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חפש סקריפטים עבור "股价站上60月线"

NG [Simple Harmonic Oscillator]The SHO is a bounded oscillator for the simple harmonic index that calculates the period of the market’s cycle. The oscillator is used for short and intermediate terms and moves within a range of -100 to 100 percent. The SHO has overbought and oversold levels at +40 and -40, respectively. At extreme periods, the oscillator may reach the levels of +60 and -60. The zero level demonstrates an equilibrium between the periods of bulls and bears. The SHO oscillates between +40 and -40. The crossover at those levels creates buy and sell signals. In an uptrend, the SHO fluctuates between 0 and +40 where the bulls are controlling the market. On the contrary, the SHO fluctuates between 0 and -40 during downtrends where the bears controlthe market. Reaching the extreme level -60 in an uptrend is a sign of weakness.
אינדיקטור Pine Script®
מאת ‎NGBaltic‎
2
DEMA Double Exponential Moving Average Strategy@Moneros 2017 Based on The DEMA is a fast-acting moving average that is more responsive to market changes than a traditional moving average en.wikipedia.org !!!! IN ORDER TO AVOID REPAITING ISSUES !!!! !!!! DO NOT VIEW IN LOWER RESOLUTIONS THAN res/2 PARAMETER !!!! for example res = 120 view >= 60m res = 60 view >= 30m the length of the DEMA sampling shouldn't be longer than a candle Best profits tested on BTCUSD res = 105 slowPeriod = 2 fastPeriod = 32 res = 125 slowPeriod = 3 fastPeriod = 21 res = 120 slowPeriod = 2 fastPeriod = 32 res = 130 slowPeriod = 1 fastPeriod = 24 res = 40 slowPeriod = 4 fastPeriod = 93 res = 60 slowPeriod = 1 fastPeriod = 67 BTCUSD
אסטרטגיית Pine Script®
מאת ‎moneros‎
29
Hersheys CoCo VolumeCoCo Volume shows you volume movement of your symbol after subtracting the movement from another symbol, preferrably the sector or market the stock belongs to. My latest update to my CoCoVolume Indicator. It calculates today's volume percent over the 60 period average for both your symbol and index, and displays that difference. If the percent is over the max it highlights the color, showing BIG action for that stock. The last version was calculating the percent volume difference from yesterday to today for the stock and index and displaying the difference. The prior method had large swings on low volume stocks... this one shows the independent volume action much better. The default values will suit most stocks. You can set three variables... - the index symbol, default is SPY - the period for averaging, default is 60 - the max volume percent, default is 500 Good trading! Brian Hershey
אינדיקטור Pine Script®
מאת ‎bnh‎
1
close-hl2 Price actionStill not tested, but looks very good ; it is the difference between EMA median price and EMA close in different time frame, I used 240, 60, and the current Time frame ,plus one more customed period ; can forcast the price movement , but it s not in scale, so it can not show how much higher or lower the price can goes but just the next direction. I think intraday on 5 ,15 ,60 better then high frame.If you need to try on Daily frame have to change the period to higher then Daily
אינדיקטור Pine Script®
מאת ‎MarcoValente‎
3
Everyday 0002 _ MAC 1st Trading Hour WalkoverThis is the second strategy for my Everyday project. Like I wrote the last time - my goal is to create a new strategy everyday for the rest of 2016 and post it here on TradingView. I'm a complete beginner so this is my way of learning about coding strategies. I'll give myself between 15 minutes and 2 hours to complete each creation. This is basically a repetition of the first strategy I wrote - a Moving Average Crossover, but I added a tiny thing. I read that "Statistics have proven that the daily high or low is established within the first hour of trading on more than 70% of the time." (source: ) My first Moving Average Crossover strategy, tested on VOLVB daily, got stoped out by the volatility and because of this missed one nice bull run and a very nice bear run. So I added this single line: if time("60", "1000-1600") regarding when to take exits: if time("60", "1000-1600") strategy.exit("Close Long", "Long", profit=2000, loss=500) strategy.exit("Close Short", "Short", profit=2000, loss=500) Sweden is UTC+2 so I guess UTC 1000 equals 12.00 in Stockholm. Not sure if this is correct, actually. Anyway, I hope this means the strategy will only take exits based on price action which occur in the afternoon, when there is a higher probability of a lower volatility. When I ran the new modified strategy on the same VOLVB daily it didn't get stoped out so easily. On the other hand I'll have to test this on various stocks . Reading and learning about how to properly test strategies is on my todo list - all tips on youtube videos or blogs to read on this topic is very welcome! Like I said the last time, I'm posting these strategies hoping to learn from the community - so any feedback, advice, or corrections is very much welcome and appreciated! /pbergden
אסטרטגיית Pine Script®
מאת ‎pbergden‎
Stochastic Enhanced [DCAUT]█ Stochastic Enhanced 📊 ORIGINALITY & INNOVATION The Stochastic Enhanced indicator builds upon George Lane's classic momentum oscillator (developed in the late 1950s) by providing comprehensive smoothing algorithm flexibility. While traditional implementations limit users to Simple Moving Average (SMA) smoothing, this enhanced version offers 21 advanced smoothing algorithms, allowing traders to optimize the indicator's characteristics for different market conditions and trading styles. Key Improvements: Extended from single SMA smoothing to 21 professional-grade algorithms including adaptive filters (KAMA, FRAMA), zero-lag methods (ZLEMA, T3), and advanced digital filters (Kalman, Laguerre) Maintains backward compatibility with traditional Stochastic calculations through SMA default setting Unified smoothing algorithm applies to both %K and %D lines for consistent signal processing characteristics Enhanced visual feedback with clear color distinction and background fill highlighting for intuitive signal recognition Comprehensive alert system covering crossovers and zone entries for systematic trade management Differentiation from Traditional Stochastic: Traditional Stochastic indicators use fixed SMA smoothing, which introduces consistent lag regardless of market volatility. This enhanced version addresses the limitation by offering adaptive algorithms that adjust to market conditions (KAMA, FRAMA), reduce lag without sacrificing smoothness (ZLEMA, T3, HMA), or provide superior noise filtering (Kalman Filter, Laguerre filters). The flexibility helps traders balance responsiveness and stability according to their specific needs. 📐 MATHEMATICAL FOUNDATION Core Stochastic Calculation: The Stochastic Oscillator measures the position of the current close relative to the high-low range over a specified period: Step 1: Raw %K Calculation %K_raw = 100 × (Close - Lowest Low) / (Highest High - Lowest Low) Where: Close = Current closing price Lowest Low = Lowest low over the %K Length period Highest High = Highest high over the %K Length period Result ranges from 0 (close at period low) to 100 (close at period high) Step 2: Smoothed %K Calculation %K = MA(%K_raw, K Smoothing Period, MA Type) Where: MA = Selected moving average algorithm (SMA, EMA, etc.) K Smoothing = 1 for Fast Stochastic, 3+ for Slow Stochastic Traditional Fast Stochastic uses %K_raw directly without smoothing Step 3: Signal Line %D Calculation %D = MA(%K, D Smoothing Period, MA Type) Where: %D acts as a signal line and moving average of %K D Smoothing typically set to 3 periods in traditional implementations Both %K and %D use the same MA algorithm for consistent behavior Available Smoothing Algorithms (21 Options): Standard Moving Averages: SMA (Simple): Equal-weighted average, traditional default, consistent lag characteristics EMA (Exponential): Recent price emphasis, faster response to changes, exponential decay weighting RMA (Rolling/Wilder's): Smoothed average used in RSI, less reactive than EMA WMA (Weighted): Linear weighting favoring recent data, moderate responsiveness VWMA (Volume-Weighted): Incorporates volume data, reflects market participation intensity Advanced Moving Averages: HMA (Hull): Reduced lag with smoothness, uses weighted moving averages and square root period ALMA (Arnaud Legoux): Gaussian distribution weighting, minimal lag with good noise reduction LSMA (Least Squares): Linear regression based, fits trend line to data points DEMA (Double Exponential): Reduced lag compared to EMA, uses double smoothing