is prominent frequency signal in the area which can cause unnecessary noise in your system, a band stop filter can cancel out just that frequency so you get everything else Configurable Parameters • Cutoff Periods – Define the cycle lengths (in bars) to filter. This is a bit counter-intuitive with the numbering since the higher the bar count on the low-pass filter, the lower the frequency cutoff is. The opposite holds true for the high pass filter. • Filter Order – Adjust steepness and responsiveness (higher order = sharper filtering, but with more delay). • Overlay Option – Display Low Pass & Band Stop outputs directly on the price chart, or in a separate pane. This is enabled by default, plotting the filters that mimic moving averages directly onto the chart. • Source Selection – Apply filters to close, open, high, low, or custom sources. Histograms for Comparison • BS–LP Histogram – Shows distance between Band Stop and Low Pass filters. • BP–HP Histogram – Highlights differences between Band Pass and High Pass filters. Histograms give the visualization of a pseudo-MACD style indicator Visual & Informational Aids • Customizable colors for each filter line. • Optional zero-line for histogram reference. • On-chart info table summarizing active filters, cutoff settings, histograms, and filter order. 📊 Use Cases Trend Detection – Use the Low Pass filter to smooth noise and follow underlying market direction. Volatility & Cycle Analysis – Apply High Pass or Band Pass to capture shorter-term patterns. Noise Suppression – Deploy Band Stop to remove specific choppy frequencies. Momentum Insight – Watch the histograms to spot divergences and relative filter strength.
Pine Script® göstergesi
TheUltimator5 tarafından
Mutanabby_AI | ATR+ | Trend-Following StrategyThis document presents the Mutanabby_AI | ATR+ Pine Script strategy, a systematic approach designed for trend identification and risk-managed position entry in financial markets. The strategy is engineered for long-only positions and integrates volatility-adjusted components to enhance signal robustness and trade management. Strategic Design and Methodological Basis The Mutanabby_AI | ATR+ strategy is constructed upon a foundation of established technical analysis principles, with a focus on objective signal generation and realistic trade execution. Heikin Ashi for Trend Filtering: The core price data is processed via Heikin Ashi (HA) methodology to mitigate transient market noise and accentuate underlying trend direction. The script offers three distinct HA calculation modes, allowing for comparative analysis and validation: Manual Calculation: Provides a transparent and deterministic computation of HA values. ticker.heikinashi(): Utilizes TradingView's built-in function, employing confirmed historical bars to prevent repainting artifacts. Regular Candles: Allows for direct comparison with standard OHLC price action. This multi-methodological approach to trend smoothing is critical for robust signal generation.   Adaptive ATR Trailing Stop: A key component is the Average True Range (ATR)-based trailing stop. ATR serves as a dynamic measure of market volatility. The strategy incorporates user-defined parameters (   Key Value and ATR Period) to calibrate the sensitivity of this trailing stop, enabling adaptation to varying market volatility regimes. This mechanism is designed to provide a dynamic exit point, preserving capital and locking in gains as a trend progresses. EMA Crossover for Signal Generation: Entry and exit signals are derived from the interaction between the Heikin Ashi derived price source and an Exponential Moving Average (EMA). A crossover event between these two components is utilized to objectively identify shifts in momentum, signaling potential long entry or exit points.   Rigorous Stop Loss Implementation: A critical feature for risk mitigation, the strategy includes an optional stop loss. This stop loss can be configured as a percentage or fixed point deviation from the entry price. Importantly, stop loss execution is based on real market prices, not the synthetic Heikin Ashi values. This design choice ensures that risk management is grounded in actual market liquidity and price levels, providing a more accurate representation of potential drawdowns during backtesting and live operation. Backtesting Protocol: The strategy is configured for realistic backtesting, employing fill_orders_on_standard_ohlc=true to simulate order execution at standard OHLC prices. A configurable Date Filter is included to define specific historical periods for performance evaluation. Data Visualization and Metrics: The script provides on-chart visual overlays for buy/sell signals, the ATR trailing stop, and the stop loss level. An integrated information table displays real-time strategy parameters, current position status, trend direction, and key price levels, facilitating immediate quantitative assessment. Applicability The Mutanabby_AI | ATR+ strategy is particularly suited for: Cryptocurrency Markets: The inherent volatility of assets such as #Bitcoin and #Ethereum makes the ATR-based trailing stop a relevant tool for dynamic risk management.   