始めましょう

"META股价历史数据"に関するスクリプトを検索

Bulls and BearsThis is a standard 'Bulls and Bears Power" Oscillator, how ever,... There are two different formulas for calculating bulls and bears, the standard version, uses Highest and Lowest of prices in a given period, BUT, the version we have in meta trader platform, uses the current high and current low for each bar. Within this indicator, you can use the standard version or the meta trader version, it will draw both bulls and bears and you can turn each one on and off in the style section.
Pine Script® インジケーター
moaserの投稿
ATR based Pivots mcbwHey everyone this is an exciting new script I have prepared for you. I was reading an old forex bulletin article some time ago when I came across this: solar.murty.net (or you can download the full bulletin with lots of other good articles here: www.forexfactory.com). You can already buy this for metatrader (www.mql5.com) so I figured to make it for free for tradingview. This bulletin suggested that you can reasonably predict daily volatility by adding or subtracting multiples of the daily ATR to the daily opening. Using this you can choose multiples to use as price targets and alternatively as stop losses. For example, if you already have a sense of market direction you can buy at market open place a stop loss at - 1 daily ATR and a profit target at + 3 ATRs for a risk to reward ratio of 3. If you are looking for smaller/quicker moves with a ratio of 3 you can have a stop loss at -0.25 ATR and a take profit at +0.75 ATR. Alternatively this article also suggests to use this method to catch volatility breakouts. If price is higher than the + 1 ATR area then you can safely assume it will be going to the +2 ATR area so you can put a buy stop at + 1 ATR with a profit target at + 2 ATR with a stop loss at +0.5 ATR to catch a volatility breakout with a risk to reward ratio of 2! Even further there are methods that you can use with ATRs of multiple window sizes, for example by opening two copies of this indicator and measuring recent volatility with a 1 week window and long term volatility within a 1 month window. If the short term volatility is crossing the long term volatility then there is a high probability chance that even more price movement will occur. However I have found that this method is good for more than daily volatility , it can also be used to measure weekly volatility , and monthly volatility and use these multiples as good long term price targets. To select if you want daily, weekly, or monthly values of the ATR of volatility you're using go to the settings and click on the options in the "Opening period". The default window of the ATR here is 14 periods, but you can change this if you want to in "ATR period". Most importantly you are able to select which multiples of the ATR you would like to use in the settings in "ATR multiple 1" which is the green line, "ATR multiple 2" which is the blue line, and "ATR multiple 3" which is the purple line. You can select any values you want to put in these, the choice of 0.25, 0.5, and 1 is not special, some people use fibonacci numbers here or simply 0.33, 0.66, and 0.99. Repainting issue: This script uses the daily value of the Average True Range (ATR), which measures the volatility that is happening today. If price becomes more volatile then the value of the ATR can increase throughout the day, but it can never decrease. What this means is that the ATR based pivots are able to expand away from the opening price, which should not affect the trades that you take based on these areas. If you base your take profit on one of these ATR multiples and the daily volatility increase this means that your take profit area will be closer to your entry than the ATR multiple. Meaning that your trades will be more conservative. While this all may sound very technical it is super intuitive, throw this on your chart and play around with it :) Happy trading!
Pine Script® インジケーター
mcbw_の投稿
7
Waddah Attar Explosion [LazyBear]This is a port of a famous MT4 indicator, as requested by user @maximus71. This indicator uses MACD/BB to track trend direction and strength. Author suggests using this indicator on 30mins. Explanation from the indicator developer: "Various components of the indicator are: Dead Zone Line: Works as a filter for weak signals. Do not trade when the red or green histogram is below it. Histograms: - Red histogram shows the current down trend. - Green histogram shows the current up trend. - Sienna line shows the explosion in price up or down. Signal for ENTER_BUY: All the following conditions must be met. - Green histo is raising. - Green histo above Explosion line. - Explosion line raising. - Both green histo and Explosion line above DeadZone line. Signal for EXIT_BUY: Exit when green histo crosses below Explosion line. Signal for ENTER_SELL: All the following conditions must be met. - Red histo is raising. - Red histo above Explosion line. - Explosion line raising. - Both red histo and Explosion line above DeadZone line. Signal for EXIT_SELL: Exit when red histo crosses below Explosion line. " All of the parameters are configurable via options page. You may have to tune it for your instrument. More info: Author note: www.forex-tsd.com Video (French): www.youtube.com List of my other indicators: - GDoc: docs.google.com - Chart:
Pine Script® インジケーター
LazyBearの投稿
39
SITFX_FuturesSpec_v17SITFX_FuturesSpec_v17 – Universal Futures Contract Library Full-scale futures contract specification library for Pine Script v6. Covers CME, CBOT, NYMEX, COMEX, CFE, Eurex, ICE, and more – including minis, micros, metals, energies, FX, and bonds. Key Features: ✅ Instrument‑agnostic: ES/MES, NQ/MNQ, YM/MYM, RTY/M2K, metals, energies, FX, bonds ✅ Full contract data: Tick size, tick value, point value, margins ✅ Continuation‑safe: Single‑line logic, no arrays or continuation errors ✅ Foundation for SITFX tools: Gann, Fibs, structure, and risk modules Usage example: import SITFX_FuturesSpec_v17/1 as fs spec = fs.get(syminfo.root) label.new(bar_index, high, str.format("{0}: Tick={1}, Value=${2}", spec.name, spec.tickSize, spec.tickValue))
Pine Script® ライブラリ
Solvereの投稿
Quantum Harmonic Oscillator Overlay🧪 Quantum Harmonic Oscillator Overlay A visual model of price behavior using quantum harmonic oscillation principles 📜 Indicator Overview The Quantum Harmonic Oscillator Overlay applies concepts from both classical physics (harmonic motion) and quantum mechanics (energy states) to model and visualize how price orbits around a central trend line. It overlays a Linear Regression line (representing the “mean position” or ground state of price) and calculates surrounding energy levels (σ-zones) akin to quantum shells that price can "jump" between. This indicator is particularly useful for visualizing mean reversion, volatility compression/expansion, and momentum-driven price breakthroughs. 🧠 Core Concepts Linear Regression Line (LSR): This is the calculated center of gravity or equilibrium path of price over a user-defined period. Think of it like the lowest energy state or central axis around which price vibrates. Standard Deviation Zones (σ-levels): 1σ: The majority of normal price activity; within this range, price tends to fluctuate if in balance. 2σ: Indicates volatility or possible breakout pressure. 3σ: Represents extreme movement — a phase shift in energy, potentially leading to reversal or continuation with higher momentum. Quantum Analogy: Just like in a quantum harmonic oscillator, particles (here, prices) move probabilistically between discrete energy states. The further the price moves from the center, the more "energy" (momentum, volume, volatility) is implied. ⚙️ Input Parameters Setting Description Linear Regression Length The number of bars used to calculate the regression trend (default 100). Affects the central path and responsiveness. σ Multipliers (1σ, 2σ, 3σ) Determine how far each band is from the regression line. Adjusting these can highlight different price behaviors. Show Energy Level Zones Toggle visibility of the colored bands around the regression line. Show LSR Center Line Toggles visibility of the white Linear Regression line itself. 