technique TEMA (Triple Exponential): Further lag reduction, triple smoothing with lag compensation ZLEMA (Zero-Lag Exponential): Lag elimination attempt using error correction, very responsive TMA (Triangular): Double-smoothed SMA, very smooth but slower response Adaptive & Intelligent Filters: T3 (Tilson T3): Six-pass exponential smoothing with volume factor adjustment, excellent smoothness FRAMA (Fractal Adaptive): Adapts to market fractal dimension, faster in trends, slower in ranges KAMA (Kaufman Adaptive): Efficiency ratio based adaptation, responds to volatility changes McGinley Dynamic: Self-adjusting mechanism following price more accurately, reduced whipsaws Kalman Filter: Optimal estimation algorithm from aerospace engineering, dynamic noise filtering Advanced Digital Filters: Ultimate Smoother: Advanced digital filter design, superior noise rejection with minimal lag Laguerre Filter: Time-domain filter with N-order implementation, adjustable lag characteristics Laguerre Binomial Filter: 6-pole Laguerre filter, extremely smooth output for long-term analysis Super Smoother: Butterworth filter implementation, removes high-frequency noise effectively 📊 COMPREHENSIVE SIGNAL ANALYSIS Absolute Level Interpretation (%K Line): %K Above 80: Overbought condition, price near period high, potential reversal or pullback zone, caution for new long entries %K in 70-80 Range: Strong upward momentum, bullish trend confirmation, uptrend likely continuing %K in 50-70 Range: Moderate bullish momentum, neutral to positive outlook, consolidation or mild uptrend %K in 30-50 Range: Moderate bearish momentum, neutral to negative outlook, consolidation or mild downtrend %K in 20-30 Range: Strong downward momentum, bearish trend confirmation, downtrend likely continuing %K Below 20: Oversold condition, price near period low, potential bounce or reversal zone, caution for new short entries Crossover Signal Analysis: %K Crosses Above %D (Bullish Cross): Momentum shifting bullish, faster line overtakes slower signal, consider long entry especially in oversold zone, strongest when occurring below 20 level %K Crosses Below %D (Bearish Cross): Momentum shifting bearish, faster line falls below slower signal, consider short entry especially in overbought zone, strongest when occurring above 80 level Crossover in Midrange (40-60): Less reliable signals, often in choppy sideways markets, require additional confirmation from trend or volume analysis Multiple Failed Crosses: Indicates ranging market or choppy conditions, reduce position sizes or avoid trading until clear directional move Advanced Divergence Patterns (%K Line vs Price): Bullish Divergence: Price makes lower low while %K makes higher low, indicates weakening bearish momentum, potential trend reversal upward, more reliable when %K in oversold zone Bearish Divergence: Price makes higher high while %K makes lower high, indicates weakening bullish momentum, potential trend reversal downward, more reliable when %K in overbought zone Hidden Bullish Divergence: Price makes higher low while %K makes lower low, indicates trend continuation in uptrend, bullish trend strength confirmation Hidden Bearish Divergence: Price makes lower high while %K makes higher high, indicates trend continuation in downtrend, bearish trend strength confirmation Momentum Strength Analysis (%K Line Slope): Steep %K Slope: Rapid momentum change, strong directional conviction, potential for extended moves but also increased reversal risk Gradual %K Slope: Steady momentum development, sustainable trends more likely, lower probability of sharp reversals Flat or Horizontal %K: Momentum stalling, potential reversal or consolidation ahead, wait for directional break before committing %K Oscillation Within Range: Indicates ranging market, sideways price action, better suited for range-trading strategies than trend following 🎯 STRATEGIC APPLICATIONS Mean Reversion Strategy (Range-Bound Markets): Identify ranging market conditions using price action or Bollinger Bands Wait for Stochastic to reach extreme zones (above 80 for overbought, below 20 for oversold) Enter counter-trend position when %K crosses %D in extreme zone (sell on bearish cross above 80, buy on bullish cross below 20) Set profit targets near opposite extreme or midline (50 level) Use tight stop-loss above recent swing high/low to protect against breakout scenarios Exit when Stochastic reaches opposite extreme or %K crosses %D in opposite direction Trend Following with Momentum Confirmation: Identify primary trend direction using higher timeframe analysis or moving averages Wait for Stochastic pullback to oversold zone (<20) in uptrend or overbought zone (>80) in downtrend Enter in trend direction when %K crosses %D confirming momentum shift (bullish cross in uptrend, bearish cross in downtrend) Use wider stops to accommodate normal trend volatility Add to position on subsequent pullbacks showing similar Stochastic pattern Exit when Stochastic shows opposite extreme with failed cross or bearish/bullish divergence Divergence-Based Reversal Strategy: Scan for divergence between price and Stochastic at swing highs/lows Confirm divergence with at least two price pivots showing divergent Stochastic readings Wait for %K to cross %D in direction of anticipated reversal as entry trigger Enter position in divergence direction with stop beyond recent swing extreme Target profit at key support/resistance levels or Fibonacci retracements Scale out as Stochastic reaches opposite extreme zone Multi-Timeframe Momentum Alignment: Analyze Stochastic on higher timeframe (4H or Daily) for primary trend bias Switch to lower timeframe (1H or 15M) for precise entry timing Only take trades where lower timeframe Stochastic signal aligns with higher timeframe momentum direction Higher timeframe Stochastic in bullish zone (>50) = only take long entries on lower timeframe Higher timeframe Stochastic in bearish zone (<50) = only take short entries on lower timeframe Exit when lower timeframe shows counter-signal or higher timeframe momentum reverses Zone Transition Strategy: Monitor Stochastic for transitions between zones (oversold to neutral, neutral to overbought, etc.) Enter long when Stochastic crosses above 20 (exiting oversold), signaling momentum shift from bearish to neutral/bullish Enter short when Stochastic crosses below 80 (exiting overbought), signaling momentum shift from bullish to neutral/bearish Use zone midpoint (50) as dynamic support/resistance for position management Trail stops as Stochastic advances through favorable zones Exit when Stochastic fails to maintain momentum and reverses back into prior zone 📋 DETAILED PARAMETER CONFIGURATION %K Length (Default: 14): Lower Values (5-9): Highly sensitive to price changes, generates more frequent signals, increased false signals in choppy markets, suitable for very short-term trading and scalping Standard Values (10-14): Balanced sensitivity and reliability, traditional default (14) widely used,适合 swing trading and intraday strategies Higher Values (15-21): Reduced sensitivity, smoother oscillations, fewer but potentially more reliable signals, better for position trading and lower timeframe noise reduction Very High Values (21+): Slow response, long-term momentum measurement, fewer trading signals, suitable for weekly or monthly analysis %K Smoothing (Default: 3): Value 1: Fast Stochastic, uses raw %K calculation without additional smoothing, most responsive to price changes, generates earliest signals with higher noise Value 3: Slow Stochastic (default), traditional smoothing level, reduces false signals while maintaining good responsiveness, widely accepted standard Values 5-7: Very slow response, extremely smooth oscillations, significantly reduced whipsaws but delayed entry/exit timing Recommendation: Default value 3 suits most trading scenarios, active short-term traders may use 1, conservative long-term positions use 5+ %D Smoothing (Default: 3): Lower Values (1-2): Signal line closely follows %K, frequent crossover signals, useful for active trading but requires strict filtering Standard Value (3): Traditional setting providing balanced signal line behavior, optimal for most trading applications Higher Values (4-7): Smoother signal line, fewer crossover signals, reduced whipsaws but slower confirmation, better for trend trading Very High Values (8+): Signal line becomes slow-moving reference, crossovers rare and highly significant, suitable for long-term position changes only Smoothing Type Algorithm Selection: For Trending Markets: ZLEMA, DEMA, TEMA: Reduced lag for faster trend entry, quick