Systematic Trend Following: Individuals employing systematic methodologies for trend capture will find the objective signal generation and rule-based execution aligned with their approach. Pine Script Developers and Quants: The transparent code structure and emphasis on realistic backtesting provide a valuable framework for further analysis, modification, and integration into broader quantitative models. Automated Trading Systems: The clear, deterministic entry and exit conditions facilitate integration into automated trading environments. Implementation and Evaluation To evaluate the Mutanabby_AI | ATR+ strategy, apply the script to your chosen chart on TradingView. Adjust the input parameters (Key Value, ATR Period, Heikin Ashi Method, Stop Loss Settings) to observe performance across various asset classes and timeframes. Comprehensive backtesting is recommended to assess the strategy's historical performance characteristics, including profitability, drawdown, and risk-adjusted returns. I'd love to hear your thoughts, feedback, and any optimizations you discover! Drop a comment below, give it a like if you find it useful, and share your results.
Pine Script® stratejisi
Mutanabby_AI tarafından
The Barking Rat LiteMomentum & FVG Reversion Strategy The Barking Rat Lite is a disciplined, short-term mean-reversion strategy that combines RSI momentum filtering, EMA bands, and Fair Value Gap (FVG) detection to identify short-term reversal points. Designed for practical use on volatile markets, it focuses on precise entries and ATR-based take profit management to balance opportunity and risk. Core Concept This strategy seeks potential reversals when short-term price action shows exhaustion outside an EMA band, confirmed by momentum and FVG signals: EMA Bands: Parameters used: A 20-period EMA (fast) and 100-period EMA (slow). Why chosen: - The 20 EMA is sensitive to short-term moves and reflects immediate momentum. - The 100 EMA provides a slower, structural anchor. When price trades outside both bands, it often signals overextension relative to both short-term and medium-term trends. Application in strategy: - Long entries are only considered when price dips below both EMAs, identifying potential undervaluation. - Short entries are only considered when price rises above both EMAs, identifying potential overvaluation. This dual-band filter avoids counter-trend signals that would occur if only a single EMA was used, making entries more selective.. Fair Value Gap Detection (FVG): Parameters used: The script checks for dislocations using a 12-bar lookback (i.e. comparing current highs/lows with values 12 candles back). Why chosen: - A 12-bar displacement highlights significant inefficiencies in price structure while filtering out micro-gaps that appear every few bars in high-volatility markets. - By aligning FVG signals with candle direction (bullish = close > open, bearish = close < open), the strategy avoids random gaps and instead targets ones that suggest exhaustion. Application in strategy: - Bullish FVGs form when earlier lows sit above current highs, hinting at downward over-extension. - Bearish FVGs form when earlier highs sit below current lows, hinting at upward over-extension. This gives the strategy a structural filter beyond simple oscillators, ensuring signals have price-dislocation context. RSI Momentum Filter: Parameters used: 14-period RSI with thresholds of 80 (overbought) and 20 (oversold). Why chosen: - RSI(14) is a widely recognized momentum measure that balances responsiveness with stability. - The thresholds are intentionally extreme (80/20 vs. the more common 70/30), so the strategy only engages at genuine exhaustion points rather than frequent minor corrections. Application in strategy: - Longs trigger when RSI < 20, suggesting oversold exhaustion. - Shorts trigger when RSI > 80, suggesting overbought exhaustion. This ensures entries are not just technically valid but also backed by momentum extremes, raising conviction. ATR-Based Take Profit: Parameters used: 14-period ATR, with a default multiplier of 4. Why chosen: - ATR(14) reflects the prevailing volatility environment without reacting too much to outliers. - A multiplier of 4 is a pragmatic compromise: wide enough to let trades breathe in volatile conditions, but tight enough to enforce disciplined exits