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Ehlers Autocorrelation Periodogram (EACP)# EACP: Ehlers Autocorrelation Periodogram ## Overview and Purpose Developed by John F. Ehlers (Technical Analysis of Stocks & Commodities, Sep 2016), the Ehlers Autocorrelation Periodogram (EACP) estimates the dominant market cycle by projecting normalized autocorrelation coefficients onto Fourier basis functions. The indicator blends a roofing filter (high-pass + Super Smoother) with a compact periodogram, yielding low-latency dominant cycle detection suitable for adaptive trading systems. Compared with Hilbert-based methods, the autocorrelation approach resists aliasing and maintains stability in noisy price data. EACP answers a central question in cycle analysis: “What period currently dominates the market?” It prioritizes spectral power concentration, enabling downstream tools (adaptive moving averages, oscillators) to adjust responsively without the lag present in sliding-window techniques. ## Core Concepts * **Roofing Filter:** High-pass plus Super Smoother combination removes low-frequency drift while limiting aliasing. * **Pearson Autocorrelation:** Computes normalized lag correlation to remove amplitude bias. * **Fourier Projection:** Sums cosine and sine terms of autocorrelation to approximate spectral energy. * **Gain Normalization:** Automatic gain control prevents stale peaks from dominating power estimates. * **Warmup Compensation:** Exponential correction guarantees valid output from the very first bar. ## Implementation Notes **This is not a strict implementation of the TASC September 2016 specification.** It is a more advanced evolution combining the core 2016 concept with techniques Ehlers introduced later. The fundamental Wiener-Khinchin theorem (power spectral density = Fourier transform of autocorrelation) is correctly implemented, but key implementation details differ: ### Differences from Original 2016 TASC Article 1. **Dominant Cycle Calculation:** - **2016 TASC:** Uses peak-finding to identify the period with maximum power - **This Implementation:** Uses Center of Gravity (COG) weighted average over bins where power ≥ 0.5 - **Rationale:** COG provides smoother transitions and reduces susceptibility to noise spikes 2. **Roofing Filter:** - **2016 TASC:** Simple first-order high-pass filter - **This Implementation:** Canonical 2-pole high-pass with √2 factor followed by Super Smoother bandpass - **Formula:** `hp := (1-α/2)²·(p-2p +p ) + 2(1-α)·hp - (1-α)²·hp ` - **Rationale:** Evolved filtering provides better attenuation and phase characteristics 3. **Normalized Power Reporting:** - **2016 TASC:** Reports peak power across all periods - **This Implementation:** Reports power specifically at the dominant period - **Rationale:** Provides more meaningful correlation between dominant cycle strength and normalized power 4. **Automatic Gain Control (AGC):** - Uses decay factor `K = 10^(-0.15/diff)` where `diff = maxPeriod - minPeriod` - Ensures K < 1 for proper exponential decay of historical peaks - Prevents stale peaks from dominating current power estimates ### Performance Characteristics - **Complexity:** O(N²) where N = (maxPeriod - minPeriod) - **Implementation:** Uses `var` arrays with native PineScript historical operator ` ` - **Warmup:** Exponential compensation (§2 pattern) ensures valid output from bar 1 ### Related Implementations This refined approach aligns with: - TradingView TASC 2025.02 implementation by blackcat1402 - Modern Ehlers cycle analysis techniques post-2016 - Evolved filtering methods from *Cycle Analytics for Traders* The code is mathematically sound and production-ready, representing a refined version of the autocorrelation periodogram concept rather than a literal translation of the 2016 article. ## Common Settings and Parameters | Parameter | Default | Function | When to Adjust | |-----------|---------|----------|---------------| | Min Period | 8 | Lower bound of candidate cycles | Increase to ignore microstructure noise; decrease for scalping. | | Max Period | 48 | Upper bound of candidate cycles | Increase for swing analysis; decrease for intraday focus. | | Autocorrelation Length | 3 | Averaging window for Pearson correlation | Set to 0 to match lag, or enlarge for smoother spectra. | | Enhance Resolution | true | Cubic emphasis to highlight peaks | Disable when a flatter spectrum is desired for diagnostics. | **Pro Tip:** Keep `(maxPeriod - minPeriod)` ≤ 64 to control $O(n^2)$ inner loops and maintain responsiveness on lower timeframes. ## Calculation and Mathematical Foundation **Explanation:** 1. Apply roofing filter to `source` using coefficients $\alpha_1$, $a_1$, $b_1$, $c_1$, $c_2$, $c_3$. 2. For each lag $L$ compute Pearson correlation $r_L$ over window $M$ (default $L$). 3. For each period $p$, project onto Fourier basis: $C_p=\sum_{n=2}^{N} r_n \cos\left(\frac{2\pi n}{p}\right)$ and $S_p=\sum_{n=2}^{N} r_n \sin\left(\frac{2\pi n}{p}\right)$. 4. Power $P_p=C_p^2+S_p^2$, smoothed then normalized via adaptive peak tracking. 5. Dominant cycle $D=\frac{\sum p\,\tilde P_p}{\sum \tilde P_p}$ over bins where $\tilde P_p≥0.5$, warmup-compensated. **Technical formula:** ``` Step 1: hp_t = ((1-α₁)/2)(src_t - src_{t-1}) + α₁ hp_{t-1} Step 2: filt_t = c₁(hp_t + hp_{t-1})/2 + c₂ filt_{t-1} + c₃ filt_{t-2} Step 3: r_L = (M Σxy - Σx Σy) / √ Step 4: P_p = (Σ_{n=2}^{N} r_n cos(2πn/p))² + (Σ_{n=2}^{N} r_n sin(2πn/p))² Step 5: D = Σ_{p∈Ω} p · ĤP_p / Σ_{p∈Ω} ĤP_p with warmup compensation ``` > 🔍 **Technical Note:** Warmup uses $c = 1 / (1 - (1 - \alpha)^{k})$ to scale early-cycle estimates, preventing low values during initial bars. ## Interpretation Details - **Primary Dominant Cycle:** - High $D$ (e.g., > 30) implies slow regime; adaptive MAs should lengthen. - Low $D$ (e.g., < 15) signals rapid oscillations; shorten lookback windows. - **Normalized Power:** - Values > 0.8 indicate strong cycle confidence; consider cyclical strategies. - Values < 0.3 warn of flat spectra; favor trend or volatility approaches. - **Regime Shifts:** - Rapid drop in $D$ alongside rising power often precedes volatility expansion. - Divergence between $D$ and price swings may highlight upcoming breakouts. ## Limitations and Considerations - **Spectral Leakage:** Limited lag range can smear peaks during abrupt volatility shifts. - **O(n²) Segment:** Although constrained (≤ 60 loops), wide period spans increase computation. - **Stationarity Assumption:** Autocorrelation presumes quasi-stationary cycles; regime changes reduce accuracy. - **Latency in Noise:** Even with roofing, extremely noisy assets may require higher `avgLength`. - **Downtrend Bias:** Negative trends may clip high-pass output; ensure preprocessing retains signal. ## References * Ehlers, J. F. (2016). “Past Market Cycles.” *Technical Analysis of Stocks & Commodities*, 34(9), 52-55. * Thinkorswim Learning Center. “Ehlers Autocorrelation Periodogram.” * Fab MacCallini. “autocorrPeriodogram.R.” GitHub repository. * QuantStrat TradeR Blog. “Autocorrelation Periodogram for Adaptive Lookbacks.” * TradingView Script by blackcat1402. “Ehlers Autocorrelation Periodogram (Updated).”