response to momentum shifts, suitable for strong directional moves HMA, ALMA: Good balance of smoothness and responsiveness, effective for clean trend following without excessive noise EMA: Classic choice for trending markets, faster than SMA while maintaining reasonable stability For Ranging/Choppy Markets: Kalman Filter, Super Smoother: Superior noise filtering, reduces false signals in sideways action, helps identify genuine reversal points Laguerre Filters: Smooth oscillations with adjustable lag, excellent for mean reversion strategies in ranges T3, TMA: Very smooth output, filters out market noise effectively, clearer extreme zone identification For Adaptive Market Conditions: KAMA: Automatically adjusts to market efficiency, fast in trends and slow in congestion, reduces whipsaws during transitions FRAMA: Adapts to fractal market structure, responsive during directional moves, conservative during uncertainty McGinley Dynamic: Self-adjusting smoothing, follows price naturally, minimizes lag in trending markets while filtering noise in ranges For Conservative Long-Term Analysis: SMA: Traditional choice, predictable behavior, widely understood characteristics RMA (Wilder's): Smooth oscillations, reduced sensitivity to outliers, consistent behavior across market conditions Laguerre Binomial Filter: Extremely smooth output, ideal for weekly/monthly timeframe analysis, eliminates short-term noise completely Source Selection: Close (Default): Standard choice using closing prices, most common and widely tested HLC3 or OHLC4: Incorporates more price information, reduces impact of sudden spikes or gaps, smoother oscillator behavior HL2: Midpoint of high-low range, emphasizes intrabar volatility, useful for markets with wide intraday ranges Custom Source: Can use other indicators as input (e.g., Heikin Ashi close, smoothed price), creates derivative momentum indicators 📈 PERFORMANCE ANALYSIS & COMPETITIVE ADVANTAGES Responsiveness Characteristics: Traditional SMA-Based Stochastic: Fixed lag regardless of market conditions, consistent delay of approximately (K Smoothing + D Smoothing) / 2 periods Equal treatment of trending and ranging markets, no adaptation to volatility changes Predictable behavior but suboptimal in varying market regimes Enhanced Version with Adaptive Algorithms: KAMA and FRAMA reduce lag by up to 40-60% in strong trends compared to SMA while maintaining similar smoothness in ranges ZLEMA and T3 provide near-zero lag characteristics for early entry signals with acceptable noise levels Kalman Filter and Super Smoother offer superior noise rejection, reducing false signals in choppy conditions by estimations of 30-50% compared to SMA Performance improvements vary by algorithm selection and market conditions Signal Quality Improvements: Adaptive algorithms help reduce whipsaw trades in ranging markets by adjusting sensitivity dynamically Advanced filters (Kalman, Laguerre, Super Smoother) provide clearer extreme zone readings for mean reversion strategies Zero-lag methods (ZLEMA, DEMA, TEMA) generate earlier crossover signals in trending markets for improved entry timing Smoother algorithms (T3, Laguerre Binomial) reduce false extreme zone touches for more reliable overbought/oversold signals Comparison with Standard Implementations: Versus Basic Stochastic: Enhanced version offers 21 smoothing options versus single SMA, allowing optimization for specific market characteristics and trading styles Versus RSI: Stochastic provides range-bound measurement (0-100) with clear extreme zones, RSI measures momentum speed, Stochastic offers clearer visual overbought/oversold identification Versus MACD: Stochastic bounded oscillator suitable for mean reversion, MACD unbounded indicator better for trend strength, Stochastic excels in range-bound and oscillating markets Versus CCI: Stochastic has fixed bounds (0-100) for consistent interpretation, CCI unbounded with variable extremes, Stochastic provides more standardized extreme readings across different instruments Flexibility Advantages: Single indicator adaptable to multiple strategies through algorithm selection rather than requiring different indicator variants Ability to optimize smoothing characteristics for specific instruments (e.g., smoother for crypto volatility, faster for forex trends) Multi-timeframe analysis with consistent algorithm across timeframes for coherent momentum picture Backtesting capability with algorithm as optimization parameter for strategy development Limitations and Considerations: Increased complexity from multiple algorithm choices may lead to over-optimization if parameters are curve-fitted to historical data Adaptive algorithms (KAMA, FRAMA) have adjustment periods during market regime changes where signals may be less reliable Zero-lag algorithms sacrifice some smoothness for responsiveness, potentially increasing noise sensitivity in very choppy conditions Performance characteristics vary significantly across algorithms, requiring understanding and testing before live implementation Like all oscillators, Stochastic can remain in extreme zones for extended periods during strong trends, generating premature reversal signals USAGE NOTES This indicator is designed for technical analysis and educational purposes to provide traders with enhanced flexibility in momentum analysis. The Stochastic Oscillator has limitations and should not be used as the sole basis for trading decisions. Important Considerations: Algorithm performance varies with market conditions - no single smoothing method is optimal for all scenarios Extreme zone signals (overbought/oversold) indicate potential reversal areas but not guaranteed turning points, especially in strong trends Crossover signals may generate false entries during sideways choppy markets regardless of smoothing algorithm Divergence patterns require confirmation from price action or additional indicators before trading Past indicator characteristics and backtested results do not guarantee future performance Always combine Stochastic analysis with proper risk management, position sizing, and multi-indicator confirmation Test selected algorithm on historical data of specific instrument and timeframe before live trading Market regime changes may require algorithm adjustment for optimal performance The enhanced smoothing options are intended to provide tools for optimizing the indicator's behavior to match individual trading styles and market characteristics, not to create a perfect predictive tool. Responsible usage includes understanding the mathematical properties of selected algorithms and their appropriate application contexts.
אינדיקטור Pine Script®
מאת ‎DCAUT‎
1m Scalping ATR (with SL & Zones)A universal ATR indicator that anchors volatility to your stop-loss. Read any market (FX, JPY pairs, Gold/Silver, indices, crypto) consistently—regardless of pip/point conventions and timeframe. Why this indicator? Classic ATR is absolute (pips/points) and feels different across markets/TFs. ATR Takeoff normalizes ATR to your stop-loss in pips and highlights clear zones for “quiet / ideal / too volatile,” so you instantly know if a 10-pip SL fits current conditions. Key features Auto pip detection (FX, JPY, XAU/XAG, indices, BTC/ETH). Selectable ATR source: chart timeframe or fixed ATR TF (e.g., “15”, “30”, “60”). Display modes: Percent of SL – ATR relative to SL in %, great for M1 (typical 10–30%). Multiple of SL – ATR as a multiple of SL (e.g., 0.6× / 1.0× / 1.2×). Panel zones: Green = “Ready for takeoff” (≤ Low), Yellow = reference (Mid), Red = too volatile (≥ High). Status badge (top-right): Quiet / ATR ok / Wild, current ATR/SL value, ATR TF used. Direction-agnostic: Works the same for longs and shorts. Inputs (at a glance) Length / Smoothing (RMA/SMA/EMA/WMA): ATR base settings. Your Stop-Loss (Pips): Reference SL (e.g., 10). ATR Timeframe (empty = chart): Use chart TF or a fixed TF. Display Mode: “Percent of SL” or “Multiple of SL.” Low/Mid/High (Percent Mode): Zone thresholds in % of SL. Low/Mid/High (Multiple Mode): Zone thresholds in ×SL. Recommended defaults Length 14, Smoothing RMA, SL 10 pips Display Mode: Percent of SL Low/Mid/High (%): 15 / 20 / 25 ATR Timeframe: empty (= chart) for reactive, or “30” for smoother M30 context with M1 entries. How to use Set SL (pips). 2) Choose display mode. 3) Optionally pick ATR TF. Interpretation: ≤ Low (green): setups allowed. ≈ Mid (yellow): neutral reference. ≥ High (red): too volatile → adjust SL/size or wait. Note: Auto-pip relies on common ticker naming; verify on exotic symbols. Disclaimer: For research/education. Not financial advice.