before mean reversion fades. Application in strategy: - At entry, a fixed target is set = Entry Price ± (ATR × 4). - This target scales automatically with volatility: narrower in calm periods, wider in explosive markets. By avoiding discretionary exits, the system maintains rule-based discipline. Visual Signals on Chart Blue “▲” below candle: Potential long entry Orange/Yellow “▼” above candle: Potential short entry Green “✔️”: Trade closed at ATR take profit Blue (20 EMA) & Orange (100 EMA) lines: Dynamic channel reference ⚙️Strategy report properties Position size: 25% equity per trade Initial capital: 10,000.00 USDT Pyramiding: 10 entries per direction Slippage: 2 ticks Commission: 0.055% per side Backtest timeframe: 1-minute Backtest instrument: HYPEUSDT Backtesting range: Jul 28, 2025 — Aug 17, 2025 Note on Sample Size: You’ll notice the report displays fewer than the ideal 100 trades in the strategy report above. This is intentional. The goal of the script is to isolate high-quality, short-term reversal opportunities while filtering out low-conviction setups. This means that the Barking Rat Lite strategy is very selective, filtering out over 90% of market noise. The brief timeframe shown in the strategy report here illustrates its filtering logic over a short window — not its full capabilities. As a result, even on lower timeframes like the 1-minute chart, signals are deliberately sparse — each one must pass all criteria before triggering. For a larger dataset: Once the strategy is applied to your chart, users are encouraged to expand the lookback range or apply the strategy to other volatile pairs to view a full sample. 💡Why 25% Equity Per Trade? While it's always best to size positions based on personal risk tolerance, we defaulted to 25% equity per trade in the backtesting data — and here’s why: Backtests using this sizing show manageable drawdowns even under volatile periods. The strategy generates a sizeable number of trades, reducing reliance on a single outcome. Combined with conservative filters, the 25% setting offers a balance between aggression and control. Users are strongly encouraged to customize this to suit their risk profile. What makes Barking Rat Lite valuable Combines multiple layers of confirmation: EMA bands + FVG + RSI Adaptive to volatility: ATR-based exits scale with market conditions Clear, actionable visuals: Easy to monitor and manage trades
Pine Script® stratejisi
TheBarkingRat tarafından
4
Globex Overnight Futures ORB with FIB's by TenAMTrader📌 Globex Overnight Futures ORB with FIB’s – by TenAMTrader This indicator is designed for futures traders who want to track the Globex Overnight Opening Range (ORB) and apply Fibonacci projections to anticipate potential support/resistance zones. It’s especially useful for traders who follow overnight sessions (such as ES, NQ, CL) and want to map out key levels before the U.S. regular session begins. ⚙️ How It Works Primary Range (ORB): You define a start and end time (default set to 18:00 – 18:15 EST). During this period, the script tracks the session high, low, and midpoint. Opening Range Plots: High Line (green) Low Line (red) Midpoint Line (yellow) A shaded cloud between High–Mid and Mid–Low for easy visualization. Fibonacci Projections: Once the ORB is complete, the script calculates a full suite of Fibonacci retracements and extensions (e.g., 0.236, 0.382, 0.618, 1.0, 1.618, 2.0). Standard key levels (0.618, 0.786, 1.0, etc.) are always shown if enabled. Optional extended levels (1.236, 1.382, 1.5, 2.0, etc.) can be toggled on/off. "Between Range" fibs (such as 0.382 and 0.618 inside the ORB) are also available for traders who like intra-range precision. 🔧 User Settings Time Inputs: Choose your ORB start/end time. Color Controls: Customize high, low, midpoint, and fib line colors. Display Toggles: Turn on/off High, Low, Midpoint lines and Fibonacci projections. Fib Extensions Toggle: Decide whether to show only major fibs or all extensions. Alerts (Optional): Alerts can be set for crossing the ORB High, Low, or Midpoint. 📊 Practical Use Cases Breakout Traders: Use the ORB high/low as breakout triggers. Mean Reversion Traders: Watch for rejections near fib extension levels. Overnight Futures Monitoring: Track Globex behavior to prepare for RTH open. Risk Management: ORB and Fib levels make for natural stop/target placement zones. ⚠️ Disclaimer This indicator is provided for educational and informational purposes only. It does not constitute financial advice, investment advice, or trading recommendations. Trading futures involves substantial risk of loss and may not be suitable for all investors. Always do your own due diligence and consult with a licensed financial professional before making trading decisions.