🎨 Visual Components Color Zone Interpretation ✅ Green ±1σ Normal oscillation / mean reversion area. Ideal for range-bound strategies. 🟧 Orange ±2σ Warning zone; price may be gaining momentum or volatility. 🔴 Red ±3σ High-momentum state or anomaly. These regions may imply trend exhaustion, reversals, or breakouts. White Line: The LSR — the average trajectory of the price movement. Pink Dots: Appear when price exceeds Zone 3 (outside ±3σ) — a signal of extreme behavior or a possible regime shift. 📈 How to Use This Indicator 1. Detect Overextensions When price touches or breaches the 3σ zone, it is likely overextended. This can be used to anticipate potential snapbacks or strong breakout trends. 2. Identify Mean Reversion Trades If price exits the 2σ or 3σ zones and returns toward the center line, this signals a likely mean reversion setup. 3. Volatility Compression or Expansion Flat zones between σ levels suggest calm markets; widening bands suggest expanding volatility. 4. Use with Confirmation Tools Combine with momentum oscillators (MACD, RSI) or volume-based signals to confirm reversals or continuation outside Zone 3. 🔮 Philosophical Note This indicator embodies the metaphor that the market behaves like a quantum oscillator — price particles exist in a probabilistic field and jump between discrete zones of volatility and energy. Tracking these transitions allows the trader to see price behavior as rhythmic, wave-like, and multidimensional rather than purely linear.
Pine Script® インジケーター
Eyemaginativeの投稿
Chaithanya Tattva Volume Zones📜 "Chaitanya Tattva" Volume Zones:- A Sacred Framework of Supply, Demand & Market Energy In the world of financial markets, price is said to reflect all information. But the true pulse of the market — its life force, its intent, and its moment of truth — is most vividly expressed not in price itself, but in volume. Chaitanya Tattva Volume Zones is a spiritually inspired volume-based tool that transforms your chart into a canvas of market consciousness, revealing moments where supply and demand engage in visible energetic spikes. These moments are often disguised as ordinary candles, but with this tool, you uncover zones of intent — footprints left by the market’s deeper intelligence. 🌟 Why “Chaitanya Tattva”? Chaitanya (चैतन्य) is a Sanskrit word meaning consciousness, awareness, or the spark of life energy. It is that which animates — the subtle intelligence behind all movement. Tattva (तत्त्व) refers to essence, truth, or the underlying principle of a thing. In classical yogic philosophy, the tattvas are the elemental building blocks of reality. Together, Chaitanya Tattva represents the conscious essence — the living pulse that animates the market through volume surges and imbalances. This tool is not just a technical indicator — it is a spiritual observation device that aligns with the rhythm of volume and price action. It doesn't predict the market. It reveals when the market has already spoken — loudly, clearly, and energetically. 📈 What Does the Tool Do? Chaitanya Tattva Volume Zones identifies exceptional volume spikes within the recent price history and visually marks the areas where market intent has been most active. Specifically, the tool: Scans for volume spikes that exceed all the volume of the last N bars (default is 20) Confirms whether the spike happened on a bullish candle (close > open) or bearish candle (close < open) For a bullish spike, it marks a Supply Zone — the area between the high and close of the candle For a bearish spike, it marks a Demand Zone — the area between the low and close Visually paints these zones with soft translucent boxes (red for supply, green for demand) that extend forward across multiple bars 🧘‍♂️ The Spiritual Framework 🔴 Supply = "Agni" — The Fire of Expansion When a bullish candle erupts with historically high volume, it symbolizes the fire (Agni) of market optimism and upward expansion. It means that buyers have absorbed available supply at that level and established dominance — but such fire may also signal exhaustion, making it a potential supply barrier if price returns. These Supply Zones are areas where: Sellers are likely to re-engage Smart money may be unloading Future resistance can be anticipated But unlike traditional indicators, this tool doesn’t guess. It reacts only to a clear volume-based event — when market energy surges — and locks in that awareness through zone marking. 🟢 Demand = "Prithvi" — The Grounding of Price On the other hand, a bearish candle with extremely high volume represents the Earth (Prithvi) — grounding the price with firm hands. A strong volume drop often means buyers are stepping in, absorbing the selling pressure. These Demand Zones are areas where: Buying interest is proven Market memory is stored Future support can be expected By respecting these zones, you're aligning your trading with natural market boundaries — not theoretical ones. 🧠 How Is It Different from Regular Volume Tools? While most volume indicators show bars on a lower panel, they leave interpretation up to the trader. “High” or “low” becomes subjective. Chaitanya Tattva Volume Zones is different: It quantifies "spike": a bar must exceed all previous N volumes It qualifies the intent: was the spike bullish or bearish? It marks zones on the price chart: no need to guess levels It preserves market memory: the zones persist visually for easy reference In essence, this tool doesn’t just report volume — it interprets volume’s context and visually encodes it into the chart. 🧘 How to Use 1. Support/Resistance Mapping Use the tool to understand where volume proved itself. If price revisits a red zone, expect possible rejection (resistance). If price revisits a green zone, expect possible absorption (support). 2. Entry Triggers You may enter: Long near demand zones if bullish confirmation appears Short near supply zones if bearish confirmation appears 3. Stop Placement Stops can be placed just beyond the zone boundary to align with areas where smart money historically defended. 4. Breakout Confidence When price breaks through one of these zones with momentum, it often signals a new energetic wave — the old balance has been overcome. 🔔 Key Features Volume spike detection across any timeframe Clear visual zones — no clutter, no lag Highly customizable: zone width, volume lookback, colors Philosophy-aligned with supply and demand theory, Wyckoff, and Order Flow 🌌 A Metaphysical View of Volume In yogic science, volume is akin to Prana — life-force energy. A market is not moved by price alone but by intent, force, and participation — all encoded in volume. Just as a human body pulses with blood when action intensifies, the market pulses with volume when institutional decisions are made. These pulses become sacred footprints — and Chaitanya Tattva Volume Zones helps you walk mindfully among them. 🔮 Final Thoughts In a sea of indicators that shout at you with every tick, Chaitanya Tattva is calm. It speaks only when energy concentrates, only when the market sends a signal born of intent. It doesn’t predict. It doesn’t repaint. It simply shows the truth, when the truth becomes undeniable. Like a sage that speaks only when needed, it waits for volume to prove itself — then draws a memory into space, a zone where traders can re-align their actions with what the market has already honored. Use it not just to trade — But to listen. To observe. To follow the Chaitanya — the conscious pulse of the market’s own breath.