אינדיקטור Pine Script®
מאת ‎Patrik_Kreuzweger‎
Session-Conditioned Regime ATRWhy this exists Classic ATR is great—until the open. The first few bars often inherit overnight gaps and 24-hour noise that have nothing to do with the intraday regime you actually trade. That inflates early ATR, scrambles thresholds, and invites hyper-recency bias (“today is crazy!”) when it’s just the open being the open. This tool was built to: Separate session reality from 24h noise. Measure volatility only inside your defined session (e.g., NYSE 09:30–16:00 ET). Judge candles against the current regime, not the last 2–3 bars. A rolling statistic from the last N completed sessions defines what “typical” means right now. Label “large” and “small” objectively. Bars are colored only when True Range meaningfully departs from the session regime—no gut feel, no open-bar distortion (gap inclusion optional). Overview Purpose: objectively identify unusually big or small candles within the active trading session, compared to the recent session regime. Use cases: volatility filters, entry/exit confirmation, session bias detection, adaptive sizing. This indicator replaces generic ATR with a session-conditioned, regime-aware measure. It colors candles only when their True Range (TR) is abnormally large/small versus the last N completed sessions of the same session window. How it works Session gating: Only bars inside the selected session are evaluated (presets for NYSE, CME RTH, FX NY; custom supported). Per-bar TR: TR = max(high, prevRef) − min(low, prevRef). prevRef is the prior close for in-session bars. First bar of the session can include the overnight gap (optional; default off). Regime statistic: For any bar in session k, aggregate all in-session TRs from the previous N completed sessions (k−N … k−1), then compute Median (default) or Mean. Today’s anchor: Running statistic from today’s session start → current bar (for context and the on-chart ratio). Color logic: Big if TR ≥ bigMult × RegimeStat Small if TR ≤ smallMult × RegimeStat Colored states: big bull, big bear, small bull, small bear. Non-triggering bars retain the chart’s native colors. Panel (top-right by default) Regime ATR (Nd): session-conditioned statistic over the past N completed sessions. Today ATR (anchored): running statistic for the current session. Ratio (Today/Regime): intraday volatility vs regime. Sample size n: number of bars used in the regime calculation. Inputs Session Preset: NYSE (09:30–16:00 ET), CME RTH (08:30–15:00 CT), FX NY (08:00–17:00 ET), Custom (session + IANA timezone). Regime Window: number of completed sessions (default 5). Statistic: Median (robust) or Mean. Include Open Gap: include overnight gap in the first in-session bar’s TR (default off). Big/Small thresholds: multipliers relative to RegimeStat (defaults: Big=1.5×, Small=0.67×). Colors: four independent colors for big/small × bull/bear. Panel position & text size. Hidden outputs: expose RegimeStat, TodayStat, Ratio, and Z-score to other scripts. Alerts RegimeATR: BIG bar — triggers when a bar meets the “Big” condition. RegimeATR: SMALL bar — triggers when a bar meets the “Small” condition. Hidden outputs (for strategies/screeners) RegimeATR_stat, TodayATR_stat, Today_vs_Regime_Ratio, BarTR_Zscore. Notes & limitations No look-ahead: calculations only use information available up to that bar. Historical colors reflect what would have been known then. Warm-up: colors begin once there are at least N completed sessions; before that, regime is undefined by design. Changing inputs (session window, multipliers, median/mean, gap toggle) recomputes the full series using the same rolling regime logic per bar. Designed for standard candles. Styling respects existing chart colors when no condition triggers. Practical tips For a broader or tighter notion of “unusual,” adjust Big/Small multipliers. Prefer Median in markets prone to outliers; use Mean if you want Z-score alignment with the panel’s regime mean/std. Use the Ratio readout to spot compression/expansion days quickly (e.g., <0.7× = compressed session, >1.3× = expanded). Roadmap More session presets: 24h continuous (crypto, index CFDs). 23h/Globex futures (CME ETH with a 60-minute maintenance break). Regional equities (LSE, Xetra, TSE), Asia/Europe/NY overlaps for FX. Half-day/holiday templates and dynamic calendars. Multi-regime comparison: track multiple overlapping regimes (e.g., RTH vs ETH for futures) and show separate stats/ratios. Robust stats options: trimmed mean, MAD/Huber alternatives; optional percentile thresholds instead of fixed multipliers. Subpanel visuals: rolling TodayATR and Ratio plots; optional Z-score ribbon. Screener/strategy hooks: export boolean series for BIG/SMALL, plus a lightweight strategy template for backtesting entries/exits conditioned on regime volatility. Performance/QOL: per-symbol presets, smarter warm-up, and finer control over sample caps for ultra-low TF charts. Changelog v0.9b (Beta) Session presets (NYSE/CME RTH/FX NY/Custom) with timezone handling. Panel enhancements: ratio + sample size n. Four-state bar coloring (big/small × bull/bear). Alerts for BIG/SMALL bars. Hidden Z-score stream for downstream use. Gap-in-TR toggle for the first in-session bar. Disclaimer For educational purposes only. Not investment advice. Validate thresholds and session settings across symbols/timeframes before live use.
אינדיקטור Pine Script®
מאת ‎scottallen‎
Market Structure ICT Screener [TradingFinder] BoS ChoCh🔵 Introduction Market Structure is the foundation of every Smart Money and ICT based trading model. It describes how price moves through a sequence of highs and lows, forming clear phases of expansion, retracement and reversal. Understanding this structure allows traders to read institutional order flow and align their positions with the true direction of liquidity. Two of the most critical components in Market Structure are the Break of Structure (BOS) and Change of Character (CHOCH). A BOS represents trend continuation, confirming strength within the current direction. In contrast, CHOCH also known as a Market Structure Shift (MSS) signals the first sign of a trend reversal or liquidity shift where order flow begins to change from bullish to bearish or vice versa. Because the market is fractal, structure can exist at multiple levels known as Major (External) and Minor (Internal). Major structure defines the overall trend on higher timeframes while minor or internal structure reveals short term swings and early reversals within that larger move. 🔵 How to Use Understanding Market Structure starts with identifying how price interacts with previous swing highs and swing lows. Every trend in the market, whether bullish or bearish, is built from a sequence of impulsive and corrective moves. Impulsive legs show strong displacement in the direction of liquidity flow, while corrective legs represent temporary pullbacks as the market rebalances before the next expansion. Recognizing these sequences is essential for reading the story of price and anticipating what may happen next. A Break of Structure (BOS) occurs when price decisively moves beyond a previous structural point by breaking above the last high in an uptrend or falling below the last low in a downtrend. This event confirms that the current trend remains intact and that liquidity has been successfully taken from one side of the market. A BOS acts as confirmation of continuation and reflects strength within the existing directional bias. A Change of Character (CHOCH) appears when price violates structure in the opposite direction of the prevailing trend. This is the first signal that market sentiment and order flow may be shifting. For example, during a downtrend if price breaks above a previous high, it indicates that sellers are losing control and a potential bullish reversal may be developing. In an uptrend, when price drops below a recent low, it suggests a possible bearish transition. Because the market is fractal, structure exists across multiple layers. Major structure reflects the dominant movement visible on higher timeframes and defines the broader directional bias. Minor or internal structure represents smaller swings within that move and helps identify early transitions before they appear on the higher timeframe. When internal and external structures align, they offer a high probability signal for trend continuation or reversal. By observing BOS and CHOCH across both internal and external structures, traders can clearly visualize when the market is expanding, contracting or preparing to shift direction. This structured understanding of price movement forms the foundation for precise trend analysis and high quality decision making in any Smart Money or ICT based trading approach. 🔵 Settings 🟣 Display Settings Table on Chart : Allows users to choose the position of the signal dashboard either directly on the chart or below it, depending on their layout preference. Number of Symbols : Enables users to control how many symbols are displayed in the screener table, from 10 to 20, adjustable in increments of 2 symbols for flexible screening depth. Table Mode : This setting offers two layout styles for the signal table : Basic : Mode displays symbols in a single column, using more vertical space. Extended : Mode arranges symbols in pairs side-by-side, optimizing screen space with a more compact view. Table Size : Lets you adjust the table’s visual size with options such as: auto, tiny, small, normal, large, huge. Table Position : Sets the screen location of the table. Choose from 9 possible positions, combining vertical (top, middle, bottom) and horizontal (left, center, right) alignments. 🟣 Symbol Settings Each of the 20 symbol slots comes with a full set of customizable parameters : Symbol : Define or select the asset (e.g., XAUUSD, BTCUSD, EURUSD, etc.). Timeframe : Set your desired timeframe for each symbol (e.g., 15, 60, 240, 1D). Pivot Period : Set the length used to detect swing highs and lows. Shorter values increase sensitivity, longer ones focus on major structures. 🔵 Conclusion Mastering Market Structure and understanding the relationship between BOS and CHOCH allows traders to see the market with greater clarity and confidence. These two elements reveal how liquidity moves through different phases of expansion and retracement and how institutional order flow shifts between accumulation and distribution. By analyzing both internal and external structures, traders can align short term and long term perspectives and anticipate where price is most likely to react. The ability to read these structural shifts helps identify continuation points, reversals and areas where liquidity is engineered or collected. Incorporating Market Structure into a consistent trading process transforms the way a trader views the chart. Instead of reacting to random movements, each swing, break and shift becomes part of a logical framework that reflects the true behavior of the market. Understanding BOS and CHOCH is not just a concept but a complete language of price that guides every professional decision in Smart Money and ICT based trading.