Pine Script® göstergesi
TenAM_Trader tarafından
Volume Spike Detector - by TenAMTrader📌 Volume Spike Detector – by TenAMTrader This indicator is designed to help traders quickly identify unusual surges in trading volume relative to recent activity. High-volume spikes can often signal strong buying or selling pressure, potential trend reversals, or breakout setups. ⚙️ How It Works The script calculates the average trading volume over a user-defined period (default: 21 bars). It then sets a spike threshold, which is that average volume plus a percentage buffer (default: 25%). Whenever the current bar’s volume exceeds this threshold, a 💰 label is plotted below the candle. If alerts are enabled, you’ll also receive a real-time alert whenever a spike occurs. 🔧 User Settings Spike Ratio % → Adjust how much higher than average volume must be to qualify as a spike. Trading Period → Set the lookback period used to calculate the average volume. Enable Alert → Turn alerts on/off. 📊 Practical Use Cases Breakout Trading: Volume spikes often confirm breakouts from consolidation zones. Reversal Signals: A sudden surge in volume may precede a trend reversal. News & Events: Spot unusual activity during earnings, economic releases, or unexpected events. ⚠️ Disclaimer This indicator is provided for educational and informational purposes only. It does not constitute financial advice, investment advice, or trading recommendations. Past performance is not indicative of future results. Always do your own research and consult with a licensed financial professional before making any trading decisions.
Pine Script® göstergesi
TenAM_Trader tarafından
Bollinger Bands % | QuantEdgeB📊 Introducing Bollinger Bands % (BB%) by QuantEdgeB 🛠️ Overview BB% | QuantEdgeB is a volatility-aware momentum tool that maps price within a Bollinger envelope onto a normalized scale. By letting you choose the base moving average (SMA, EMA, DEMA, TEMA, HMA, ALMA, EHMA, THMA, RMA, WMA, VWMA, T3, LSMA) and even Heikin-Ashi sources, it adapts to your style while keeping readings consistent across symbols and timeframes. Clear thresholds and color-coded visuals make it easy to spot emerging strength, fading moves, and potential mean-reversions. ✨ Key Features • 🔹 Flexible Baseline Pick from 12 MA types (plus Heikin-Ashi source option) to tailor responsiveness and smoothness. • 🔹 Normalized Positioning Price is expressed as a percentage of the band range, yielding an intuitive 0–100 style read (can exceed in extreme trends). • 🔹 Actionable Thresholds Default Long 55 / Short 45 levels provide simple, objective triggers. • 🔹 Visual Clarity Color-coded candles, shaded OB/OS zones, and adaptive color themes speed up decision-making. • 🔹 Ready-to-Alert Built-in alerts for long/short transitions. 📐 How It Works 1️⃣ Band Construction A moving average (your choice) defines the midline; volatility (standard deviation) builds upper/lower bands. 2️⃣ Normalization The indicator measures where price sits between the lower and upper band, scaling that into a bounded oscillator (BB%). 3️⃣ Signal Logic • ✅ Long when BB% rises above 55 (strength toward the top of the envelope). • ❌ Short when BB% falls below 45 (weakness toward the bottom). 4️⃣ OB/OS Context Shaded regions above/below typical ranges highlight exhaustion and potential snap-backs. ⚙️ Custom Settings • Base MA Type: SMA, EMA, DEMA, TEMA, HMA, ALMA, EHMA, THMA, RMA, WMA, VWMA, T3, LSMA • Source Mode: Classic price or Heikin-Ashi (close/open/high/hlc3) • Base Length: default 40 • Band Width: standard deviation-based (2× SD by default) • Long / Short Thresholds: defaults 55 / 45 • Color Mode: Alpha, MultiEdge, TradingSuite, Premium, Fundamental, Classic, Warm, Cold, Strategy • Candles & Labels: optional candle coloring and signal markers 👥 Ideal For ✅ Trend Followers — Ride strength as price compresses near the upper band. ✅ Swing/Mean-Reversion Traders — Fade extremes when BB% stretches into OB/OS zones. ✅ Multi-Timeframe Analysts — Compare band position consistently across periods. ✅ System Builders — Use BB% as a normalized feature for strategies and filters. 📌 Conclusion BB% | QuantEdgeB delivers a clean, normalized read of price versus its volatility envelope—adaptable via rich MA/source options and easy to automate with thresholds and alerts. 🔹 Key Takeaways: 1️⃣ Normalized view of price inside the volatility bands 2️⃣ Flexible baseline (12+ MA choices) and Heikin-Ashi support 3️⃣ Straightforward 55/45 triggers with clear visual context 📌 Disclaimer: Past performance is not indicative of future results. No strategy guarantees success. 📌 Strategic Advice: Always backtest, tune parameters, and align with your risk profile before live trading.