Pine Script® インジケーター
TradingSpiritualの投稿
Ergodic Market Divergence (EMD)Ergodic Market Divergence (EMD) Bridging Statistical Physics and Market Dynamics Through Ensemble Analysis The Revolutionary Concept: When Physics Meets Trading After months of research into ergodic theory—a fundamental principle in statistical mechanics—I've developed a trading system that identifies when markets transition between predictable and unpredictable states. This indicator doesn't just follow price; it analyzes whether current market behavior will persist or revert, giving traders a scientific edge in timing entries and exits. The Core Innovation: Ergodic Theory Applied to Markets What Makes Markets Ergodic or Non-Ergodic? In statistical physics, ergodicity determines whether a system's future resembles its past. Applied to trading: Ergodic Markets (Mean-Reverting) - Time averages equal ensemble averages - Historical patterns repeat reliably - Price oscillates around equilibrium - Traditional indicators work well Non-Ergodic Markets (Trending) - Path dependency dominates - History doesn't predict future - Price creates new equilibrium levels - Momentum strategies excel The Mathematical Framework The Ergodic Score combines three critical divergences: Ergodic Score = (Price Divergence × Market Stress + Return Divergence × 1000 + Volatility Divergence × 50) / 3 Where: Price Divergence: How far current price deviates from market consensus Return Divergence: Momentum differential between instrument and market Volatility Divergence: Volatility regime misalignment Market Stress: Adaptive multiplier based on current conditions The Ensemble Analysis Revolution Beyond Single-Instrument Analysis Traditional indicators analyze one chart in isolation. EMD monitors multiple correlated markets simultaneously (SPY, QQQ, IWM, DIA) to detect systemic regime changes. This ensemble approach: Reveals Hidden Divergences: Individual stocks may diverge from market consensus before major moves Filters False Signals: Requires broader market confirmation Identifies Regime Shifts: Detects when entire market structure changes Provides Context: Shows if moves are isolated or systemic Dynamic Threshold Adaptation Unlike fixed-threshold systems, EMD's boundaries evolve with market conditions: Base Threshold = SMA(Ergodic Score, Lookback × 3) Adaptive Component = StDev(Ergodic Score, Lookback × 2) × Sensitivity Final Threshold = Smoothed(Base + Adaptive) This creates context-aware signals that remain effective across different market environments. The Confidence Engine: Know Your Signal Quality Multi-Factor Confidence Scoring Every signal receives a confidence score based on: Signal Clarity (0-35%): How decisively the ergodic threshold is crossed Momentum Strength (0-25%): Rate of ergodic change Volatility Alignment (0-20%): Whether volatility supports the signal Market Quality (0-20%): Price convergence and path dependency factors Real-Time Confidence Updates The Live Confidence metric continuously updates, showing: - Current opportunity quality - Market state clarity - Historical performance influence - Signal recency boost - Visual Intelligence System Adaptive Ergodic Field Bands Dynamic bands that expand and contract based on market state: Primary Color: Ergodic state (mean-reverting) Danger Color: Non-ergodic state (trending) Band Width: Expected price movement range Squeeze Indicators: Volatility compression warnings Quantum Wave Ribbons Triple EMA system (8, 21, 55) revealing market flow: Compressed Ribbons: Consolidation imminent Expanding Ribbons: Directional move developing Color Coding: Matches current ergodic state Phase Transition Signals Clear entry/exit markers at regime changes: Bull Signals: Ergodic restoration (mean reversion opportunity) Bear Signals: Ergodic break (trend following opportunity) Confidence Labels: Percentage showing signal quality Visual Intensity: Stronger signals = deeper colors Professional Dashboard Suite Main Analytics Panel (Top Right) Market State Monitor - Current regime (Ergodic/Non-Ergodic) - Ergodic score with threshold - Path dependency strength - Quantum coherence percentage Divergence Metrics - Price divergence with severity - Volatility regime classification - Strategy mode recommendation - Signal strength indicator Live Intelligence - Real-time confidence score - Color-coded risk levels - Dynamic strategy suggestions Performance Tracking (Left Panel) Signal Analytics - Total historical signals - Win rate with W/L breakdown - Current streak tracking - Closed trade counter Regime Analysis - Current market behavior - Bars since last signal - Recommended actions - Average confidence trends Strategy Command Center (Bottom Right) Adaptive Recommendations - Active strategy mode - Primary approach (mean reversion/momentum) - Suggested indicators ("weapons") - Entry/exit methodology - Risk management guidance - Comprehensive Input Guide Core Algorithm Parameters Analysis Period (10-100 bars) Scalping (10-15): Ultra-responsive, more signals, higher noise Day Trading (20-30): Balanced sensitivity and stability Swing Trading (40-100): Smooth signals, major moves only Default: 20 - optimal for most timeframes Divergence Threshold (0.5-5.0) Hair Trigger (0.5-1.0): Catches every wiggle, many false signals Balanced (1.5-2.5): Good signal-to-noise ratio Conservative (3.0-5.0): Only extreme divergences Default: 1.5 - best risk/reward balance Path Memory (20-200 bars) Short Memory (20-50): Recent behavior focus, quick adaptation Medium Memory (50-100): Balanced historical context Long Memory (100-200): Emphasizes established patterns Default: 50 - captures sufficient history without lag Signal Spacing (5-50 bars) Aggressive (5-10): Allows rapid-fire signals Normal (15-25): Prevents clustering, maintains flow Conservative (30-50): Major setups only Default: 15 - optimal trade frequency Ensemble Configuration Select markets for consensus analysis: SPY: Broad market sentiment QQQ: Technology leadership IWM: Small-cap risk appetite DIA: Blue-chip stability More instruments = stronger consensus but potentially diluted signals Visual Customization Color Themes (6 professional options): Quantum: Cyan/Pink - Modern trading aesthetic