אינדיקטור Pine Script®
מאת ‎TFlab‎
2
TAKA Auto Retrace + SL v4.2Automatically detects market trend and displays dynamic retracement zones for buy-the-dip and sell-the-rally setups, with an adaptive Stop-Loss line. ⸻ ⚙️ Logic Overview • Trend Detection: Based on the relationship between SMA 20 and SMA 60 • Uptrend → Blue zone (Buy the Dip) • Downtrend → Red zone (Sell the Rally) • Retracement Levels: Auto-draws Fibonacci 0.382 – 0.618 range • Stop-Loss Mode: Select from • Fib 0.786 (default) • Structure (last swing high/low) • ATR-based (volatility adaptive) ⸻ 🎯 How to Use 1️⃣ Add the indicator to your chart 2️⃣ Adjust len to fit the latest swing move 3️⃣ When price enters the zone, wait for a confirmation signal (arrow, BOS, MACD cross) 4️⃣ Enter after the 0.5 breakout 5️⃣ SL = auto-generated line  TP = 0.382 → 0.236 → 1.0 partial targets ⸻ 🧩 Recommended Combo N-Wave or Dow Theory × MACD × TAKA Retrace = “Wait on the zone, strike on the signal.” ⸻ Short version (for compact description): Auto trend detection via SMA 20/60. Draws Fibonacci 0.382–0.618 zones with adaptive Stop-Loss (Fib / Structure / ATR). Uptrend = Buy zone | Downtrend = Sell zone. ⸻ That fits TradingView’s description box and looks clean when published 市場トレンドを自動で判定し 「押し目買い」「戻り売り」ゾーンを自動表示 さらにボラティリティに対応した損切りラインも描画します ⸻ ロジック概要 • トレンド判定：SMA20とSMA60の関係で方向を判断 • 上昇トレンド → 青帯（押し目買い） • 下落トレンド → 赤帯（戻り売り） • リトレース描画：フィボナッチ0.382〜0.618を自動描画 • 損切り方式（選択可） • Fib 0.786（基本形） • Structure（直近高安） • ATR（ボラティリティ対応） ⸻ 使い方 1️⃣ チャートに追加 2️⃣ lenを調整し、直近のスイングに合わせる 3️⃣ 価格が帯に入ったらサイン（矢印・BOS・MACDクロス）を待つ 4️⃣ 0.5ライン突破でエントリー 5️⃣ SL＝自動ライン / TP＝0.382→0.236→1.0で分割利確 ⸻ 推奨組み合わせ N波動 or ダウ理論 × MACD × TAKA Retrace ＝「ゾーンで待ち、サインで撃つ」戦略
אינדיקטור Pine Script®
מאת ‎UMIBOUZU_TAKA‎
Trader Assistant 2Title Trader Assistant 2 — Multi‑Timeframe ATR Volatility and Intrabar Range Monitor Summary Trader Assistant 2 is a compact, multi‑timeframe dashboard that helps you instantly gauge market conditions across 1m, 5m, 15m, 30m, 1h, and 4h. It blends two ATR‑based views: - Volatility regime: current ATR vs its baseline (ATR moving average). - Intrabar range usage: how much of ATR the current bar has already traveled from its open. Each timeframe is color‑coded by the worst of the two signals, so you see risk and heat at a glance. An optional lead cell summarizes active alerts and lists the timeframes that triggered them. What you see on the chart - Single‑row table positioned at the bottom‑right of the chart. - One cell per enabled timeframe: - Green (soft): normal conditions - Orange: elevated risk/volatility - Red: high/critical risk/volatility - Text turns white when a warning/critical condition is present - Optional “alert” cell on the left: - Yellow when any warning is present - Red when any critical condition is present - Message indicates which timeframes fired due to Volatility and/or ATR usage (e.g., “Volatility (5m, 15m) | ATR (1m)”) How it works (high level) - Volatility regime: compares current ATR to a smoothed ATR baseline. If the ratio exceeds your Elevated or High thresholds, the timeframe escalates to orange or red. - Intrabar ATR usage: measures absolute distance from the bar’s open. If the move exceeds your Yellow or Red percentage of ATR, the timeframe escalates accordingly. - Combined color: the cell shows the highest severity between the two checks. Mermaid (logic overview) flowchart LR A --> B B --> C C --> D{Vol Severity(Normal/Elevated/High)} E --> F F --> G{ATR Usage Severity(Normal/Yellow/Red)} D --> H G --> H H --> I H --> J Inputs and defaults - Timeframe toggles: 1m, 5m, 15m, 30m, 1h, 4h (enable/disable any mix) - ATR periods per timeframe (defaults): - 1m: 60 - 5m: 24 - 15m: 16 - 30m: 14 - 1h: 12 - 4h: 12 - ATR baseline smoothing: - Moving average period: 20 (used to compare current ATR vs average) - Volatility thresholds (percent of baseline): - Elevated: 80% - High: 120% - Intrabar ATR usage thresholds: - Yellow: 50% of ATR - Red: 75% of ATR Typical use cases - Session open scan: Quickly see where heat is building and which timeframes require caution. - News and high‑impact events: Identify heightened conditions before entering or managing positions. - Trade filtering: Avoid entries during red conditions or tighten risk; favor normal/green regimes for cleaner structure. - Risk sizing: Reduce size or switch to passive management when multiple timeframes show elevated/high conditions. Tips and best practices - Threshold tuning: Different markets/venues need different percentages. Start with defaults, then adjust to your symbol’s volatility. - Baseline smoothing: Increase the MA period to reduce noise in the volatility regime. - Multi‑TF alignment: When higher timeframes turn orange/red, treat lower‑TF signals with extra caution. - Combine with structure and volume tools for a complete decision framework. Notes and limitations - Visual monitor: This is an on‑chart dashboard/visual alert. It does not emit TradingView alert() notifications. - Multi‑timeframe behavior: Values update according to each source timeframe’s bar closes. - Strategy‑agnostic: This does not generate buy/sell signals. Use it for context, regime awareness, and risk control. - Educational only: Not financial advice. Always backtest and validate on your own instruments. Color legend - Green: Normal conditions - Orange: Elevated volatility and/or significant intrabar range usage - Red: High/critical conditions (exercise caution) - Yellow alert cell: Warning present in at least one timeframe - Red alert cell: Critical condition present in at least one timeframe Quick start 1) Add the indicator to your chart. 2) Enable the timeframes relevant to your trading horizon. 3) Keep defaults or tune ATR periods and thresholds to your symbol. 4) Read the row from left to right: alert cell (if present), then timeframes. Prioritize management when you see orange/red, and be selective with entries during heat.
אינדיקטור Pine Script®
מאת ‎gurmanalexander‎
LA - EMA Bands with MTF DashboardDetailed Explanation of the LA - EMA Bands with MTF Dashboard Indicator This custom Pine Script v6 indicator, designed for Trading View, overlays EMA-based price channels on the chart while incorporating a multi-timeframe (MTF) dashboard for broader market context. It focuses on visualizing trend direction and momentum through three sets of EMA bands, each representing different time horizons, and extends this with a tabular dashboard that summarizes signals across user-selected timeframes. The bands help identify support, resistance, and trend shifts, while the dashboard provides at-a-glance alignment across multiple periods, aiding in confirming trades or spotting divergences. Unlike volatility-based channels (e.g., Bollinger or Keltner), it relies solely on EMAs for simplicity and lag-reduced responsiveness. Inputs Section The script begins with user-configurable options grouped for ease. A timeframe input allows specifying a resolution for the EMA bands' data fetching, defaulting to the chart's timeframe if left empty—this enables higher-timeframe overlays on lower charts for context. Next, a shared source input defines the price data for all midlines, defaulting to the midpoint of high and low (hl2) but customizable to close, open, or others. The EMA bands have dedicated toggles and length inputs for each of the three sets: the first (long-term) defaults to 144 periods, the second (medium-term) to 72, and the third (short-term) to 12. These are inlined for compact settings panels, with minimum lengths of 1 to prevent errors. A boolean toggle controls the visibility of the MTF dashboard. Following this are nine pairs of inputs for dashboard timeframes: each pair includes a show/hide toggle and an editable timeframe string (e.g., '1' for 1-minute, 'D' for daily). Defaults progress from short (1, 3, 5 minutes) to longer (15, 30, 60 minutes, daily, weekly, monthly), grouped in inlines for organization. Only enabled and non-empty timeframes appear in the dashboard. Helpers Section Two utility functions are defined here. The first computes an EMA on any source series over a specified length using Trading View's built-in function, reused throughout for midlines and bands. The second function generates a signal string ("B" for buy/bullish, "S" for sell/bearish, or "-" for neutral) based on the direction of an EMA applied to high prices. It compares the current EMA value to the previous one, mirroring the band fill logic for consistency in the dashboard. Core Components per Band Set: Midline: An EMA calculated on a user-selectable source price (default: hl2, which is the midpoint between high and low prices). This acts as the central trend line. Upper Band: An EMA applied directly to the high prices of each bar. Lower Band: An EMA applied to the low prices of each bar. These form a channel that captures the smoothed range of price action, highlighting potential support (lower band), resistance (upper band), and overall trend direction (midline). Multiple Band Sets: The indicator includes three independent EMA band sets, each with its own length parameter for customization: EMA1 (default length: 144) – Focuses on long-term trends. EMA2 (default length: 72) – Targets medium-term trends. EMA3 (default length: 12) – Emphasizes short-term momentum. Each set can be toggled on or off via input checkboxes, allowing users to reduce chart clutter if needed. Visual Elements: Midline Plot: Displayed as a line colored based on its direction