Pine Script®指標
由mihakralj提供
Dynamic Market Structure (MTF) - Dow TheoryDynamic Market Structure (MTF) OVERVIEW This advanced indicator provides a comprehensive and fully customizable solution for analyzing market structure based on classic Dow Theory principles. It automates the identification of key structural points, including Higher Highs (HH), Higher Lows (HL), Lower Lows (LL), and Lower Highs (LH). Going beyond simple pivot detection, this tool visualizes the flow of the trend by plotting dynamic Breaks of Structure (BOS) and potential reversals with Changes of Character (CHoCH). It is designed to be a flexible and powerful tool for traders who use price action and trend analysis as a core part of their strategy. CORE CONCEPTS The indicator is built on the foundational principles of Dow Theory: Uptrend: A series of Higher Highs and Higher Lows. Downtrend: A series of Lower Lows and Lower Highs. Break of Structure (BOS): Occurs when price action continues the current trend by creating a new HH in an uptrend or a new LL in a downtrend. Change of Character (CHoCH): Occurs when the established trend sequence is broken, signaling a potential reversal. For example, when a Lower Low forms after a series of Higher Highs. CALCULATION METHODOLOGY This section explains the indicator's underlying logic: Pivot Detection: The indicator's core logic is based on TradingView's built-in ta.pivothigh() and ta.pivotlow() functions. The sensitivity of this detection is fully controlled by the user via the Pivot Lookback Left and Pivot Lookback Right settings. Structure Calculation (BOS/CHoCH): The script identifies market structure by analyzing the sequence of these confirmed pivots. A bullish BOS is plotted when a new ta.pivothigh is confirmed at a price higher than the previous confirmed ta.pivothigh. A bearish CHoCH is plotted when a new ta.pivotlow is confirmed at a price lower than the previous confirmed ta.pivotlow , breaking the established sequence of higher lows. The logic is mirrored for bearish BOS and bullish CHoCH. Invalidation Levels: This feature identifies the last confirmed pivot before a structure break (e.g., the last ta.pivotlow before a bullish BOS) and plots a dotted line from it to the breakout bar. This level is considered the structural invalidation point for that move. MTF Confirmation: This unique feature provides confluence by analyzing a second, lower timeframe. When a pivot (e.g., a Higher Low) is confirmed on the main chart, the script requests pivot data from the user-selected lower timeframe. If a corresponding trend reversal is detected on that lower timeframe (e.g., a break of its own minor downtrend), the pivot is labeled "Firm" (FHL); otherwise, it is labeled "Soft" (SHL). KEY FEATURES This indicator is packed with advanced features designed to provide a deeper level of market insight: Dynamic Structure Lines: BOS and CHoCH levels are plotted with clean, dashed lines that dynamically start at the old pivot and terminate precisely at the breakout bar, keeping the chart clean and precise. Invalidation Levels: For every structure break, the indicator can plot a dotted "Invalidation" line (INV). This marks the critical support or resistance pivot that, if broken, would negate the previous move, providing a clear reference for risk management. Multi-Timeframe (MTF) Confirmation: Add a layer of confluence to your analysis by confirming pivots on a lower timeframe. The indicator can label Higher Lows and Lower Highs as either "Firm" (FHL/FLH) if confirmed by a reversal on a lower timeframe, or "Soft" (SHL/SLH) if not. Flexible Pivot Detection: Fully adjustable Pivot Lookback settings for the left and right sides allow you to tune the indicator's sensitivity to match any timeframe or trading style, from long-term investing to short-term scalping. Full Customization: Take complete control of the indicator's appearance. A dedicated style menu allows you to customize the colors for all bullish, bearish, and reversal elements, including the transparency of the trend-based candle coloring. HOW TO USE Trend Identification: Use the sequence of HH/HL and LL/LH, along with the trend-colored candles, to quickly assess the current market direction on any timeframe. Entry Signals: A confirmed BOS can signal a potential entry in the direction of the trend. A CHoCH can signal a potential reversal, offering an opportunity to enter a new trend early. Risk Management: Use the automatically plotted "Invalidation" (INV) lines as a logical reference point for placing stop losses. A break of this level indicates that the structure you were trading has failed. Confluence: Use the "Firm" pivot signals from the MTF analysis to identify high-probability swing points that are supported by price action on multiple timeframes. SETTINGS BREAKDOWN Pivot Lookback Left/Right: Controls the sensitivity of pivot detection. Higher numbers find more significant (but fewer) pivots. MTF Confirmation: Enable/disable the "Firm" vs. "Soft" pivot analysis and select your preferred lower timeframe for confirmation. Style Settings: Customize all colors and the transparency of the candle coloring to match your chart's theme. Show Invalidation Levels: Toggle the visibility of the dotted invalidation lines. This indicator is a powerful tool for visualizing and trading with the trend. Experiment with the settings to find a configuration that best fits your personal trading strategy.
Pine Script®指標
由Leree123提供
3
Historical Matrix Analyzer [PhenLabs]📊Historical Matrix Analyzer Version: PineScriptv6 📌Description The Historical Matrix Analyzer is an advanced probabilistic trading tool that transforms technical analysis into a data-driven decision support system. By creating a comprehensive 56-cell matrix that tracks every combination of RSI states and multi-indicator conditions, this indicator reveals which market patterns have historically led to profitable outcomes and which have not. At its core, the indicator continuously monitors seven distinct RSI states (ranging from Extreme Oversold to Extreme Overbought) and eight unique indicator combinations (MACD direction, volume levels, and price momentum). For each of these 56 possible market states, the system calculates average forward returns, win rates, and occurrence counts based on your configurable lookback period. The result is a color-coded probability matrix that shows you exactly where you stand in the historical performance landscape. The standout feature is the Current State Panel, which provides instant clarity on your active market conditions. This panel displays signal strength classifications (from Strong Bullish to Strong Bearish), the average return percentage for similar past occurrences, an estimated win rate using Bayesian smoothing to prevent small-sample distortions, and a confidence level indicator that warns you when insufficient data exists for reliable conclusions. 🚀Points of Innovation Multi-dimensional state classification combining 7 RSI levels with 8 indicator combinations for 56 unique trackable market conditions Bayesian win rate estimation with adjustable smoothing strength to provide stable probability estimates even with limited historical samples Real-time active cell highlighting with “NOW” marker that visually connects current market conditions to their historical performance data Configurable color intensity sensitivity allowing traders to adjust heat-map responsiveness from conservative to aggressive visual feedback Dual-panel display system separating the comprehensive statistics matrix from an easy-to-read current state summary panel Intelligent confidence scoring that automatically warns traders when occurrence counts fall below reliable thresholds 🔧Core Components RSI State Classification: Segments RSI readings into 7 distinct zones (Extreme Oversold <20, Oversold 20-30, Weak 30-40, Neutral 40-60, Strong 60-70, Overbought 70-80, Extreme Overbought >80) to capture momentum extremes and transitions Multi-Indicator Condition Tracking: Simultaneously monitors MACD crossover status (bullish/bearish), volume relative to moving average (high/low), and price direction (rising/falling) creating 8 binary-encoded combinations Historical Data Storage Arrays: Maintains rolling lookback windows storing RSI states, indicator states, prices, and bar indices for precise forward-return calculations Forward Performance Calculator: Measures price changes over configurable forward bar periods (1-20 bars) from each historical state, accumulating total returns and win counts per matrix cell Bayesian Smoothing Engine: Applies statistical prior assumptions (default 50% win rate) weighted by user-defined strength parameter to stabilize estimated win rates when sample sizes are small Dynamic Color Mapping System: Converts average returns into color-coded heat map with intensity adjusted by sensitivity parameter and transparency modified by confidence levels 🔥Key Features 56-Cell Probability Matrix: Comprehensive grid displaying every possible combination of RSI state and indicator condition, with each cell showing average return percentage, estimated win rate, and occurrence count for complete statistical visibility Current State Info Panel: Dedicated display showing your exact position in the matrix with signal strength emoji indicators, numerical statistics, and color-coded confidence warnings for immediate situational awareness Customizable Lookback Period: Adjustable historical window from 50 to 500 bars allowing traders to focus on recent market behavior or capture longer-term pattern stability across different market cycles Configurable Forward Performance Window: Select target holding periods from 1 to 20 bars ahead to align probability calculations with your trading timeframe, whether day trading or swing trading Visual Heat Mapping: Color-coded cells transition from red (bearish historical performance) through gray (neutral) to green (bullish performance) with intensity reflecting statistical significance and occurrence frequency Intelligent Data Filtering: Minimum occurrence threshold (1-10) removes unreliable patterns with insufficient historical samples, displaying gray warning colors for low-confidence cells Flexible Layout Options: Independent positioning of statistics matrix and info panel to any screen corner, accommodating different chart layouts and personal preferences Tooltip Details: Hover over any matrix cell to see full RSI label, complete indicator status description, precise average return, estimated win rate, and total occurrence count 🎨Visualization Statistics Matrix Table: A 9-column by 8-row grid with RSI states labeling vertical axis and indicator combinations on horizontal axis, using compact abbreviations (XOverS, OverB, MACD↑, Vol↓, P↑) for space efficiency Active Cell Indicator: The current market state cell displays “⦿ NOW ⦿” in yellow text with enhanced color saturation to immediately draw attention to relevant historical performance Signal Strength Visualization: Info panel uses emoji indicators (🔥 Strong Bullish, ✅ Bullish, ↗️ Weak Bullish, ➖ Neutral, ↘️ Weak Bearish, ⛔ Bearish, ❄️ Strong Bearish, ⚠️ Insufficient Data) for rapid interpretation Histogram Plot: Below the price chart, a green/red histogram