Pine Script® göstergesi
QuantEdgeB tarafından
Monthly Expected Move (IV + Realized)What it does Overlays 1-month expected move bands on price using both forward-looking options data and backward-looking realized movement: IV30 band — from your pasted 30-day implied vol (%) Straddle band — from your pasted ATM ~30-DTE call+put total HV band — from Historical Volatility computed on-chart ATR band — from ATR% extrapolated to ~1 trading month Use it to quickly answer: “How much could this stock move in ~1 month?” and “Is the market now pricing more/less movement than we’ve actually been getting?” Inputs (quick) Implied (forward-looking) Use IV30 (%) — paste annualized IV30 from your options platform. Use ATM 30-DTE Straddle — paste Call+Put total (per share) at the ATM strike, ~30 DTE. Realized (backward-looking) HV lookback (days) — default 21 (≈1 trading month). ATR length — default 14. Note: TradingView can’t fetch option data automatically. Paste the IV30 % or the straddle total you read from your broker (use Mark/mid prices). How it’s calculated IV band (±%) = IV30 × √(21/252) (annualized → ~1-month). Straddle band (±%) = (ATM Call + Put) / Spot to that expiry (≈30 DTE). HV band (±%) = stdev(log returns, N) × √252 × √(21/252). ATR band (±%) = (ATR(len)/Close) × √21. All bands are plotted as upper/lower envelopes around price, plus an on-chart readout of each ±% for quick scanning. How to use it (at a glance) IV/Straddle bands wider than HV/ATR → market expects bigger movement than recent actuals (possible catalyst/expansion). All bands narrow → likely a low-mover; look elsewhere if you want action. HV > IV → realized swings exceed current pricing (mean-reversion or vol bleed often follows). Pro tips For ATM straddle: pick the expiry closest to ~30 DTE, use the ATM strike (closest to spot), and add Call Mark + Put Mark (per share). If the exact ATM strike isn’t quoted, average the two neighboring strikes. The simple straddle/spot heuristic can read slightly below the IV-derived 1σ; that’s normal. Keep the chart on daily timeframe—the math assumes trading-day conventions (~252/yr, ~21/mo).