compared to the previous bar: green for rising (bullish), red for falling (bearish), and black for neutral (flat). Band Fill: The area between the upper and lower bands is filled with a semi-transparent color indicating the trend of the upper band: light green for rising (suggesting expanding highs/upward momentum) and light pink for falling (contracting highs/downward pressure). The bands themselves are plotted in blue with a thin linewidth. Multi-Timeframe Support: Users can input a custom timeframe (e.g., 'D' for daily), and the indicator fetches data from that resolution. This enables higher-timeframe context on lower-timeframe charts, such as viewing daily EMA bands on a 1-hour chart. Calculation Mechanics: All EMAs are computed using Trading View's built-in ta.ema() function. Data is retrieved in a single request.security() call for efficiency, with lookahead enabled to avoid repainting. No multipliers or volatility adjustments are included, making it a simple EMA-based envelope rather than a true volatility channel. In practice, this indicator helps traders identify trend strength, potential breakouts (price crossing bands), or mean-reversion opportunities (price bouncing within bands). It's particularly useful for swing or position trading where multi-period alignment (e.g., all midlines green) signals conviction. Pros Multi-Period Insight: By combining short (12), medium (72), and long (144) periods, it offers a layered view of trends across time horizons, helping confirm alignments or divergences without needing multiple separate indicators. Visual Clarity: Color-coded trends and fills make it easy to spot bullish/bearish shifts at a glance, reducing analysis time. Flexibility: Custom timeframe input allows for multi-timeframe analysis, while shared source and toggles provide user control. Simplicity and Efficiency: Purely EMA-based, it's computationally light and avoids overcomplication, making it accessible for beginners while still useful for spotting channel-based setups like squeezes or expansions. No Repainting: With lookahead, plots are stable once bars close. Cons Lagging Nature: EMAs inherently lag price action, especially longer ones like 144-period, which may cause delayed signals in fast-moving or ranging markets. Lack of Volatility Adjustment: Unlike Keltner Channels or Bollinger Bands, it doesn't incorporate ATR or standard deviation, so bands may not accurately reflect true volatility—potentially leading to false breakouts in high-volatility environments. Chart Clutter: Displaying all three band sets simultaneously can overcrowd the chart, particularly on lower timeframes or volatile assets. Subjective Interpretation: Color changes and band interactions require trader discretion; there's no built-in alerting or quantitative signals, which might lead to inconsistent results. Market Dependency: Defaults may not suit all assets (e.g., stocks vs. crypto); shorter periods like 12 could whipsaw in noisy markets, while 144 might be too slow for intraday trading. Justification for Default Values (12, 72, and 144) The default lengths of 12, 72, and 144 are not arbitrary but draw from established trading principles, particularly W.D. Gann's geometric and numerical theories, as well as Fibonacci sequences, to create a harmonic progression for short-, medium-, and long-term analysis. Here's the rationale: 12 (Short-Term): This is a common period for capturing recent momentum in technical indicators, often seen in setups like the MACD (which uses 12- and 26-day EMAs). It aligns with natural cycles, such as the 12 months in a year, and in Gann theory, 12 serves as a base unit for squaring price and time (e.g., in the "Square of 12" where multiples like 12, 24, etc., measure cycles in days, weeks, or months). At 12 periods, the EMA reacts quickly to price changes without excessive noise, making it ideal for short-term trend detection. 72 (Medium-Term): This acts as an intermediate bridge, derived from Gann's divisions of the 360-degree circle (a key Gann concept representing a full cycle). Specifically, 72 is 360/5 (relating to pentagonal geometry and natural harmonics) and appears in Gann's time cycle measurements (e.g., as a multiple in the Square of 12: 12×6=72). It's roughly half of 144, providing a balanced midpoint for medium-term trends without overlapping too closely with the others. In practice, 72 periods smooth out short-term fluctuations while still responding to developing trends. 144 (Long-Term): This is a powerhouse number in trading lore, being both 12 squared (12×12=144, central to Gann's "Square of 144" for monthly charts and major cycle turns, as there are 12 months in a year) and a Fibonacci sequence value (1, 1, 2, 3, 5, 8, 13, 21, 34, 55, 89, 144...). Fibonacci periods are popular in moving averages for their alignment with natural growth patterns in markets, and 144 is often used for long-term regime definition (e.g., confirming trends over 144 bars). It helps identify major support/resistance in extended cycles. Overall, these values form a geometric/harmonic series (12, 72=12×6, 144=12×12), promoting alignment with market cycles as per Gann and Fibonacci principles, rather than generic lengths like 50 or 200. They can be adjusted based on the asset or timeframe, but the defaults provide a starting point rooted in time-tested trading numerology for balanced multi-period analysis. Please use this along with other indicators (eg. Pivot, MACD, etc) for better results.
אינדיקטור Pine Script®
מאת ‎aravindleo_99‎
Relative Strength index 2xRelative Strength Index 2× The RSI*2 by AZly is an advanced dual-RSI indicator that allows traders to analyze momentum from two distinct perspectives — short-term and medium-term — on a single chart. It combines RSI precision with multi-timeframe flexibility, giving a clear view of both immediate and underlying momentum trends. ⚙️ How It Works This indicator calculates and plots two fully independent RSI lines, each with customizable settings: RSI 1 (Main RSI) : Captures medium-term momentum, ideal for trend and context. RSI 2 (Fast RSI) : Reacts quickly to short-term moves, identifying overbought and oversold conditions. Both RSIs include: Custom timeframe, source, and smoothing method (SMA, EMA, WMA, VWMA, HMA, SMMA). Gradient zones to visualize momentum strength and reversals. Adjustable levels and colors for clear chart presentation. 📘 Andrew Cardwell Zones (RSI 1) RSI 1 uses Andrew Cardwell’s “range rules” to distinguish bullish and bearish momentum phases: Bullish Range: RSI holds between 40–80, finding support around 40–45. Bearish Range: RSI stays between 20–60, with rallies capped near 55–60. A breakout from one range into another often signals a trend phase transition — marking potential trend beginnings or endings. ⚡ Overbought/Oversold Zones (RSI 2) RSI 2 is designed for fast reactions and reversal detection: 95–100: Extreme overbought zone — potential exhaustion and short setup. 5–0: Extreme oversold zone — potential exhaustion and long setup. Crossing these levels highlights short-term momentum exhaustion , often preceding pullbacks or strong price reversals. 💡 Why It’s Better Compared to traditional RSI indicators, this version provides superior control and insight: Dual independent RSIs with separate timeframes and smoothing. Cardwell-style range recognition for better context of trend strength. Extreme bands for fast RSI 2 to time entries with precision. Dynamic gradient zones for intuitive visual interpretation. Multi-timeframe flexibility that adapts to any trading style. 🎯 Trading Concepts Trend Confirmation: RSI 1 above 50 (bullish range) confirms uptrend bias; below 50 (bearish range) confirms downtrend. Reversal Setup: RSI 2 hitting extreme zones (above 95 or below 5) while RSI 1 stays steady often signals exhaustion and reversal setups. Divergence Confirmation: When RSI 2 diverges from price and RSI 1 supports the direction, it strengthens reversal probability. Range Transition: A shift in RSI 1’s range (from bearish to bullish or vice versa) confirms a major change in market structure. 🕒 Trade Timing (Entry Ideas) Timing is one of the indicator’s strongest features. Wait for RSI 2 to reach an extreme zone (above 95 or below 5). Then confirm the direction with RSI 1 — trades are most effective when RSI 1’s range aligns with the anticipated move. Buy Setup: RSI 1 in bullish range + RSI 2 rebounds upward from the 5 zone. Sell Setup: RSI 1 in bearish range + RSI 2 turns down from the 95 zone. Best Timing: Enter when RSI 2 crosses back inside the 10–90 range in the same direction as RSI 1’s trend. This captures momentum just as it resumes — avoiding early or late entries. 🔷 M & W Patterns (RSI 2) RSI 2 also reveals short-term exhaustion structures: “ M ” Formation: Two RSI peaks near 95–100 — bearish reversal setup. “ W ” Formation: Two RSI troughs near 0–5 — bullish reversal setup. These shapes often appear before price reversals, offering early momentum clues. ⚠️ Important Trading Guidance It is strongly recommended not to trade against the prevailing trend or attempt to pick exact tops or bottoms. The indicator works best when used in alignment with trend direction. Counter-trend entries carry higher risk and lower probability. 📊 Recommended Use Ideal for momentum traders, scalpers, and multi-timeframe analysts seeking precise timing and context. Works on all markets — forex, crypto, stocks, indexes, and commodities.