Matrix: Green/Red - Classic terminal look Heat: Blue/Red - Temperature metaphor Neon: Cyan/Magenta - High contrast Ocean: Turquoise/Coral - Calming palette Sunset: Red-orange/Teal - Warm gradients Display Controls: - Toggle each visual component - Adjust transparency levels - Scale dashboard text - Show/hide confidence scores - Trading Strategies by Market State - Ergodic State Strategy (Primary Color Bands) Market Characteristics - Price oscillates predictably - Support/resistance hold - Volume patterns repeat - Mean reversion dominates Optimal Approach Entry: Fade moves at band extremes Target: Middle band (equilibrium) Stop: Just beyond outer bands Size: Full confidence-based position Recommended Tools - RSI for oversold/overbought - Bollinger Bands for extremes - Volume profile for levels - Non-Ergodic State Strategy (Danger Color Bands) Market Characteristics - Price trends persistently - Levels break decisively - Volume confirms direction - Momentum accelerates Optimal Approach Entry: Breakout from bands Target: Trail with expanding bands Stop: Inside opposite band Size: Scale in with trend Recommended Tools - Moving average alignment - ADX for trend strength - MACD for momentum - Advanced Features Explained Quantum Coherence Metric Measures phase alignment between individual and ensemble behavior: 80-100%: Perfect sync - strong mean reversion setup 50-80%: Moderate alignment - mixed signals 0-50%: Decoherence - trending behavior likely Path Dependency Analysis Quantifies how much history influences current price: Low (<30%): Technical patterns reliable Medium (30-50%): Mixed influences High (>50%): Fundamental shift occurring Volatility Regime Classification Contextualizes current volatility: Normal: Standard strategies apply Elevated: Widen stops, reduce size Extreme: Defensive mode required Signal Strength Indicator Real-time opportunity quality: - Distance from threshold - Momentum acceleration - Cross-validation factors Risk Management Framework Position Sizing by Confidence 90%+ confidence = 100% position size 70-90% confidence = 75% position size 50-70% confidence = 50% position size <50% confidence = 25% or skip Dynamic Stop Placement Ergodic State: ATR × 1.0 from entry Non-Ergodic State: ATR × 2.0 from entry Volatility Adjustment: Multiply by current regime Multi-Timeframe Alignment - Check higher timeframe regime - Confirm ensemble consensus - Verify volume participation - Align with major levels What Makes EMD Unique Original Contributions First Ergodic Theory Trading Application: Transforms abstract physics into practical signals Ensemble Market Analysis: Revolutionary multi-market divergence system Adaptive Confidence Engine: Institutional-grade signal quality metrics Quantum Coherence: Novel market alignment measurement Smart Signal Management: Prevents clustering while maintaining responsiveness Technical Innovations Dynamic Threshold Adaptation: Self-adjusting sensitivity Path Memory Integration: Historical dependency weighting Stress-Adjusted Scoring: Market condition normalization Real-Time Performance Tracking: Built-in strategy analytics Optimization Guidelines By Timeframe Scalping (1-5 min) Period: 10-15 Threshold: 0.5-1.0 Memory: 20-30 Spacing: 5-10 Day Trading (5-60 min) Period: 20-30 Threshold: 1.5-2.5 Memory: 40-60 Spacing: 15-20 Swing Trading (1H-1D) Period: 40-60 Threshold: 2.0-3.0 Memory: 80-120 Spacing: 25-35 Position Trading (1D-1W) Period: 60-100 Threshold: 3.0-5.0 Memory: 100-200 Spacing: 40-50 By Market Condition Trending Markets - Increase threshold - Extend memory - Focus on breaks Ranging Markets - Decrease threshold - Shorten memory - Focus on restores Volatile Markets - Increase spacing - Raise confidence requirement - Reduce position size - Integration with Other Analysis - Complementary Indicators For Ergodic States - RSI divergences - Bollinger Band squeezes - Volume profile nodes - Support/resistance levels For Non-Ergodic States - Moving average ribbons - Trend strength indicators - Momentum oscillators - Breakout patterns - Fundamental Alignment - Check economic calendar - Monitor sector rotation - Consider market themes - Evaluate risk sentiment Troubleshooting Guide Too Many Signals: - Increase threshold - Extend signal spacing - Raise confidence minimum Missing Opportunities - Decrease threshold - Reduce signal spacing - Check ensemble settings Poor Win Rate - Verify timeframe alignment - Confirm volume participation - Review risk management Disclaimer This indicator is for educational and informational purposes only. It does not constitute financial advice. Trading involves substantial risk of loss and is not suitable for all investors. Past performance does not guarantee future results. The ergodic framework provides unique market insights but cannot predict future price movements with certainty. Always use proper risk management, conduct your own analysis, and never risk more than you can afford to lose. This tool should complement, not replace, comprehensive trading strategies and sound judgment. Markets remain inherently unpredictable despite advanced analysis techniques. Transform market chaos into trading clarity with Ergodic Market Divergence. Created with passion for the TradingView community Trade with insight. Trade with anticipation. — Dskyz , for DAFE Trading Systems
Pine Script® インジケーター
DskyzInvestmentsの投稿
7