displays the current cell’s average return percentage, providing a time-series view of how historical performance changes as market conditions evolve Color Intensity Scaling: Cell background transparency and saturation dynamically adjust based on both the magnitude of average returns and the occurrence count, ensuring visual emphasis on reliable patterns Confidence Level Display: Info panel bottom row shows “High Confidence” (green), “Medium Confidence” (orange), or “Low Confidence” (red) based on occurrence counts relative to minimum threshold multipliers 📖Usage Guidelines RSI Period Default: 14 Range: 1 to unlimited Description: Controls the lookback period for RSI momentum calculation. Standard 14-period provides widely-recognized overbought/oversold levels. Decrease for faster, more sensitive RSI reactions suitable for scalping. Increase (21, 28) for smoother, longer-term momentum assessment in swing trading. Changes affect how quickly the indicator moves between the 7 RSI state classifications. MACD Fast Length Default: 12 Range: 1 to unlimited Description: Sets the faster exponential moving average for MACD calculation. Standard 12-period setting works well for daily charts and captures short-term momentum shifts. Decreasing creates more responsive MACD crossovers but increases false signals. Increasing smooths out noise but delays signal generation, affecting the bullish/bearish indicator state classification. MACD Slow Length Default: 26 Range: 1 to unlimited Description: Defines the slower exponential moving average for MACD calculation. Traditional 26-period setting balances trend identification with responsiveness. Must be greater than Fast Length. Wider spread between fast and slow increases MACD sensitivity to trend changes, impacting the frequency of indicator state transitions in the matrix. MACD Signal Length Default: 9 Range: 1 to unlimited Description: Smoothing period for the MACD signal line that triggers bullish/bearish state changes. Standard 9-period provides reliable crossover signals. Shorter values create more frequent state changes and earlier signals but with more whipsaws. Longer values produce more confirmed, stable signals but with increased lag in detecting momentum shifts. Volume MA Period Default: 20 Range: 1 to unlimited Description: Lookback period for volume moving average used to classify volume as “high” or “low” in indicator state combinations. 20-period default captures typical monthly trading patterns. Shorter periods (10-15) make volume classification more reactive to recent spikes. Longer periods (30-50) require more sustained volume changes to trigger state classification shifts. Statistics Lookback Period Default: 200 Range: 50 to 500 Description: Number of historical bars used to calculate matrix statistics. 200 bars provides substantial data for reliable patterns while remaining responsive to regime changes. Lower values (50-100) emphasize recent market behavior and adapt quickly but may produce volatile statistics. Higher values (300-500) capture long-term patterns with stable statistics but slower adaptation to changing market dynamics. Forward Performance Bars Default: 5 Range: 1 to 20 Description: Number of bars ahead used to calculate forward returns from each historical state occurrence. 5-bar default suits intraday to short-term swing trading (5 hours on hourly charts, 1 week on daily charts). Lower values (1-3) target short-term momentum trades. Higher values (10-20) align with position trading and longer-term pattern exploitation. Color Intensity Sensitivity Default: 2.0 Range: 0.5 to 5.0, step 0.5 Description: Amplifies or dampens the color intensity response to average return magnitudes in the matrix heat map. 2.0 default provides balanced visual emphasis. Lower values (0.5-1.0) create subtle coloring requiring larger returns for full saturation, useful for volatile instruments. Higher values (3.0-5.0) produce vivid colors from smaller returns, highlighting subtle edges in range-bound markets. Minimum Occurrences for Coloring Default: 3 Range: 1 to 10 Description: Required minimum sample size before applying color-coded performance to matrix cells. Cells with fewer occurrences display gray “insufficient data” warning. 3-occurrence default filters out rare patterns. Lower threshold (1-2) shows more data but includes unreliable single-event statistics. Higher thresholds (5-10) ensure only well-established patterns receive visual emphasis. Table Position Default: top_right Options: top_left, top_right, bottom_left, bottom_right Description: Screen location for the 56-cell statistics matrix table. Position to avoid overlapping critical price action or other indicators on your chart. Consider chart orientation and candlestick density when selecting optimal placement. Show Current State Panel Default: true Options: true, false Description: Toggle visibility of the dedicated current state information panel. When enabled, displays signal strength, RSI value, indicator status, average return, estimated win rate, and confidence level for active market conditions. Disable to declutter charts when only the matrix table is needed. Info Panel Position Default: bottom_left Options: top_left, top_right, bottom_left, bottom_right Description: Screen location for the current state information panel (when enabled). Position independently from statistics matrix to optimize chart real estate. Typically placed opposite the matrix table for balanced visual layout. Win Rate Smoothing Strength Default: 5 Range: 1 to 20 Description: Controls Bayesian prior weighting for estimated win rate calculations. Acts as virtual sample size assuming 50% win rate baseline. Default 5 provides moderate smoothing preventing extreme win rate estimates from small samples. Lower values (1-3) reduce smoothing effect, allowing win rates to reflect raw data more directly. Higher values (10-20) increase conservatism, pulling win rate estimates toward 50% until substantial evidence accumulates. ✅Best Use Cases Pattern-based discretionary trading where you want historical confirmation before entering setups that “look good” based on current technical alignment Swing trading with holding periods matching your forward performance bar setting, using high-confidence bullish cells as entry filters Risk assessment and position sizing, allocating larger size to trades originating from cells with strong positive average returns and high estimated win rates Market regime identification by observing which RSI states and indicator combinations are currently producing the most reliable historical patterns Backtesting validation by comparing your manual strategy signals against the historical performance of the corresponding matrix cells Educational tool for developing intuition about which technical condition combinations have actually worked versus those that feel right but lack historical evidence ⚠️Limitations Historical patterns do not guarantee future performance, especially during unprecedented market events or regime changes not represented in the lookback period Small sample sizes (low occurrence counts) produce unreliable statistics despite Bayesian smoothing, requiring caution when acting on low-confidence cells Matrix statistics lag behind rapidly changing market conditions, as the lookback period must accumulate new state occurrences before updating performance data Forward return calculations use fixed bar periods that may not align with actual trade exit timing, support/resistance levels, or volatility-adjusted profit targets 💡What Makes This Unique Multi-Dimensional State Space: Unlike single-indicator tools, simultaneously tracks 56 distinct market condition combinations providing granular pattern resolution unavailable in traditional technical analysis Bayesian Statistical Rigor: Implements proper probabilistic smoothing to prevent overconfidence from limited data, a critical feature missing from most pattern recognition tools Real-Time Contextual Feedback: The “NOW” marker and dedicated info panel instantly connect current market conditions to their historical performance profile, eliminating guesswork Transparent Occurrence Counts: Displays sample sizes directly in each cell, allowing traders to judge statistical reliability themselves rather than hiding data quality issues Fully Customizable Analysis Window: Complete control over lookback depth and forward return horizons lets traders align the tool precisely with their trading timeframe and strategy requirements 🔬How It Works 1. State Classification and Encoding Each bar’s RSI value is evaluated and assigned to one of 7 discrete states based on threshold levels (0: <20, 1: 20-30, 2: 30-40, 3: 40-60, 4: 60-70, 5: 70-80, 6: >80) Simultaneously, three binary conditions are evaluated: MACD line position relative to signal line, current volume relative to its moving average, and current close relative to previous close These three binary conditions are combined into a single indicator state integer (0-7) using binary encoding, creating 8 possible indicator combinations The RSI state and indicator state are stored together, defining one of 56 possible market condition cells in the matrix 2. Historical Data Accumulation As each bar completes, the current state classification, closing price, and bar index are stored in rolling arrays maintained at the size specified by the lookback period When the arrays reach capacity, the oldest data point is removed and the newest added, creating a sliding historical window This continuous process builds a comprehensive database of past market conditions and their subsequent price movements 3. Forward Return Calculation and Statistics Update On each bar, the indicator looks back through the stored historical data to find bars where sufficient forward bars exist to measure outcomes For each historical occurrence, the price change from that bar to the bar N periods ahead (where N is the forward performance bars setting) is calculated as a percentage return This percentage return is added to the cumulative return total for the specific matrix cell corresponding to that historical bar’s state classification Occurrence counts are incremented, and wins are tallied for positive returns, building comprehensive statistics for each of the 56 cells The Bayesian smoothing formula combines these raw statistics with prior assumptions (neutral 50% win rate) weighted by the smoothing strength parameter to produce estimated win rates that remain stable even with small samples 💡Note: The Historical Matrix Analyzer is designed as a decision support tool, not a standalone trading system. Best results come from using it to validate discretionary trade ideas or filter systematic strategy signals. Always combine matrix insights with proper risk management, position sizing rules, and awareness of broader market context. The estimated win rate feature uses Bayesian statistics specifically to prevent false confidence from limited data, but no amount of smoothing can create reliable predictions from fundamentally insufficient sample sizes. Focus on high-confidence cells (green-colored confidence indicators) with occurrence counts well above your minimum threshold for the most actionable insights.