Pine Script® göstergesi
rixman14 tarafından
Volume Profile Grid [Alpha Extract]A sophisticated volume distribution analysis system that transforms market activity into institutional-grade visual profiles, revealing hidden support/resistance zones and market participant behavior. Utilizing advanced price level segmentation, bullish/bearish volume separation, and dynamic range analysis, the Volume Profile Grid delivers comprehensive market structure insights with Point of Control (POC) identification, Value Area boundaries, and volume delta analysis. The system features intelligent visualization modes, real-time sentiment analysis, and flexible range selection to provide traders with clear, actionable volume-based market context. 🔶 Dynamic Range Analysis Engine Implements dual-mode range selection with visible chart analysis and fixed period lookback, automatically adjusting to current market view or analyzing specified historical periods. The system intelligently calculates optimal bar counts while maintaining performance through configurable maximum limits, ensuring responsive profile generation across all timeframes with institutional-grade precision. // Dynamic period calculation with intelligent caching get_analysis_period() => if i_use_visible_range chart_start_time = chart.left_visible_bar_time current_time = last_bar_time time_span = current_time - chart_start_time tf_seconds = timeframe.in_seconds() estimated_bars = time_span / (tf_seconds * 1000) range_bars = math.floor(estimated_bars) final_bars = math.min(range_bars, i_max_visible_bars) math.max(final_bars, 50) // Minimum threshold else math.max(i_periods, 50) 🔶 Advanced Bull/Bear Volume Separation Employs sophisticated candle classification algorithms to separate bullish and bearish volume at each price level, with weighted distribution based on bar intersection ratios. The system analyzes open/close relationships to determine volume direction, applying proportional allocation for doji patterns and ensuring accurate representation of buying versus selling pressure across the entire price spectrum. 🔶 Multi-Mode Volume Visualization Features three distinct display modes for bull/bear volume representation: Split mode creates mirrored profiles from a central axis, Side by Side mode displays sequential bull/bear segments, and Stacked mode separates volumes vertically. Each mode offers unique insights into market participant behavior with customizable width, thickness, and color parameters for optimal visual clarity. // Bull/Bear volume calculation with weighted distribution for bar_offset = 0 to actual_periods - 1 bar_high = high bar_low = low bar_volume = volume // Calculate intersection weight weight = math.min(bar_high, next_level) - math.max(bar_low, current_level) weight := weight / (bar_high - bar_low) weighted_volume = bar_volume * weight // Classify volume direction if bar_close > bar_open level_bull_volume += weighted_volume else if bar_close < bar_open level_bear_volume += weighted_volume else // Doji handling level_bull_volume += weighted_volume * 0.5 level_bear_volume += weighted_volume * 0.5 🔶 Point of Control & Value Area Detection Implements institutional-standard POC identification by locating the price level with maximum volume accumulation, providing critical support/resistance zones. The Value Area calculation uses sophisticated sorting algorithms to identify the price range containing 70% of trading volume, revealing the market's accepted value zone where institutional participants concentrate their activity. 🔶 Volume Delta Analysis System Incorporates real-time volume delta calculation with configurable dominance thresholds to identify significant bull/bear imbalances. The system visually highlights price levels where buying or selling pressure exceeds threshold percentages, providing immediate insight into directional volume flow and potential reversal zones through color-coded delta indicators. // Value Area calculation using 70% volume accumulation total_volume_sum = array.sum(total_volumes) target_volume = total_volume_sum * 0.70 // Sort volumes to find highest activity zones for i = 0 to array.size(sorted_volumes) - 2 for j = i + 1 to array.size(sorted_volumes) - 1 if array.get(sorted_volumes, j) > array.get(sorted_volumes, i) // Swap and track indices for value area boundaries // Accumulate until 70% threshold reached for i = 0 to array.size(sorted_indices) - 1 accumulated_volume += vol array.push(va_levels, array.get(volume_levels, idx)) if accumulated_volume >= target_volume break ❓How It Works 🔶 Weighted Volume Distribution Implements proportional volume allocation based on the percentage of each bar that intersects with price levels. When a bar spans multiple levels, volume is distributed proportionally based on the intersection ratio, ensuring precise representation of trading activity across the entire price spectrum without double-counting or volume loss. 🔶 Real-Time Profile Generation Profiles regenerate on each bar close when in visible range mode, automatically adapting to chart zoom and scroll actions. The system maintains optimal performance through intelligent caching mechanisms and selective line updates, ensuring smooth operation even with maximum resolution settings and extended analysis periods. 🔶 Market Sentiment Analysis Features comprehensive volume analysis table displaying total volume metrics, bullish/bearish percentages, and overall market sentiment classification. The system calculates volume dominance ratios in real-time, providing immediate insight into whether buyers or sellers control the current price structure with percentage-based sentiment thresholds. 🔶 Visual Profile Mapping Provides multi-layered visual feedback through colored volume bars, POC line highlighting, Value Area boundaries, and optional delta indicators. The system supports profile mirroring for alternative perspectives, line extension for future reference, and customizable label positioning with detailed price information at critical levels. Why Choose Volume Profile Grid The Volume Profile Grid represents the evolution of volume analysis tools, combining traditional volume profile concepts with modern visualization techniques and intelligent analysis algorithms. By integrating dynamic range selection, sophisticated bull/bear separation, and multi-mode visualization with POC/Value Area detection, it provides traders with institutional-quality market structure analysis that adapts to any trading style. The comprehensive delta analysis and sentiment monitoring system eliminates guesswork while the flexible visualization options ensure optimal clarity across all market conditions, making it an essential tool for traders seeking to understand true market dynamics through volume-based price discovery.