אינדיקטור Pine Script®
מאת ‎YunakAZly‎
Volume Bubbles & Liquidity Heatmap 30% + biasLuxAlgo gave us an open script, I just primmed it up with the use of Chat GPT:There is no single magic number (like “delta must be 800”) that will guarantee directional follow-through in every market. But you can make a mathematically rigorous filter that gives you a high-probability test — by normalizing the delta against that market’s typical behavior and requiring multiple confirmations. Below is a compact, actionable algorithm you can implement immediately (in your platform or spreadsheet) plus concrete thresholds and the math behind them. High-IQ rule set (math + trade logic) Use three independent checks. Only take the trade if ALL three pass. 1) Z-score (statistical significance of the delta) Compute rolling mean 𝜇 μ and std dev 𝜎 σ of delta on the same timeframe (e.g. 5m) over a lookback window 𝑊 W (suggest 𝑊 = 50 W=50–200 bars). 𝑍 = delta bar − 𝜇 𝑊 𝜎 𝑊 Z= σ W ​ delta bar ​ −μ W ​ ​ Threshold: require 𝑍 ≥ 2.5 Z≥2.5 (strong) — accept 2.0 for less strict, 3.0 for very rare signals. Why: a Z>=2.5 means this delta is an outlier (~<1% one-sided), not normal noise. 2) Relative Imbalance (strength vs total volume) Compute imbalance ratio: 𝑅 = ∣ delta bar ∣ volume bar R= volume bar ​ ∣delta bar ​ ∣ ​ Threshold: require 𝑅 ≥ 0.25 R≥0.25 (25% of the bar’s volume is one-sided). For scalping you can tighten to 0.30–0.40. Why: a big delta with tiny volume isn’t meaningful; this normalizes to participation. 3) Net follow-through over a confirmation window Look ahead 𝑁 N bars (or check the next bar if you need intrabar speed). Compute cumulative delta and price move: cum_delta 𝑁 = ∑ 𝑖 = 1 𝑁 delta bar + 𝑖 cum_delta N ​ = i=1 ∑ N ​ delta bar+i ​ price_move = close bar + 𝑁 − close bar price_move=close bar+N ​ −close bar ​ Thresholds: require cum_delta 𝑁 cum_delta N ​ has the same sign as the trigger and ∣ cum_delta 𝑁 ∣ ≥ 0.5 × ∣ delta bar ∣ ∣cum_delta N ​ ∣≥0.5×∣delta bar ​ ∣, and price_move price_move exceeds a minimum meaningful tick amount (instrument dependent). For ES / US30 type futures: price move ≥ 5–10 ticks; for forex pairs maybe 10–20 pips? Use ATR 20 20 ​ ×0.05 as a generic minimum. Why: separates immediate absorption (buy delta then sellers soak it) from genuine continuation. Bonus check — Structural context (must be satisfied) Trigger should not occur against a strong structural barrier (VWAP, daily high/low, previous session POC) unless you’re explicitly trading exhaustion/absorption setups. If signal occurs near resistance and price does not clear that resistance within 𝑁 N bars, treat as probable trap. Putting it together — final trade decision Take the long (example): If 𝑍 ≥ 2.5 Z≥2.5 and 𝑅 ≥ 0.25 R≥0.25 and cum_delta_N confirms and no hard resistance above (or you’re willing to trade absorption), then enter. Place stop: under the low of the last 2–3 bars or X ATR (instrument dependent). Initial target: risk:reward 1:1 minimum, scale out at 1.5–2R after confirming further delta. Concrete numeric illustration using your numbers You saw FOL = 456, then sell reaction with ~350 opposite. How to interpret: Suppose your 5-min rolling mean 𝜇 μ = 100 and 𝜎 σ=120 (example): 𝑍 = ( 456 − 100 ) / 120 ≈ 2.97 ⇒ statistically big Z=(456−100)/120≈2.97⇒statistically big So it passes Z. If volume on that bar = 2000 contracts: 𝑅 = 456 / 2000 = 0.228 ⇒ just below 0.25 threshold R=456/2000=0.228⇒just below 0.25 threshold So it fails R (weak participation proportionally), explaining why 456 alone didn’t move price. Seller came back with 350 opposite soon after — check cum_delta_N: cum_delta 𝑛 𝑒 𝑥 𝑡 3 ≈ 456 − 350 = 106  net cum_delta next3 ​ ≈456−350=106 net Net is small relative to the initial spike — not convincing follow-through. Conclusion: despite a big absolute number (456), relative measures and lack of follow-through meant the move failed. That’s exactly why raw numbers alone are unreliable. Advanced refinement (for elite performance) Use rolling median + MAD instead of mean/std if delta distribution is skewed. Scale Z by volume volatility: divide Z by volume bar / volume ‾ volume bar ​ / volume ​ to penalize low-volume bars. Use a signed cumulative delta over micro-windows: compute windowed cumulative delta standardized: 𝑍 cum = ∑ 𝑖 = 0 𝑀 − 1 delta 𝑡 − 𝑖 − 𝑀 𝜇 𝑀 𝜎 Z cum ​ = M ​ σ ∑ i=0 M−1 ​ delta t−i ​ −Mμ ​ and require 𝑍 cum ≥ 3 Z cum ​ ≥3 for very high confidence. Add market-depth / DOM confirmation (if available): require that resting ask size above is less than resting bid size below by a factor (i.e. visible liquidity supports the move). Practical thresholds to start with (tune per instrument) Lookback 𝑊 W: 100 bars (5m → about a trading day) Z threshold: 2.5 Imbalance ratio 𝑅 R: ≥ 0.25 (tighten to 0.30 for scalping) Confirmation window 𝑁 N: next 1–3 bars for intraday scalps; 3–6 bars for short swings Cum delta confirmation: ≥ 0.5 × initial delta and same sign Price move confirmation: ≥ 0.03 × ATR20 (or set absolute ticks per instrument) TL;DR — the single best rule Don’t chase absolute numbers. Use Z-score of delta + delta/volume ratio + real follow-through. If all three align, odds are heavily in your favor. If you want, I can: give you a tiny script (pseudocode or Pine / Python) that computes Z, R, cum_delta_N and flags qualifying bars, or run the calculation on a sample of your recent bars if you paste a small CSV of time, delta, volume, close. Which do you want? (I’ll give code right away.) You said: give me a percentage of difference where we have a high probability ChatGPT said: Thought for 7s Nice — straight to the point. Here’s a concise, practical set of percentage thresholds (and associated confidence estimates) you can use right now to flag a “high probability” delta signal. I’ll give you three tiers (good / strong / elite), explain what each means, show how to compute it, and give a short example using your 456/2000 bar. One-line rule Compute delta percent 𝑃 = ∣ delta ∣ volume × 100 % P= volume ∣delta∣ ​ ×100%. Then require Z-score of delta ≥ 2.5 and P to be at or above the threshold below for the desired confidence tier. Threshold tiers (percent of bar volume) Good (high-probability trade candidate) P ≥ 20–25% Typical success probability (when combined with Z≥2.5 and no hard structural resistance): ~60–70%. Use when you want a steady flow of signals with decent edge. Strong (high confidence) P ≥ 30–35% Typical success probability: ~70–80% (with Z≥2.5 + structural alignment). Fewer signals, higher win-rate. Good default for intraday. Elite (very high probability / low false positives) P ≥ 40–50% Typical success probability: ~80–90% (with Z≥3 and confirmation). Rare signals. Use for meaningful size or when you need maximum certainty. Why percentage matters (short) Absolute delta (456) is meaningless without volume context. A 456 delta on 2,000 volume → P = 456/2000 = 22.8% → sits just below the Good threshold, which matches why it failed: decent but not dominant participation. Additional required checks (don’t skip these) To turn P into a reliable filter, always require: Z-score of the delta ≥ 2.5 (or ≥3 for Elite signals). No immediate structural barrier (VWAP, strong resistance) that would plausibly absorb the order. Follow-through: within next N bars (N = 1–3 for scalps) price moves in the same direction by ≥ 0.03×ATR20 (or instrument-specific tick threshold). If this fails, cut fast. Combine all three and your realized win-rate will approach the probabilities above. Practical quick checklist (to apply each signal) Compute P = |delta|/volume. Is P ≥ 30%? (or your chosen tier) Compute Z = (delta − mean)/std over last 100 bars. Is Z ≥ 2.5? Is price not pinned under a heavy resistance? Enter on next bar close (or intrabar on continuation), stop under last 2-bar low (for longs). If price fails to move ≥ 0.03×ATR20 within 3 bars, exit. Example (your bar) delta = 456, volume = 2000 → P = 22.8% → below Good threshold (25%). Even if Z was high, P failed — explains the failure. You need P ≥ ~30% plus Z≥2.5 to call it a Strong signal. Final notes (instrument & timeframe) These percentages were calibrated for futures/US indices and short intraday bars (1–5m). For FX or low-tick instruments, use absolute ticks + a smaller P threshold (start