Pine Script®指標
由PhenLabs提供
1
Quantum Flux Universal Strategy Summary in one paragraph Quantum Flux Universal is a regime switching strategy for stocks, ETFs, index futures, major FX pairs, and liquid crypto on intraday and swing timeframes. It helps you act only when the normalized core signal and its guide agree on direction. It is original because the engine fuses three adaptive drivers into the smoothing gains itself. Directional intensity is measured with binary entropy, path efficiency shapes trend quality, and a volatility squash preserves contrast. Add it to a clean chart, watch the polarity lane and background, and trade from positive or negative alignment. For conservative workflows use on bar close in the alert settings when you add alerts in a later version. Scope and intent • Markets. Large cap equities and ETFs. Index futures. Major FX pairs. Liquid crypto • Timeframes. One minute to daily • Default demo used in the publication. QQQ on one hour • Purpose. Provide a robust and portable way to detect when momentum and confirmation align, while dampening chop and preserving turns • Limits. This is a strategy. Orders are simulated on standard candles only Originality and usefulness • Unique concept or fusion. The novelty sits in the gain map. Instead of gating separate indicators, the model mixes three drivers into the adaptive gains that power two one pole filters. Directional entropy measures how one sided recent movement has been. Kaufman style path efficiency scores how direct the path has been. A volatility squash stabilizes step size. The drivers are blended into the gains with visible inputs for strength, windows, and clamps. • What failure mode it addresses. False starts in chop and whipsaw after fast spikes. Efficiency and the squash reduce over reaction in noise. • Testability. Every component has an input. You can lengthen or shorten each window and change the normalization mode. The polarity plot and background provide a direct readout of state. • Portable yardstick. The core is normalized with three options. Z score, percent rank mapped to a symmetric range, and MAD based Z score. Clamp bounds define the effective unit so context transfers across symbols. Method overview in plain language The strategy computes two smoothed tracks from the chart price source. The fast track and the slow track use gains that are not fixed. Each gain is modulated by three drivers. A driver for directional intensity, a driver for path efficiency, and a driver for volatility. The difference between the fast and the slow tracks forms the raw flux. A small phase assist reduces lag by subtracting a portion of the delayed value. The flux is then normalized. A guide line is an EMA of a small lead on the flux. When the flux and its guide are both above zero, the polarity is positive. When both are below zero, the polarity is negative. Polarity changes create the trade direction. Base measures • Return basis. The step is the change in the chosen price source. Its absolute value feeds the volatility estimate. Mean absolute step over the window gives a stable scale. • Efficiency basis. The ratio of net move to the sum of absolute step over the window gives a value between zero and one. High values mean trend quality. Low values mean chop. • Intensity basis. The fraction of up moves over the window plugs into binary entropy. Intensity is one minus entropy, which maps to zero in uncertainty and one in very one sided moves. Components • Directional Intensity. Measures how one sided recent bars have been. Smoothed with RMA. More intensity increases the gain and makes the fast and slow tracks react sooner. • Path Efficiency. Measures the straightness of the price path. A gamma input shapes the curve so you can make trend quality count more or less. Higher efficiency lifts the gain in clean trends. • Volatility Squash. Normalizes the absolute step with Z score then pushes it through an arctangent squash. This caps the effect of spikes so they do not dominate the response. • Normalizer. Three modes. Z score for familiar units, percent rank for a robust monotone map to a symmetric range, and MAD based Z for outlier resistance. • Guide Line. EMA of the flux with a small lead term that counteracts lag without heavy overshoot. Fusion rule • Weighted sum of the three drivers with fixed weights visible in the code comments. Intensity has fifty percent weight. Efficiency thirty percent. Volatility twenty percent. • The blend power input scales the driver mix. Zero means fixed spans. One means full driver control. • Minimum and maximum gain clamps bound the adaptive gain. This protects stability in quiet or violent regimes. Signal rule • Long suggestion appears when flux and guide are both above zero. That sets polarity to plus one. • Short suggestion appears when flux and guide are both below zero. That sets polarity to minus one. • When polarity flips from plus to minus, the strategy closes any long and enters a short. • When flux crosses above the guide, the strategy closes any short. What you will see on the chart • White polarity plot around the zero line • A dotted reference line at zero named Zen • Green background tint for positive polarity and red background tint for negative polarity • Strategy long and short markers placed by the TradingView engine at entry and at close conditions • No table in this version to keep the visual clean and portable Inputs with guidance Setup • Price source. Default ohlc4. Stable for noisy symbols. • Fast span. Typical range 6 to 24. Raising it slows the fast track and can reduce churn. Lowering it makes entries more reactive. • Slow span. Typical range 20 to 60. Raising it lengthens the baseline horizon. Lowering it brings the slow track closer to price. Logic • Guide span. Typical range 4 to 12. A small guide smooths without eating turns. • Blend power. Typical range 0.25 to 0.85. Raising it lets the drivers modulate gains more. Lowering it pushes behavior toward fixed EMA style smoothing. • Vol window. Typical range 20 to 80. Larger values calm the volatility driver. Smaller values adapt faster in intraday work. • Efficiency window. Typical range 10 to 60. Larger values focus on smoother trends. Smaller values react faster but accept more noise. • Efficiency gamma. Typical range 0.8 to 2.0. Above one increases contrast between clean trends and chop. Below one flattens the curve. • Min alpha multiplier. Typical range 0.30 to 0.80. Lower values increase smoothing when the mix is weak. • Max alpha multiplier. Typical range 1.2 to 3.0. Higher values shorten smoothing when the mix is strong. • Normalization window. Typical range 100 to 300. Larger values reduce drift in the baseline. • Normalization mode. Z score, percent rank, or MAD Z. Use MAD Z for outlier heavy symbols. • Clamp level. Typical range 2.0 to 4.0. Lower clamps reduce the influence of extreme runs. Filters • Efficiency filter is implicit in the gain map. Raising efficiency gamma and the efficiency window increases the preference for clean trends. • Micro versus macro relation is handled by the fast and slow spans. Increase separation for swing, reduce for scalping. • Location filter is not included in v1.0. If you need distance gates from a reference such as VWAP or a moving mean, add them before publication of a new version. Alerts • This version does not include alertcondition lines to keep the core minimal. If you prefer alerts, add names Long Polarity Up, Short Polarity Down, Exit Short on Flux Cross Up in a later version and select on bar close for conservative workflows. Strategy has been currently adapted for the QQQ asset with 30/60min timeframe. For other assets may require new optimization Properties visible in this publication • Initial capital 25000 • Base currency Default • Default order size method percent of equity with value 5 • Pyramiding 1 • Commission 0.05 percent • Slippage 10 ticks • Process orders on close ON • Bar magnifier ON • Recalculate after order is filled OFF • Calc on every tick OFF Honest limitations and failure modes • Past results do not guarantee future outcomes • Economic releases, circuit breakers, and thin books can break the assumptions behind intensity and efficiency • Gap heavy symbols may benefit from the MAD Z normalization • Very quiet regimes can reduce signal contrast. Use longer windows or higher guide span to stabilize context • Session time is the exchange time of the chart • If both stop and target can be hit in one bar, tie handling would matter. This strategy has no fixed stops or targets. It uses polarity flips for exits. If you add stops later, declare the preference Open source reuse and credits • None beyond public domain building blocks and Pine built ins such as EMA, SMA, standard deviation, RMA, and percent rank • Method and fusion are original in construction and disclosure Legal Education and research only. Not investment advice. You are responsible for your decisions. Test on historical data and in simulation before any live use. Use realistic costs. Strategy add on block Strategy notice Orders are simulated by the TradingView engine on standard candles. No request.security() calls are used. Entries and exits • Entry logic. Enter long when both the normalized flux and its guide line are above zero. Enter short when both are below zero • Exit logic. When polarity flips from plus to minus, close any long and open a short. When the flux crosses above the guide line, close any short • Risk model. No initial stop or target in v1.0. The model is a regime flipper. You can add a stop or trail in later versions if needed • Tie handling. Not applicable in this version because there are no fixed stops or targets Position sizing • Percent of equity in the Properties panel. Five percent is the default for examples. Risk per trade should not exceed five to ten percent of equity. One to two percent is a common choice Properties used on the published chart • Initial capital 25000 • Base currency Default • Default order size percent of equity with value 5 • Pyramiding 1 • Commission 0.05 percent • Slippage 10 ticks • Process orders on close ON • Bar magnifier ON • Recalculate after order is filled OFF • Calc on every tick OFF Dataset and sample size • Test window Jan 2, 2014 to Oct 16, 2025 on QQQ one hour • Trade count in sample 324 on the example chart Release notes template for future updates Version 1.1. • Add alertcondition lines for long, short, and exit short • Add optional table with component readouts • Add optional stop model with a distance unit expressed as ATR or a percent of price Notes. Backward compatibility Yes. Inputs migrated Yes.