Walk Forward PatternsINTRO In Euclidean geometry, every mathematical output has a planar projection. 'Walk Forward Patterns' can be considered a practical example of this concept. On the other hand, this indicator might also be viewed as an experiment in 'how playing with Lego as a child contributes to time series analysis' :) OVERVIEW This script dynamically generates the necessary optimization and testing ranges for Walk Forward Analysis based on user-defined bar count and length inputs. It performs automatic calculations for each step, offers 8 different window options depending on the inputs, and visualizes the results dynamically. I should also note that most of the window models consist of original patterns I have created. ADDITIONAL INFO : WHAT IS WALK FORWARD ANALYSIS? Although it is not the main focus of this indicator, providing a brief definition of Walk Forward Analysis can be helpful in correctly interpreting the results it generates. Walk Forward Analysis (WFA) is a systematic method for optimizing parameters and validating trading strategies. It involves dividing historical data into variable segments, where a strategy is first optimized on an in-sample period and then tested on an out-of-sample period. This process repeats by shifting the windows forward, ensuring that each test evaluates the strategy on unseen data, helping to assess its robustness and adaptability in real market conditions. ORIGINALITY There are very few studies on Walk Forward Analysis in TradingView. Even worse, there are no any open-source studies available. Someone has to start somewhere, I suppose. And in my personal opinion, determining the optimization and backtest intervals is the most challenging part of WFA. These intervals serve as a prerequisite for automated parameter optimization. I felt the need to publish this pattern module, which I use in my own WFA models, partly due to this gap on community scripts. INDICATOR MECHANICS To use the indicator effectively, you only need to perform four simple tasks: Specify the total number of bars in your chart in the 'Bar Index' parameter. Define the optimization (In-Sample Test) length. Define the testing (Out-Of-Sample Test) length. Finally, select the window type. The indicator automatically models everything else (including the number of steps) based on your inputs. And the result; you now have a clear idea of which bars to use for your Walk Forward tests! A COMMONLY USED WINDOW SELECTION METHOD: ROLLING A more concrete definition of Walk Forward Analysis, specifically for the widely used Rolling method, can be described as follows: Parameters that have performed well over a certain period are identified (Optimization: In-Sample). These parameters are then tested on a shorter, subsequent period (Backtest: Out-of-Sample). The process is repeated forward in time (At each step, the optimization and backtest periods are shifted by the backtest length). If the cumulative percentage profit obtained from the backtest results is greater than half of the historical optimization profit, the strategy is considered "successful." If the strategy is successful, the most recent (untested) optimization values are used for live trading. OTHER WINDOW OPTIONS ANCHORED: That's a pattern based on progressively expanding optimization ranges at each step. Backtest ranges move forward in a staircase-like manner. STATIC: Optimization ranges remain fixed, while backtest ranges are shifted forward. BLOCKED: Optimization ranges are shifted forward in groups of three blocks. Backtest ranges are also shifted in a staircase manner, even at the cost of creating gaps from the optimization end bars. TRIANGULAR: Optimization ranges are shifted forward in triangular regions, while backtest ranges move in a staircase pattern. RATIO: The optimization length increases by 25% of the initial step’s fixed length at each step. In other words, the length grows by 25% of the first step's length incrementally. Backtest ranges always start from the bar where the optimization ends. FIBONACCI: A variation of the Ratio method, where the optimization shift factor is set to 0.618 RANDOM WALK Unlike the window models explained above, we can also generate optimization and backtest ranges completely randomly—offering almost unlimited variations! When you select the "Random" option in the "Window" parameter on the indicator interface, random intervals are generated based on various trigonometric calculations. By changing the numerical value in the '🐒' parameter, you can create entirely unique patterns. WHY THE 🐒 EMOJI? Two reasons. First, I think that as humanity, we are a species of tailless primates who become happy when we understand things :). At least evolutionarily. The entire history of civilization is built on the effort to express the universe in a scale we can comprehend. 'Knowledge' is an invention born from this effort, which is why we feel happiness when we 'understand'. Second, I can't think of a better metaphor for randomness than a monkey sitting at a keyboard. See: Monkey Test. Anyway, I’m rambling :) NOTES The indicator generates results for up to 100 steps. As the number of steps increases, the table may extend beyond the screen—don’t forget to zoom out! FINAL WORDS I haven’t published a Walk Forward script yet . However, there seem to be examples that can perform parameter optimization in the true sense of the word, producing more realistic results without falling into overfitting in my library. Hopefully, I’ll have the chance to publish one in the coming weeks. Sincerely thanks to Kıvanç Özbilgiç, Robert Pardo, Kevin Davey, Ernest P. Chan for their inspiring publishments. DISCLAIMER That's just a script, nothing more. I hope it helps everyone. Do not forget to manage your risk. And trade as safely as possible. Best of luck! © dg_factor
Pine Script® インジケーター
dg_factorの投稿
1
MMRI Chart (Primary)The **Mannarino Market Risk Indicator (MMRI)** is a financial risk measurement tool created by financial strategist Gregory Mannarino. It’s designed to assess the risk level in the stock market and economy based on current bond market conditions and the strength of the U.S. dollar. The MMRI considers factors like the U.S. 10-Year Treasury Yield and the Dollar Index (DXY), which indicate investor confidence in government debt and the dollar's purchasing power, respectively. The formula for MMRI uses the 10-Year Treasury Yield multiplied by the Dollar Index, divided by a constant (1.61) to normalize the risk measure. A higher MMRI score suggests increased market risk, while a lower score indicates more stability. Mannarino has set certain thresholds to interpret the MMRI score: - **Below 100**: Low risk. - **100–200**: Moderate risk. - **200–300**: High risk. - **Above 300**: Extreme risk, indicating market instability and potential downturns. This tool aims to provide insight into economic conditions that may affect asset classes like stocks, bonds, and precious metals. Mannarino often updates MMRI scores and risk analyses in his public market updates.