at 15–20%). Always backtest on the specific instrument/timeframe and tune thresholds. If you want, I’ll generate a tiny script (Python or Pine) that calculates P and Z and flags Good/Strong/Elite signals for your chart history so you can see exact historical hit rates. Which language (Python or Pine)? You said: so if we have 456 g vs 350 r what pct is that in favour of green? ChatGPT said: Perfect — let’s calculate it carefully, digit by digit so we don’t make a slip. We have: Green (buy) volume = 456 Red (sell) volume = 350 We want to know what percentage is in favor of green, relative to the total volume. Step 1. Compute total volume Total = 456 + 350 = 806 Total=456+350=806 Step 2. Compute green’s share \text{Green %} = \frac{456}{806} \times 100 Now do it precisely: 456 ÷ 806 = 0.565506 456÷806=0.565506 (rounded) So: 0.565506 × 100 = 56.55 % 0.565506×100=56.55% Step 3. Compute red’s share (for context) 350 806 = 0.434494 → 43.45 % 806 350 ​ =0.434494→43.45% Step 4. Compute difference (bias toward green) 56.55 % − 43.45 % = 13.10 % 56.55%−43.45%=13.10% ✅ Final answer: Green = 56.6% of total Red = 43.4% of total Bias = +13.1 percentage points in favor of green So that’s only a 13% advantage to buyers — modest pressure, not a dominant imbalance. For a high-probability signal (as we discussed earlier), you generally want ≥30% imbalance (e.g. ~65/35 split or stronger). Original: ''The Volume Bubbles & Liquidity Heatmap indicator is a powerful trading tool designed to give traders a clearer picture of volume dynamics and liquidity distribution across multiple timeframes. By combining dynamic volume bubbles with a liquidity heatmap, this indicator makes it easy to identify areas of price interest, spot market imbalances, and improve decision-making for both scalpers and swing traders. This trading indicator is ideal for volume traders, price action traders, and liquidity-focused traders who need a clean, multi-dimensional view of buyer/seller activity and the zones where market participants are most active. With full customization over bubble display, timeframes, and visual settings, traders can tailor the tool to fit virtually any trading strategy or market.''
אינדיקטור Pine Script®
מאת ‎TRADE_the_ORB‎
Multi-Confluence MTF S/R Signal5 Confluences: RSI - Detects oversold/overbought conditions with momentum MACD - Confirms trend direction and momentum shifts Moving Average Trend - Validates price position relative to 50 SMA and 20 EMA Volume - Ensures strong participation (1.5x average volume) Price Action - Confirms breakout (higher high for buys, lower low for sells) Features: Green triangles below bars = BUY signal (all 5 confluences bullish) Red triangles above bars = SELL signal (all 5 confluences bearish) Background coloring when signals occur Real-time dashboard showing each confluence status Built-in alerts you can enable Customizable parameters for all indicators Multi-Timeframe Features: Higher Timeframe Analysis (Default: 60 min) HTF Trend - Checks if price is above/below moving averages on higher timeframe HTF MACD - Confirms momentum direction HTF RSI - Validates not overbought/oversold Signal Types: Strong Signals (Full triangles with text) ✅ All 5 current timeframe confluences aligned ✅ Higher timeframe confirmation (2 of 3 HTF conditions) GREEN "BUY" or RED "SELL" labels Weak Signals (Small transparent triangles with "?") ✅ All 5 current timeframe confluences aligned ❌ NO higher timeframe confirmation Use with caution - may signal counter-trend trades Dashboard Updates: Shows Current Timeframe section (all 5 confluences) Shows HTF status (your chosen higher timeframe) Displays final signal strength Customizable Settings: Enable/Disable MTF - Toggle multi-timeframe confirmation Higher Timeframe - Choose any timeframe (15m, 60m, 4H, D, etc.) Require HTF - Force HTF confirmation or allow weak signals Alerts: Strong Buy/Sell - Full confirmation Weak Buy/Sell - No HTF confirmation
אינדיקטור Pine Script®
מאת ‎traekiw‎
VWAP / ORB / VP & POCThis is an all-in-one technical analysis tool designed to give you a comprehensive view of the market on a single chart. It combines three powerful indicators—VWAP, Opening Range, and Volume Profile—to help you identify key price levels, understand intraday trends, and spot areas of high liquidity. What It Does The indicator plots three distinct components on your chart: Volume-Weighted Average Price (VWAP): A benchmark that shows the average price a security has traded at throughout the day, based on both price and volume. It's often used by institutional traders to gauge whether they are getting a good price. The script also plots standard deviation or percentage-based bands around the VWAP line, which can act as dynamic support and resistance. Opening Range Breakout (ORB): A tool that highlights the high and low of the initial trading period of a session (e.g., the first 15 minutes). The script draws lines for the opening price, range high, and range low for the rest of the session. It also colors the chart with zones to visually separate price action above, below, and within this critical opening range. Volume Profile (VP): A powerful study that shows trading activity over a set number of bars at specific price levels. Unlike traditional volume that is plotted over time, this is plotted on the price axis. It helps you instantly see where the most and least trading has occurred, identifying significant levels like the Point of Control (POC)—the single price with the most volume—and the Value Area (VA), where the majority of trading took place. How to Use It for Trading The real strength of this indicator comes from finding confluence, where two or more of its components signal the same key level. Identifying Support & Resistance: The POC, VWAP bands, Opening Range high/low, and session open price are all powerful levels to watch. When price approaches one of these levels, you can anticipate a potential reaction (a bounce or a breakout). Gauging Intraday Trend: A simple rule of thumb is to consider the intraday trend bullish when the price is trading above the VWAP and bearish when it is trading below the VWAP. Finding High-Value Zones: The Volume Profile’s Value Area (VA) shows you where the market has accepted a price. Trading within the VA is considered "fair value," while prices outside of it are "unfair." Reversals often happen when the price tries to re-enter the Value Area from the outside. Settings: Here’s a breakdown of all the settings you can change to customize the indicator to your liking. Volume Profile Settings: Number of Bars: How many of the most recent bars to use for the calculation. A higher number gives a broader profile. Row Size: The number of price levels (rows) in the profile. Higher numbers give a more detailed, granular view. Value Area Volume %: The percentage of total volume to include in the Value Area (standard is 70%). Horizontal Offset: Moves the Volume Profile further to the right to avoid overlapping with recent price action. Colors & Styles: Customize the colors for the POC line, Value Area, and the up/down volume bars. VWAP Settings: Anchor Period: Resets the VWAP calculation at the start of a new Session, Week, Month, Year, etc. You can even anchor it to corporate events like Earnings or Splits. Source: The price source used in the calculation (default is hlc3, the average of the high, low, and close). Bands Calculation Mode: Standard Deviation: The bands are based on statistical volatility. Percentage: The bands are a fixed percentage away from the VWAP line. Bands Multiplier: Sets the distance of the bands from the VWAP. You can enable and configure up to three sets of bands. ORB Settings (Opening Range) Opening Range Timeframe: The duration of the opening range (e.g., 15 for 15 minutes, 60 for the first hour). Market Session & Time Zone: Crucial for ensuring the range is calculated at the correct time for the asset you're trading. Line & Zone Styles: Full customization for the colors, thickness, and style (Solid, Dashed, Dotted) of the High, Low, and Opening Price lines, as well as the background colors for the zones above, below, and within the range.
אינדיקטור Pine Script®
מאת ‎Mereep01‎
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