Pine Script®策略
由exlux提供
RSI MA Cross + Divergence Signal (V2) Core Logic RSI + Moving Average The script calculates a standard RSI (default 14). It then overlays a moving average (SMA/EMA/WMA, default 9). When RSI crosses above its MA → bullish momentum. When RSI crosses below its MA → bearish momentum. Divergence Filter Signals are only valid if there’s confirmed divergence: Bullish divergence: Price makes a lower low, RSI makes a higher low. Bearish divergence: Price makes a higher high, RSI makes a lower high. Overbought / Oversold Filter Optional extra: Bullish signals only valid if RSI ≤ 30 (oversold). Bearish signals only valid if RSI ≥ 70 (overbought). This ensures signals happen in “stretched” conditions. Risk & Trade Management Entries taken only when all conditions align. Exits can be managed with ATR stops, partial take-profits, breakeven moves, and trailing stops (we coded these in the strategy version). Cooldown, session filters, and daily loss guard to keep risk tight. 🔹 Strengths ✅ High selectivity: Combining RSI cross + divergence + OB/OS means signals are rare but higher quality. ✅ Great at catching reversals: Divergence highlights where price may be running out of steam. ✅ Risk management baked in: ATR stops + partial exits smooth out equity curve. ✅ Works across markets: ES, FX, crypto — anywhere RSI divergences are respected. ✅ Flexible: You can loosen/tighten filters depending on aggressiveness. 🔹 Weaknesses ❌ Lag from pivots: Divergence only confirms after a few bars → you enter late sometimes. ❌ Choppy in ranges: In sideways markets, RSI divergences appear often and whipsaw. ❌ Filters reduce signals: With all filters ON (divergence + OB/OS + trend + session), signals can be very rare — may under-trade. ❌ Not standalone: Needs higher-timeframe context (trend, liquidity pools) to avoid counter-trend entries. 🔹 Best Ways to Trade It Use Higher Timeframe Bias Run the strategy on 15m/1H, but only trade in direction of higher timeframe trend (e.g., 4H EMA). Example: If daily is bullish → only take bullish divergences. Pair With Structure Look for signals at key zones: HTF support/resistance, VWAP, or FVGs. Divergence + RSI cross inside an FVG is a strong entry trigger. Adjust OB/OS for Volatility For crypto/FX: use 35/65 instead of 30/70 (markets trend harder). For ES/S&P: 30/70 works fine. Risk Management Is King Use partial exits: take profit at 1R, trail rest. Size by % of equity (we coded this into the strategy). Avoid News Spikes Divergences break down around CPI, NFP, Fed announcements — stay flat. 🔹 When It Shines Trending markets that make extended pushes → clean divergences. Reversal zones (oversold → bullish bounce, overbought → bearish fade). Swing trading (15m–4H) — less noise than 1m/5m scalping. 🔹 When to Avoid Low volatility chop → lots of false divergences. During high-impact news → RSI swings wildly. In strong one-way trends without pullbacks — divergence keeps calling tops/bottoms too early. ✅ Summary: This is a reversal-focused RSI divergence strategy with strict filters. It’s powerful when combined with higher-timeframe bias + structure confluence, but weak if traded blindly in choppy or news-driven conditions. Best to treat it as a precision entry trigger, not a full system — layer it on top of your FVG/ORB framework for maximum edge.
Pine Script®指標
由noxum提供
1
Measured Move Volume XIndicator Description The "Measured Move Volume X" indicator, developed for TradingView using Pine Script version 6, projects potential price targets based on the measured move concept, where the magnitude of a prior price leg (Leg A) is used to forecast a subsequent move. It overlays translucent boxes on the chart to visualize bullish (green) or bearish (red) price projections, extending them to the right for a user-specified number of bars. The indicator integrates volume analysis (relative to a simple moving average), RSI for momentum, and VWAP for price-volume weighting, combining these into a confidence score to filter entry signals, displayed as triangles on breakouts. Horizontal key level lines (large, medium, small) are drawn at significant price points derived from the measured moves, with customizable thresholds, colors, and styles. Exhaustion hints, shown as orange labels near box extremes, indicate potential reversal points. Anomalous candles, marked with diamond shapes, are identified based on volume spikes and body-to-range ratios. Optional higher timeframe candle coloring enhances context. The indicator is fully customizable through input groups for lookback periods, transparency, and signal weights, making it adaptable to various assets and timeframes. Adjustment Tips for Optimization To optimize the "Measured Move Volume X" indicator for specific assets or timeframes, adjust the following input parameters: Leg A Lookback (default: 14 bars): Increase to 20-30 for volatile markets (e.g., cryptocurrencies) to capture larger price swings; decrease to 5-10 for intraday charts (e.g., stocks) for faster signals. Extend Box to the Right (default: 30 bars): Extend to 50+ for daily or weekly charts to project further targets; shorten to 10-20 for lower timeframes to reduce clutter. Volume SMA Length (default: 20) and Relative Volume Threshold (default: 1.5): Lower the threshold to 1.2-1.3 for low-volume assets (e.g., commodities) to detect subtler spikes; raise to 2.0+ for high-volume equities to filter noise. Match SMA length to RSI length for consistency. RSI Parameters (default: length 14, overbought 70, oversold 30): Set overbought to 80 and oversold to 20 in trending markets to reduce premature exit signals; shorten length to 7-10 for scalping. Key Level Thresholds (default: large 10%, medium 5%, small 5%): Increase thresholds (e.g., large to 15%) for volatile assets to focus on significant moves; disable medium or small lines to declutter charts. Confidence Score Weights (default: volume 0.5, VWAP 0.3, RSI 0.2): Increase volume weight (e.g., 0.7) for volume-driven markets like futures; emphasize RSI (e.g., 0.4) for momentum-focused strategies. Anomaly Detection (default: volume multiplier 1.5, small body ratio 0.2, large body ratio 0.75): Adjust the volume multiplier higher for stricter anomaly detection in noisy markets; fine-tune body-to-range ratios based on asset-specific candle patterns. Use TradingView’s replay feature to test adjustments on historical data, ensuring settings suit the chosen market and timeframe. Tips for Using the Indicator Interpreting Signals: Green upward triangles indicate bullish breakout entries when price exceeds the prior high with a confidence score ≥40; red downward triangles signal bearish breakouts. Use these to identify potential entry points aligned with the projected box targets. Box Projections: Bullish boxes project upward targets (top of box) equal to the prior leg’s height added to the breakout price; bearish boxes project downward. Monitor price action near box edges for target completion or reversal. Exhaustion Hints: Orange labels near box tops (bullish) or bottoms (bearish) suggest potential exhaustion when price deviates within the set percentage (default: 5%) and RSI or volume conditions are met. Use these as cues to watch for reversals. Key Level Lines: Large, medium, and small lines mark significant price levels from box tops/bottoms. Use these as potential support/resistance zones, especially when drawn with high volume (colored differently). Anomaly Candles: Orange diamonds highlight candles with unusual volume/body characteristics, indicating potential reversals or pauses. Combine with box levels for context. Higher Timeframe Coloring: Enable to color bars based on higher timeframe candle closures (e.g., 1, 2, 5, or 15 minutes) for added trend context. Customization: Toggle "Only Show Bullish Moves" to focus on bullish setups. Adjust transparency and line styles for visual clarity. Test settings to balance signal frequency and chart readability. Inputs: Organized into groups (e.g., "Measured Move Settings") using input.int, input.float, input.color, and input.bool for user customization, with tooltips for clarity. Calculations: Computes relative volume (ta.sma(volume, volLookback)), VWAP (ta.vwap(hlc3)), RSI (ta.rsi(close, rsiLength)), and prior leg extremes (ta.highest/lowest) using prior bar data ( ) to prevent repainting. Boxes and Lines: Creates boxes (box.new) for bullish/bearish projections and lines (line.new) for key levels. The f_addLine function manages line arrays (array.new_line), capping at maxLinesCount to avoid clutter. Confidence Score: Combines volume, VWAP distance, and RSI into a weighted score (confScore), filtering entries (≥40). Rounded for display. Exhaustion Hints: Functions like f_plotBullExitHint assess price deviation, RSI, and volume decrease, using label.new for dynamic orange labels. Entry Signals and Plots: plotshape displays triangles for breakouts; plot and hline show VWAP and RSI levels; request.security handles higher timeframe coloring. Anomaly Detection: Identifies candles with small-body high-volume or large-body average-volume patterns via ratios, plotted as diamonds.