Pine Script® インジケーター
Emilio2014の投稿
[Pandora] Error Function Treasure Trove - ERF/ERFI/Sigmoids+PRAISE: At this time, I have to graciously thank the wonderful minds behind the new "Pine Profiler Mode" (PPM). Directly prior to this release, it allowed me to ascertain script performance even more. While I usually write mostly in highly optimized Pine code, PPM visually identified a few bottlenecks that would otherwise be hard to identify. Anyone who contributed to PPMs creation and testing before release... BRAVO!!! I commend all of those who assisted in it's state-of-the-art engineering and inception, well done! BACKSTORY: This script is specifically being released in defense of another member, an exceptionally unique PhD. It was brought to my attention that a script-mod-event occurred, regarding the publishing of a measly antiquated error function (ERF) calculation within his script. This sadly resulted in the now former member jumping ship after receiving unmannerly responses amidst his curious inquiries as to why his erf() was modded. To forbid rusty and rudimentary formulations because a mod-on-duty is temporally offended by a non-nefarious release of code, is in MY opinion an injustice to principles of perpetuating open-source code intended to benefit thousands to millions of community members. While Pine is the heart and soul of TV, the mathematical concepts contributed from the minds of members is the inspirational fuel of curiosity that powers it's pertinent reason to exist and evolve. It is an indisputable fact that most members are not greatly skilled Pine Poets. Many members may be incapable of innovating robust function code in Pine, even if they have one or more PhDs. We ALL come from various disciplines of mathematical comprehension and education. Some mathematicians are not greatly skilled at coding, while some coders are not exceptional at math. So... what am I to do to attempt to resolve this circumstantial challenge??? Those who know me best are aware that I will always side with "the right side of history" in order to accomplish my primary self-defined missions I choose to accept. Serving as an algorithmic advocate, I felt compelled to intercede by compiling numerous error functions into elegant code of very high caliber that any and every TV member may choose to employ, so this ERROR never happens again. After weeks of contemplation into algorithms I knew little about, I prioritized myself to resolve an unanticipated matter by creating advanced formulas of exquisitely crafted error functions refined to the best of my current abilities. My aversion for unresolved problems motivated me to eviscerate error function insufficiencies with many more rigid formulations beyond what is thought to exist. ERF needed a proper algorithmic exorcism anyways. In my furiosity, I contemplated an array of madMAXimum diplomatic demolition methods, choosing the chain saw massacre technique to slaughter dysfunctionalities I encountered on a battered ERF roadway. This resulted in prolific solutions that should assuredly endure the test of time. Poetically, as you will come to see, I am ripping the lid off of Pandora's box of error functions in this case to correct wrongs into a splendid bundle of rights for members. INTENTION: Error function (ERF) enthusiasts... PREPARE FOR GLORY!! The specific purpose of this script is to deprecate classic error functions with the creation of a fierce and formidable army of superior formulations, each having varying attributes of computational complexity with differing absolute error ranges in their results for multiple compute scenarios. This is NOT an indicator... It is intended to allow members to embark on endeavors to advance the profound knowledge base of this growing worldwide community of 60+ million inquisitive minds. For those of you who believe computational mathematics and statistics is near completion at its finest; I am here to inform you, this is ridiculous to ponder. We are no where near statistical excellence that can and will exist eventually. At this time, metaphorically speaking, we are merely scratching microns off of the surface of the skin of a statistical apple Isaac Newton once pondered. THIS RELEASE: Following weeks of pondering methodical experiments beyond the ordinary, I am liberating these wild notions of my error function explorations to the entire globe as copyleft code, not just Pine. This Pandora's basket of ERFs is being openly disclosed for the sake of the sanctity of mathematics, empirical science (not the garbage we are told by CONTROLocrats to blindly trust), revolutionary cutting edge engineering, cosmology, physics, information technology, artificial intelligence, and EVERY other mathematical branch of human knowledge being discovered over centuries. I do believe James Glaisher would favor my aims concerning ERF aspirations embracing the "Power of Pine". The included functions are intended for TV members to use in any way they see fit. This is a gift to ALL members to foster future innovative excellence on this platform. Any attempt to moderate this code without notification of "self-evident clear and just cause" will be considered an irrevocable egregious action. The original foundational PURPOSE of establishing script moderation (I clearly remember) was primarily to maintain active vigilance over a growing community against intentional nefarious actions and/or behaviors in blatant disrespect to other author's works AND also thwart rampant copypasting bandit operations, all while accommodating balanced principles of fairness for an educational community cause via open source publishing that should support future algorithmic inventions well beyond my lifespan. APPLICATIONS: The related error functions are used in probability theory, statistics, and numerous and engineering scientific disciplines. Its key characteristics and applications are innumerable in computational realms. Its versatility and significance make it a fundamental tool in arenas of quantitative analysis and scientific research... Probability Theory - Is widely used in probability theory to calculate probabilities and quantiles of the normal distribution. Statistics - It's related to the Gaussian integral and plays a crucial role in statistics, especially in hypothesis testing and confidence interval calculations. Physics - In physics, it arises in the study of diffusion equations, quantum mechanics, and heat conduction problems. Engineering - Applications exist in engineering disciplines such as signal processing, control theory, and telecommunications. Error Analysis - It's employed in error analysis and uncertainty quantification. Numeric Approximations - Due to its lack of a closed-form expression, numerical methods are often employed to approximate erf/erfi(). AI, LLMs, & MACHINE LEARNING: The error function (ERF) is indispensable to various AI applications, particularly due to its relation to Gaussian distributions and error analysis. It is used in Gaussian processes for regression and classification, probabilistic inference for Bayesian