Pine Script® göstergesi
AlphaExtract tarafından
2
VIX > 20/25 HighlightThis indicator tracks the CBOE Volatility Index (VIX) and highlights when volatility exceeds critical thresholds. Plots the VIX with dashed reference lines at 20 and 25. Background turns orange when the VIX is above 20. Background turns bright red when the VIX is above 25. Includes alert conditions to notify you when the VIX crosses above 20 or 25. Use this tool to quickly visualize periods of elevated market stress and manage risk accordingly.
Pine Script® göstergesi
cfbagnoud tarafından
Candle Body Size AlertThis indicator monitors the body size of each candle (close minus open, ignoring wicks) and compares it to a user-defined threshold measured in ticks. If the candle body exceeds the threshold, the indicator triggers an alert condition at the close of the candle. Features: 1. Adjustable threshold in ticks (default: 4000) 2. Adjustable timeframe (or use chart timeframe) 3. Alerts only at candle close (no intrabar signals) Use Case: Designed for traders who want to be notified when unusually large candles form, helping to identify strong momentum moves or volatility spikes.
Pine Script® göstergesi
ibrahiimH tarafından
Calm before the StormCalm before the Storm - Bollinger Bands Volatility Indicator What It Does This indicator identifies and highlights periods of extremely low market volatility by analyzing Bollinger Bands distance. It uses percentile-based analysis to find the "quietest" market periods and highlights them with a gradient background, operating on the premise that low volatility periods often precede significant price movements. How It Works Volatility Measurement: Calculates the distance between Bollinger Bands upper and lower boundaries Percentile Analysis: Analyzes the lowest X% of volatility periods over a configurable lookback period (default: lowest 40% over 200 bars) Visual Highlighting: Uses gradient opacity to show volatility levels - the lower the volatility, the more opaque the background highlighting Adaptive Threshold: Automatically calculates what constitutes "low volatility" based on recent market conditions Who Should Use It Primary Users: Breakout Traders: Looking for consolidation periods that may precede significant moves Options Traders: Seeking low implied volatility periods before volatility expansion Swing Traders: Identifying accumulation/distribution phases before trend continuation or reversal Range Traders: Spotting tight trading ranges for mean reversion strategies Trading Styles: Volatility-based strategies Breakout and momentum trading Options strategies (volatility plays) Market timing approaches When to Use It Market Conditions: Consolidation Phases: When price is moving sideways with decreasing volatility Pre-Announcement Periods: Before earnings, economic data, or major events Market Transitions: During shifts between trending and ranging markets Low Volume Periods: When institutional participation is reduced Strategic Applications: Entry Timing: Wait for volatility compression before positioning for breakouts Risk Management: Reduce position sizes during highlighted periods (anticipating volatility expansion) Options Strategy: Sell premium during low volatility, buy during expansion Multi-Timeframe Analysis: Combine with higher timeframe trends for confluence Key Benefits Objective Volatility Measurement: Removes subjectivity from identifying "quiet" markets Adaptive Analysis: Automatically adjusts to current market conditions Visual Clarity: Easy-to-interpret gradient highlighting Customizable Sensitivity: Adjustable percentile thresholds for different trading styles Best Used In Combination With: Trend analysis tools Support/resistance levels Volume indicators Momentum oscillators This indicator is particularly valuable for traders who understand that periods of low volatility are often followed by periods of high volatility, allowing them to position ahead of potential significant price movements.
Pine Script® göstergesi
naikamit8 tarafından