Pine Script®指標
由kwsatterfield1提供
2
RenKagi Fusion: Aura & SMA Clash IndicatorRenKagi Fusion: Aura & SMA Clash Indicator Welcome to the RenKagi Fusion Indicator – a powerful, customizable tool that blends the strengths of Renko and Kagi charts to provide noise-filtered trend insights, enhanced with visual Aura effects and SMA (Simple Moving Average) crossover signals. Designed for traders seeking a unique edge in trend detection and reversal identification, this indicator combines traditional charting techniques with modern visualizations to help you navigate markets more effectively. Whether you're trading stocks, forex, or crypto, RenKagi Fusion offers a clean, actionable overview of market dynamics. Key Features RenKagi Line (Weighted Fusion of Renko and Kagi): The core of the indicator is the RenKagi line, a weighted average of Renko (brick-based trend filtering) and Kagi (reversal-focused line charts). Users can adjust the weight (default: 60% Renko, 40% Kagi) to prioritize stability or sensitivity. This fusion reduces market noise while highlighting key price movements. Trend Scoring System: Calculates strength scores for Renko, Kagi, and RenKagi (capped at 20 points, converted to percentages). Scores increase with trend continuation and reset on reversals, giving a quantitative measure of momentum. Aura Effects (Optional): Visual "glow" around lines based on score percentage – higher scores mean more opaque and thicker auras, adding a dynamic layer to trend visualization. SMA Clash (Crossover Detection): Monitors daily SMA50, SMA100, and SMA200 for golden/death crosses (SMA50 crossing above/below longer SMAs) and RenKagi-SMA crossovers. These are displayed in a persistent info table for quick reference. Customizable Visuals: Toggle lines, boxes, shapes, auras, and labels. Background coloring based on selected source (Renko, Kagi, or RenKagi) for intuitive trend bias. Info Table: A configurable table (position and colors adjustable) summarizing scores, directions, cross states, brick size (with type), Kagi reversal (with type), and weights. No clutter – all in one place. Alert Conditions: Built-in alerts for direction changes (Renko, Kagi, RenKagi), SMA crossovers, and golden/death crosses – perfect for real-time notifications. How It Works Renko Logic: Builds bricks based on user-selected type (Traditional fixed size, ATR dynamic, or Percentage). Scores build as trends persist, resetting on reversals. Kagi Logic: Line reverses on thresholds (Traditional, ATR, or Percentage), scoring continuous moves. RenKagi Calculation: Weighted average: (renkoPrice * renkoWeight + kagiLine * (100 - renkoWeight)) / 100. Score is a blend of individual scores. SMA Integration: Daily timeframe SMAs for reliable long-term signals. Crossovers trigger alerts and update table states persistently until reversed. Advantages for Traders Noise Reduction: By fusing Renko's block structure with Kagi's reversal focus, it filters out minor fluctuations, helping identify strong trends early. Versatility: Fully customizable – adjust weights, types, and visuals to fit any market or timeframe. Ideal for swing trading, trend following, or scalping. Visual Clarity: Aura and background coloring provide at-a-glance insights, while the table consolidates data without overwhelming the chart. Actionable Signals: Golden/Death crosses and direction changes offer clear entry/exit points, backed by alerts for timely execution. Performance Optimization: Limits on lines/labels/boxes (500 each) ensure smooth operation on large datasets. Usage Tips Start with default settings for balanced performance. Use in higher timeframes for trend confirmation or lower for intraday signals. Combine with your favorite strategies – e.g., buy on RenKagi upward cross with SMA50 and golden cross confirmation. Test on historical data to optimize weights and thresholds. Note: This indicator is for educational and informational purposes only. Past performance is not indicative of future results. Always conduct your own analysis and use risk management. No financial advice is provided. If you find this useful, please like, comment, or share your feedback!
Pine Script®指標
由IQ-TRADER提供
Hazel nut BB Strategy, volume base- lite versionHazel nut BB Strategy, volume base — lite version Having knowledge and information in financial markets is only useful when a trader operates with a well-defined trading strategy. Trading strategies assist in capital management, profit-taking, and reducing potential losses. This strategy is built upon the core principle of supply and demand dynamics. Alongside this foundation, one of the widely used technical tools — the Bollinger Bands — is employed to structure a framework for profit management and risk control. In this strategy, the interaction of these tools is explained in detail. A key point to note is that for calculating buy and sell volumes, a lower timeframe function is used. When applied with a tick-level resolution, this provides the most precise measurement of buyer/seller flows. However, this comes with a limitation of reduced historical depth. Users should be aware of this trade-off: if precise tick-level data is required, shorter timeframes should be considered to extend historical coverage . The strategy offers multiple configuration options. Nevertheless, it should be treated strictly as a supportive tool rather than a standalone trading system. Decisions must integrate personal analysis and other instruments. For example, in highly volatile assets with narrow ranges, it is recommended to adjust profit-taking and stop-loss percentages to smaller values. ◉ Volume Settings • Buyer and seller volume (up/down volume) are requested from a lower timeframe, with an option to override the automatic resolution. • A global lookback period is applied to calculate moving averages and cumulative sums of buy/sell/delta volumes. • Ratios of buyers/sellers to total volume are derived both on the current bar and across the lookback window. ◉ Bollinger Band • Bands are computed using configurable moving averages (SMA, EMA, RMA, WMA, VWMA). • Inputs allow control of length, standard deviation multiplier, and offset. • The basis, upper, and lower bands are plotted, with a shaded background between them. ◉ Progress & Proximity • Relative position of the price to the Bollinger basis is expressed as percentages (qPlus/qMinus). • “Near band” conditions are triggered when price progress toward the upper or lower band exceeds a user-defined threshold (%). • A signed score (sScore) represents how far the close has moved above or below the basis relative to band width. ◉ Info Table • Optional compact table summarizing: • - Upper/lower band margins • - Buyer/seller volumes with moving averages • - Delta and cumulative delta • - Buyer/seller ratios per bar and across the window • - Money flow values (buy/sell/delta × price) for bar-level and summed periods • The table is neutral-colored and resizable for different chart layouts. ◉ Zone Event Gate • Tracks entry into and exit from “near band” zones. • Arming logic: a side is armed when price enters a band proximity zone. • Trigger logic: on exit, a trade event is generated if cumulative buyer or seller volume dominates over a configurable window. ◉ Trading Logic • Orders are placed only on zone-exit events, conditional on volume dominance. • Position sizing is defined as a fixed percentage of strategy equity. • Long entries occur when leaving the lower zone with buyer dominance; short entries occur when leaving the upper zone with seller dominance. ◉ Exit Rules • Open positions are managed by a strict priority sequence: • 1. Stop-loss (% of entry price) • 2. Take-profit (% of entry price) • 3. Opposite-side event (zone exit with dominance in the other direction) • Stop-loss and take-profit levels are configurable ◉ Notes • This lite version is intended to demonstrate the interaction of Bollinger Bands and volume-based dominance logic. • It provides a framework to observe how price reacts at band boundaries under varying buy/sell pressure, and how zone exits can be systematically converted into entry/exit signals. When configuring this strategy, it is essential to carefully review the settings within the Strategy Tester. Ensure that the chosen parameters and historical data options are correctly aligned with the intended use. Accurate back testing depends on applying proper configurations for historical reference. The figure below illustrates sample result and configuration type.