networks, soft margin computation in SVMs, neural networks involving Gaussian activation functions or noise, and clustering algorithms like Gaussian Mixture Models. Improved ERF approximations can enhance precision in these applications, reduce computational complexity, handle outliers and noise better, and improve optimization and convergence, possibly leading to more accurate, efficient, and robust AI systems. BONUS ALGORITHMS: While ERFs are versatile, its opposite also exists in the form of inverse error functions (ERFIs). I have also included a modified form of the inverse fisher transform along side MY sigmoid (sigmyod). I am uncertain what sigmyod() may be used for, but it's a culmination of my examinations deep into "sigmoid domains", something I am fascinated by. Whatever implications it may possess, I am unveiling it along with it's cousin functions. For curious minds, this quality of composition seen here is ideally what underlies what I would term "Pandora functionality" that empowers my Pandora indication. I go through hordes of formulations, testing, and inspection to find what appears to be the most beneficial logical/mathematical equation to apply... SCRIPT OPERATION: To showcase the characteristics and performance of my ERF/ERFI formulations, I devised a multi-modal script. By using bar_index , I generated a broad sequence of numeric values to input into the first ERF/ERFI parameter. These sequences allow you to inspect the contours of the error function's outputs for both ERF and ERFI. When combined with compute-intensive precision functions (CIPFs), the polynomial function output values can be subtracted from my CIPFs to obtain results of absolute error, displaying the accuracy of the many polynomial estimation functions I tuned in testing for Pine's float environment. A host of numeric input settings are wildly adjustable to inspect values/curvatures across the range of numeric input sequences. Very large numbers, such as Divisor:100,000,100/Offset:200,000,000 for ERF modes or... Divisor:100,000,100/Offset:100,000,000 for ERFI modes, will display miniscule output values calculated from input values in close proximity to 0.0 for the various estimates, similar to a microscope. ERFI approximations very near in proximity to +/-1.0 will always yield large deviations of absolute error. Dragging/zooming your chart or using the Offset input will aid with visually clipping off those ERFI extremes where float precision functions cannot suffice. NOTICE: perf() and perfi() are intended for precision computation (as good as it basically gets) in a float environment. However, they are CPU intensive (especially perfi). I wouldn't recommend these being used in ANY Pine script unless it's an "absolute necessity" to do so to accomplish your goal. I only built them to obtain "absolute error curvatures" of the error functions for the polynomial approximations. These are visible in the accuracy modes in the indicator Settings.
Pine Script® インジケーター
ImmortalFreedomの投稿
7
Price SextantThe provided Pine Script™ code is for a technical analysis indicator called "Price Sextant." This indicator helps visualize the price position relative to its linear regression and standard deviation levels. Here's a brief description: Price Sextant Indicator: Purpose: The Price Sextant indicator aims to show the current price's deviation from the linear regression line by dividing the price chart into different zones or sextants. Components: Linear Regression: The script calculates a linear regression line based on the closing prices over a specified length (default is 50 bars). Standard Deviation Sections: It then computes standard deviation levels from the linear regression, creating upper and lower sections around the regression line. Scoring: Each section is assigned a numerical score, and labels with corresponding scores are displayed on the chart. Arrow and Midline: An arrow is drawn to indicate the current price's position in relation to the regression line and standard deviation bands. It changes color based in what section it is: orange section shows a ranging price, below orange section -1 arrow turns red and show down trend and if arrow above +1 section it turns green and show strong up trend of price. A midline is plotted to mark the position of the linear regression line. Sextant Description: In navigation, a sextant is an instrument used to measure the angle between two visible objects. In the context of this indicator, the term "Sextant" is likely used metaphorically to describe the division of the price chart into six sections or zones based on the linear regression and standard deviation bands. This indicator can help traders identify potential overbought or oversold conditions, as well as assess the strength and direction of the trend. Please note that the effectiveness of the indicator depends on various factors, and it's advisable to use it in conjunction with other analysis tools for a comprehensive trading strategy.
Pine Script® インジケーター
VanHe1singの投稿
4
COT MCIThe COT MCI script is a market indicator based on the data from the Commitment of Traders Reports. Integration of COT Report Data: The script sources COT data from futures contracts, including: Treasury Bonds (ZB), Dollar Index (DX), 10-Year Treasury Notes (ZN) Commodities like Soybeans (ZS), Soy Meal (ZM), Soy Oil (ZL), Corn (ZC), Wheat (ZW), Kansas City Wheat (KE), Pork (HE), Cattle (LE) Precious Metals such as Gold (GC), Silver (SI), Palladium (PA), Platinum (PL) Industrial Metals like Copper (HG), Aluminum (AUP), Steel (HRC) Energy Products like Crude Oil (CL), Heating Oil (HO), Gasoline (RB), Natural Gas (NG), Brent Crude (BB) Currencies such as AUD (6A), GBP (6B), CAD (6C), EUR (6E), JPY (6J), CHF (6S), NZD (6N), BRL (6L), MXN (6M), RUB (6R), ZAR (6Z) Others: Sugar (SB), Coffee (KC), Cocoa (CC), Cotton (CT), Ethanol (EH), Rice (ZR), Oats (ZO), Whey (DC), Orange Juice (OJ), Lumber (LBS), Livestock (GF), E-mini S&P 500 (ES), E-mini Russell 2000 (RTY), E-mini Dow Jones (YM), E-mini NASDAQ-100 (NQ), VIX Futures (VX), S&P 500 (SP), DJIA (DJIA) Cryptocurrencies such as Bitcoin (BTC) and Ethereum (ETH) Functions and Logic of the Script: COT Calculation: Determines the net positions for commercial actors and large speculators. Also Available are short and long positions of commercials or large speculators. Position Change Analysis: Analyzes the percentage changes in net positions and open interest data over a period of 6 weeks (Weekly Chart). Average Value Calculation: Determines short-term and long-term trend averages. Trend Analysis: Buy and sell signals (represented in colors) are based on linear regressions and average calculations. Usage and Application Examples: Ideal for traders looking for a detailed analysis of market dynamics and position changes in the futures market. Suitable for decision-making in transaction timing and assessing market sentiment. Usage Notes: Users should be familiar with the interpretation of COT data and basic concepts of futures trading. Particularly suitable for medium to long-term trading strategies.