Pine Script®策略
由ata_sabanci提供
Tristan's Box: Pre-Market Range Breakout + RetestMarket Context: This is designed for U.S. stocks, focusing on pre-market price action (4:00–9:30 AM ET) to identify key support/resistance levels before the regular session opens. Built for 1 min and 5 min timelines, and is intended for day trading / scalping. Core Idea: Pre-market range (high/low) often acts as a magnet for price during regular hours. The first breakout outside this range signals potential strong momentum in that direction. Retest of the breakout level confirms whether the breakout is valid, avoiding false moves. Step-by-Step Logic: Pre-Market Range Identification: Track high and low from 4:00–9:30 AM ET. Draw a box spanning this range for visual reference and calculation. Breakout Detection: When the first candle closes above the pre-market high → long breakout. When the first candle closes below the pre-market low → short breakout. The first breakout candle is highlighted with a “YOLO” label for visual confirmation. Retest Confirmation: Identify the first candle whose wick touches the pre-market box (high touches top for short, low touches bottom for long). Wait for the next candle: if it closes outside the box, it confirms the breakout. Entry Execution: Long entry: on the confirming candle after a wick-touch above the pre-market high. Short entry: on the confirming candle after a wick-touch below the pre-market low. Only the first valid entry per direction per day is taken. Visuals & Alerts: Box represents pre-market high/low. Top/bottom box border lines show the pre-market high / low levels cleanly. BUY/SELL markers are pinned to the confirming candle. Added a "YOLO" marker on breakout candle. Alert conditions trigger when a breakout is confirmed by the retest. Strategy Type: Momentum breakout strategy with confirmation retest. Combines pre-market structure and risk-managed entries. Designed to filter false breakouts by requiring confirmation on the candle after the wick-touch. In short, it’s a pre-market breakout momentum strategy: it uses the pre-market high/low as reference, waits for a breakout, and then enters only after a confirmation retest, reducing the chance of entering on a false spike. Always use good risk management.
Pine Script®策略
由OhRayOhRay提供
1
Deadband Hysteresis Filter [BackQuant]Deadband Hysteresis Filter What this is This tool builds a “debounced” price baseline that ignores small fluctuations and only reacts when price meaningfully departs from its recent path. It uses a deadband to define how much deviation matters and a hysteresis scheme to avoid rapid flip-flops around the decision boundary. The baseline’s slope provides a simple trend cue, used to color candles and to trigger up and down alerts. Why deadband and hysteresis help They filter micro noise so the baseline does not react to every tiny tick. They stabilize state changes. Hysteresis means the rule to start moving is stricter than the rule to keep holding, which reduces whipsaw. They produce a stepped, readable path that advances during sustained moves and stays flat during chop. How it works (conceptual) At each bar the script maintains a running baseline dbhf and compares it to the input price p . Compute a base threshold baseTau using the selected mode (ATR, Percent, Ticks, or Points). Build an enter band tauEnter = baseTau × Enter Mult and an exit band tauExit = baseTau × Exit Mult where typically Exit Mult < Enter Mult . Let diff = p − dbhf . If diff > +tauEnter , raise the baseline by response × (diff − tauEnter) . If diff < −tauEnter , lower the baseline by response × (diff + tauEnter) . Otherwise, hold the prior value. Trend state is derived from slope: dbhf > dbhf → up trend, dbhf < dbhf → down trend. Inputs and what they control Threshold mode ATR — baseTau = ATR(atrLen) × atrMult . Adapts to volatility. Useful when regimes change. Percent — baseTau = |price| × pctThresh% . Scale-free across symbols of different prices. Ticks — baseTau = syminfo.mintick × tickThresh . Good for futures where tick size matters. Points — baseTau = ptsThresh . Fixed distance in price units. Band multipliers and response Enter Mult — outer band. Price must travel at least this far from the baseline before an update occurs. Larger values reject more noise but increase lag. Exit Mult — inner band for hysteresis. Keep this smaller than Enter Mult to create a hold zone that resists small re-entries. Response — step size when outside the enter band. Higher response tracks faster; lower response is smoother. UI settings Show Filtered Price — plots the baseline on price. Paint candles — colors bars by the filtered slope using your long/short colors. How it can be used Trend qualifier — take entries only in the direction of the baseline slope and skip trades against it. Debounced crossovers — use the baseline as a stabilized surrogate for price in moving-average or channel crossover rules. Trailing logic — trail stops a small distance beyond the baseline so small pullbacks do not eject the trade. Session aware filtering — widen Enter Mult or switch to ATR mode for volatile sessions; tighten in quiet sessions. Parameter interactions and tuning Enter Mult vs Response — both govern sensitivity. If you see too many flips, increase Enter Mult or reduce Response. If turns feel late, do the opposite. Exit Mult — widening the gap between Enter and Exit expands the hold zone and reduces oscillation around the threshold. Mode choice — ATR adapts automatically; Percent keeps behavior consistent across instruments; Ticks or Points are useful when you think in fixed increments. Timeframe coupling — on higher timeframes you can often lower Enter Mult or raise Response because raw noise is already reduced. Concrete starter recipes General purpose — ATR mode, atrLen=14 , atrMult=1.0–1.5 , Enter=1.0 , Exit=0.5 , Response=0.20 . Balanced noise rejection and lag. Choppy range filter — ATR mode, increase atrMult to 2.0, keep Response≈0.15 . Stronger suppression of micro-moves. Fast intraday — Percent mode, pctThresh=0.1–0.3 , Enter=1.0 , Exit=0.4–0.6 , Response=0.30–0.40 . Quicker turns for scalping. Futures ticks — Ticks mode, set tickThresh to a few spreads beyond typical noise; start with Enter=1.0 , Exit=0.5 , Response=0.25 . Strengths Clear, explainable logic with an explicit noise budget. Multiple threshold modes so the same tool fits equities, futures, and crypto. Built-in hysteresis that reduces flip-flop near the boundary. Slope-based coloring and alerts that make state changes obvious in real time. Limitations and notes All filters add lag. Larger thresholds and smaller response trade faster reaction for fewer false turns. Fixed Points or Ticks can under- or over-filter when volatility regime shifts. ATR adapts, but will also expand bands during spikes. On extremely choppy symbols, even a well tuned band will step frequently. Widen Enter Mult or reduce Response if needed. This is a chart study. It does not include commissions, slippage, funding, or gap risks. Alerts DBHF Up Slope — baseline turns from down to up on the latest bar. DBHF Down Slope — baseline turns from up to down on the latest bar. Implementation details worth knowing Initialization sets the baseline to the first observed price to avoid a cold-start jump. Slope is evaluated bar-to-bar. The up and down alerts check for a change of slope rather than raw price crossings. Candle colors and the baseline plot share the same long/short palette with transparency applied to the line. Practical workflow Pick a mode that matches how you think about distance. ATR for volatility aware, Percent for scale-free, Ticks or Points for fixed increments. Tune Enter Mult until the number of flips feels appropriate for your timeframe. Set Exit Mult clearly below Enter Mult to create a real hold zone. Adjust Response last to control “how fast” the baseline chases price once it decides to move. Final thoughts Deadband plus hysteresis gives you a principled way to “only care when it matters.” With a sensible threshold and response, the filter yields a stable, low-chop trend cue you can use directly for bias or plug into your own entries, exits, and risk rules.
Pine Script®指標
由BackQuant提供
10
ATAI Volume Pressure Analyzer V 1.0 — Pure Up/DownATAI Volume Pressure Analyzer V 1.0 — Pure Up/Down Overview Volume is a foundational tool for understanding the supply–demand balance. Classic charts show only total volume and don’t tell us what portion came from buying (Up) versus selling (Down). The ATAI Volume Pressure Analyzer fills that gap. Built on Pine Script v6, it scans a lower timeframe to estimate Up/Down volume for each host‑timeframe candle, and presents “volume pressure” in a compact HUD table that’s comparable across symbols and timeframes. 1) Architecture & Global Settings Global Period (P, bars) A single global input P defines the computation window. All measures—host‑TF volume moving averages and the half‑window segment sums—use this length. Default: 55. Timeframe Handling The core of the indicator is estimating Up/Down volume using lower‑timeframe data. You can set a custom lower timeframe, or rely on auto‑selection: ◉ Second charts → 1S ◉ Intraday → 1 minute ◉ Daily → 5 minutes ◉ Otherwise → 60 minutes Lower TFs give more precise estimates but shorter history; higher TFs approximate buy/sell splits but provide longer history. As a rule of thumb, scan thin symbols at 5–15m, and liquid symbols at 1m. 2) Up/Down Volume & Derived Series The script uses TradingView’s library function tvta.requestUpAndDownVolume(lowerTf) to obtain three values: ◉ Up volume (buyers) ◉ Down volume (sellers) ◉ Delta (Up − Down) From these we define: ◉ TF_buy = |Up volume| ◉ TF_sell = |Down volume| ◉ TF_tot = TF_buy + TF_sell ◉ TF_delta = TF_buy − TF_sell A positive TF_delta indicates buyer dominance; a negative value indicates selling pressure. To smooth noise, simple moving averages of TF_buy and TF_sell are computed over P and used as baselines. 3) Key Performance Indicators (KPIs) Half‑window segmentation To track momentum shifts, the P‑bar window is split in half: ◉ C→B: the older half ◉ B→A: the newer half (toward the current bar) For each half, the script sums buy, sell, and delta. Comparing the two halves reveals strengthening/weakening pressure. Example: if AtoB_delta < CtoB_delta, recent buying pressure has faded. [ 4) HUD (Table) Display /i] Colors & Appearance Two main color inputs define the theme: a primary color and a negative color (used when Δ is negative). The panel background uses a translucent version of the primary color; borders use the solid primary color. Text defaults to the primary color and flips to the negative color when a block’s Δ is negative. Layout The HUD is a 4×5 table updated on the last bar of each candle: ◉ Row 1 (Meta): indicator name, P length, lower TF, host TF ◉ Row 2 (Host TF): current ↑Buy, ↓Sell, ΔDelta; plus Σ total and SMA(↑/↓) ◉ Row 3 (Segments): C→B and B→A blocks with ↑/↓/Δ ◉ Rows 4–5: reserved for advanced modules (Wings, α/β, OB/OS, Top 5) Advanced Modules 5.1 Wings “Wings” visualize volume‑driven movement over C→B (left wing) and B→A (right wing) with top/bottom lines and a filled band. Slopes are ATR‑per‑bar normalized for cross‑symbol/TF comparability and converted to angles (degrees). Coloring mirrors HUD sign logic with a near‑zero threshold (default ~3°): ◉ Both lines rising → blue (bullish) ◉ Both falling → red (bearish) ◉ Mixed/near‑zero → gray Left wing reflects the origin of the recent move; right wing reflects the current state. 5.2 α / β at Point B We compute the oriented angle between the two wings at the midpoint B: β is the bottom‑arc angle; α = 360° − β is the top‑arc angle. ◉ Large α (>180°) or small β (<180°) flags meaningful imbalance. ◉ Intuition: large α suggests potential selling pressure; small β implies fragile support. HUD cells highlight these conditions. 5.3 OB/OS Spike OverBought/OverSold (OB/OS) labels appear when directional volume spikes align with a 7‑oscillator vote (RSI, Stoch, %R, CCI, MFI, DeMarker, StochRSI). ◉ OB label (red): unusually high sell volume + enough OB votes ◉ OS label (teal): unusually high buy volume + enough OS votes Minimum votes and sync window are user‑configurable; dotted connectors can link labels to the candle wick. 5.4 Top3 Volume Peaks Within the P window the script ranks the top three BUY peaks (B1–B3) and top three SELL peaks (S1–S3). ◉ B1 and S1 are drawn as horizontal resistance (at B1 High) and support (at S1 Low) zones with adjustable thickness (ticks/percent/ATR). ◉ The HUD dedicates six cells to show ↑/↓/Δ for each rank, and prints the exact High (B1) and Low (S1) inline in their cells. 6) Reading the HUD — A Quick Checklist ◉ Meta: Confirm P and both timeframes (host & lower). ◉ Host TF block: Compare current ↑/↓/Δ against their SMAs. ◉ Segments: Contrast C→B vs B→A deltas to gauge momentum change. ◉ Wings: Right‑wing color/angle = now; left wing = recent origin. ◉ α / β: Look for α > 180° or β < 180° as imbalance cues. ◉ OB/OS: Note labels, color (red/teal), and the vote count. ◉Top3: Keep B1 (resistance) and S1 (support) on your radar. Use these together to sketch scenarios and invalidation levels; never rely on a single signal in isolation. [ 7) Example Highlights (What the table conveys) /i] ◉ Row 1 shows the indicator name, the analysis length P (default 55), and both TFs used for computation and display. ◉ B1 / S1 blocks summarize each side’s peak within the window, with Δ indicating buyer/seller dominance at that peak and inline price (B1 High / S1 Low) for actionable levels. ◉ Angle cells for each wing report the top/bottom line angles vs. the horizontal, reflecting the directional posture. ◉ Ranks B2/B3 and S2/S3 extend context beyond the top peak on each side. ◉ α / β cells quantify the orientation gap at B; changes reflect shifting buyer/seller influence on trend strength. Together these visuals often reveal whether the “wings” resemble a strong, upward‑tilted arm supported by buyer volume—but always corroborate with your broader toolkit 8) Practical Tips & Tuning ◉ Choose P by market structure. For daily charts, 34–89 bars often works well. ◉ Lower TF choice: Thin symbols → 5–15m; liquid symbols → 1m. ◉ Near‑zero angle: In noisy markets, consider 5–7° instead of 3°. ◉ OB/OS votes: Daily charts often work with 3–4 votes; lower TFs may prefer 4–5. ◉ Zone thickness: Tie B1/S1 zone thickness to ATR so it scales with volatility. ◉ Colors: Feel free to theme the primary/negative colors; keep Δ<0 mapped to the negative color for readability. Combine with price action: Use this indicator alongside structure, trendlines, and other tools for stronger decisions. Technical Notes Pine Script v6. ◉ Up/Down split via TradingView/ta library call requestUpAndDownVolume(lowerTf). ◉ HUD‑first design; drawings for Wings/αβ/OBOS/Top3 align with the same sign/threshold logic used in the table. Disclaimer: This indicator is provided solely for educational and analytical purposes. It does not constitute financial advice, nor is it a recommendation to buy or sell any security. Always conduct your own research and use multiple tools before making trading decisions.
Pine Script®指標
由ata_sabanci提供
13
Support Vs Reward RvCSupport Vs Reward RvC The Support Vs Reward RvC indicator is a simple yet effective tool that analyzes candle strength relative to both price movement and trading volume. Highlights candles where both body size and volume expand or contract, helping traders spot momentum shifts and weakening moves. 📌 How it works: - “C” expect a Continuation of Trend in the next one or two candles; - “R” expect a Reverse of Trend in the next one or two candles. Works well on bigger time candles like 10-15 minutes but also gives important info in day-trading or scalping. Marks candles where both body size and volume increase or decrease, making momentum shifts easy to spot. This smart candle analyzer reveals momentum surges and fading moves through body size and volume dynamics. It compares each candle’s body size (open-to-close range) and its volume against the previous candle. If both the body and volume are greater than the previous candle, a green “C” from Continuation of Trend is displayed under the bar. If both the body and volume are smaller than the previous candle, a red “R” from Reverse of Trend is displayed under the bar. Custom filters allow users to ignore insignificant moves by setting a minimum body size (as % of price) and a minimum volume threshold. 📌 Use cases: Spot momentum shifts when price and volume expand together. Identify weakening moves when both price action and volume contract. Can be combined with other strategies for confirmation of entries or exits. ⚙️ Inputs: Minimum Body Size % (of price): Filters out small candles. Minimum Volume: Ensures only significant moves are marked. This indicator is best used as a confirmation tool within a larger trading strategy, rather than as a standalone buy/sell signal.
Pine Script®指標
由arisdet提供
Session Pivots + EMA20/50 + Bollinger BandsMulti-tool indicator combining session pivots, EMA trend filters, Bollinger Bands, and alerts for intraday trading. 📌 Description One of the biggest advantages of this indicator is that it supports TradingView’s ALERT system, so traders can be notified the moment price crosses the daily/session pivot level. This allows faster decision-making without constant chart watching. This script combines three powerful tools into a single indicator: Session Pivot Levels (with Support/Resistance): Automatically calculates pivot, R1–R3 and S1–S3 levels based on the previous trading session (London, New York, Asia, or custom). Levels are plotted with clean labels and connector lines so you always see the exact price values ahead of time. EMA Trend Filters (20 & 50): Tracks short- and medium-term market direction with two popular exponential moving averages, helping confirm entries and exits. Bollinger Bands (fully customizable): Adds volatility bands with choice of SMA, EMA, SMMA, WMA, or VWMA for the middle line, plus adjustable standard deviation and offset. ✅ Key Features Auto-detects London, New York, and Asian sessions or set your own custom session. Displays up to 3 levels of support and resistance from the previous session. Clean label display with customizable theme options (Dark, Light, Custom). Alerts included: Get notified instantly when price crosses above or below the Pivot. EMA20/50 trend confirmation built-in. Bollinger Bands with multiple moving average types and volatility settings. Works for Forex, Crypto, Indices, Commodities — optimized for intraday & scalping. This makes it a complete intraday toolkit, reducing the need to load multiple separate indicators. 📄 Full documentation available here: [ link ]
Pine Script®指標
由FarhadCCM提供