Pine Script® インジケーター
ComJoTraderの投稿
4
[blackcat] L1 Volatility Quality Index (VQI)The Volatility Quality Index (VQI) is an indicator used to measure the quality of market volatility. Volatility refers to the extent of price changes in the market. VQI helps traders assess market stability and risk levels by analyzing price volatility. This introduction may be a bit abstract, so let me help you understand it with a comparative metaphor if you're not immersed in various technical indicators. Imagine you are playing a jump rope game, and you notice that sometimes the rope moves fast and other times it moves slowly. This is volatility, which describes the speed of the rope. VQI is like an instrument specifically designed to measure rope speed. It observes the movement of the rope and provides a numerical value indicating how fast or slow it is moving. This value can help you determine both the stability of the rope and your difficulty level in jumping over it. With this information, you know when to start jumping and when to wait while skipping rope. In trading, VQI works similarly. It observes market price volatility and provides a numerical value indicating market stability and risk levels for traders. If VQI has a high value, it means there is significant market volatility with relatively higher risks involved. Conversely, if VQI has a low value, it indicates lower market volatility with relatively lower risks involved as well. The calculation involves dividing the range by values obtained from calculating Average True Range (ATR) multiplied by a factor/multiple. The purpose of VQI is to assist traders in evaluating the quality of market volatility so they can develop better trading strategies accordingly. Therefore, VQI helps traders understand the quality of market volatility for better strategy formulation and risk management—just like adjusting your jumping style based on rope speed during jump-rope games; traders can adjust their trading decisions based on VQI values. The calculation of VQI indicator depends on given period length and multiple factors: Period length is used to calculate Average True Range (ATR), while the multiple factor adjusts the range of volatility. By dividing the range by values and multiplying it with a multiple, VQI numerical value can be obtained. VQI indicator is typically presented in the form of a histogram on price charts. Higher VQI values indicate better quality of market volatility, while lower values suggest poorer quality of volatility. Traders can use VQI values to assess the strength and reliability of market volatility, enabling them to make wiser trading decisions. It should be noted that VQI is just an auxiliary indicator; traders should consider other technical indicators and market conditions comprehensively when making decisions. Additionally, parameter settings for VQI can also be adjusted and optimized based on individual trading preferences and market characteristics.
Pine Script® インジケーター
blackcat1402の投稿
7
CE - 42MACRO Fixed Income and Macro This is Part 2 of 2 from the 42MACRO Recreation Series However, there will be a bonus Indicator coming soon! The CE - 42MACRO Fixed Income and Macro Table is a next level Macroeconomic and market analysis indicator. It aims to provide a probabilistic insight into the market realized GRID Macro regimes, track a multiplex of important Assets, Indices, Bonds and ETF's to derive extra market insights by showing the most important aggregates and their performance over multiple timeframes... and what that might mean for the whole market direction. For traders and especially investors, the unique functionalities will be of high value. Quick guide on how to use it: docs.google.com WARNING By the nature of the macro regimes, the outcomes are more accurate over longer Chart Timeframes (Week to Months). However, it is also a valuable tool to form an advanced, market realized, short to medium term bias. NOTE This Indicator is intended to be used alongside the 1nd part "CE - 42MACRO Equity Factor" for a more wholistic approach and higher accuracy. Methodology: The Equity Factor Table tracks specifically chosen Assets to identify their performance and add the combined performances together to visualize 42MACRO's GRID Equity Model. For this it uses the below Assets: Convertibles ( AMEX:CWB ) Leveraged Loans ( AMEX:BKLN ) High Yield Credit ( AMEX:HYG ) Preferreds ( NASDAQ:PFF ) Emerging Market US$ Bonds ( NASDAQ:EMB ) Long Bond ( NASDAQ:TLT ) 5-10yr Treasurys ( NASDAQ:IEF ) 5-10yr TIPS ( AMEX:TIP ) 0-5yr TIPS ( AMEX:STIP ) EM Local Currency Bonds ( AMEX:EMLC ) BDCs ( AMEX:BIZD ) Barclays Agg ( AMEX:AGG ) Investment Grade Credit ( AMEX:LQD ) MBS ( NASDAQ:MBB ) 1-3yr Treasurys ( NASDAQ:SHY ) Bitcoin ( AMEX:BITO ) Industrial Metals ( AMEX:DBB ) Commodities ( AMEX:DBC ) Gold ( AMEX:GLD ) Equity Volatility ( AMEX:VIXM ) Interest Rate Volatility ( AMEX:PFIX ) Energy ( AMEX:USO ) Precious Metals ( AMEX:DBP ) Agriculture ( AMEX:DBA ) US Dollar ( AMEX:UUP ) Inverse US Dollar ( AMEX:UDN ) Functionalities: Fixed Income and Macro Table Shows relative market Asset performance Comes with different Calculation options like RoC, Sharpe ratio, Sortino ratio, Omega ratio and Normalization Allows for advanced market (health) performance Provides the calculated, realized GRID market regimes Informs about "Risk ON" and "Risk OFF" market states Visuals - for your best experience only use one (+ BarColoring) at a time: You can visualize all important metrics: - GRID regimes of the currently chosen calculation type - Risk On/Risk Off with background colouring and additional +1/-1 values - a smoother GRID model - a smoother Risk On/ Risk Off metric - Barcoloring for enabled metric of the above If you have more suggestions, please write me Fixed Income and Macro: The visualisation of the relative performance of the different assets provides valuable information about the current market environment and the actual market performance. It furthermore makes it possible to obtain a deeper understanding of how the interconnected market works and makes it simple to identify the actual market direction, thus also providing all the information to derive overall market health, market strength or weakness. Utility: The Fixed Income and Macro Table is divided in 4 Columns which are the GRID regimes: Economic Growth: Goldilocks Reflation Economic Contraction: Inflation Deflation Top 5 Fixed Income/ Macro Factors: Are the values green for a specific Column? If so then the market reflects the corresponding GRID behavior. Bottom 5 Fixed Income/ Macro Factors: Are the values red for a specific Column? If so then the market reflects the corresponding GRID behavior. So if we have Goldilocks as current regime we would see green values in the Top 5 Goldilocks Cells and red values in the Bottom 5 Goldilocks Cells. You will find that Reflation will look similar, as it is also a sign of Economic Growth. Same is the case for the two Contraction regimes. ****** This Indicator again is based to a majority on 42MACRO's models. I only brought them into TV and added things on top of it. If you have questions or need a more in-depth guide DM me. GM
Pine Script® インジケーター
Celestial-Eyeの投稿
4