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Bitcoin Block Height (Total Blocks)Bitcoin Block Height by RagingRocketBull 2020 Version 1.0 Differences between versions are listed below: ver 1.0: compare QUANDL Difficulty vs Blockchain Difficulty sources, get total error estimate ver 2.0: compare QUANDL Hash Rate vs Blockchain Hash Rate sources, get total error estimate ver 3.0: Total Blocks estimate using different methods -------------------------------- This indicator estimates Bitcoin Block Height (Total Blocks) using Difficulty and Hash Rate in the most accurate way possible, since QUANDL doesn't provide a direct source for Bitcoin Block Height (neither QUANDL:BCHAIN, nor QUANDL:BITCOINWATCH/MINING). Bitcoin Block Height can be used in other calculations, for instance, to estimate the next date of Bitcoin Halving. Using this indicator I demonstrate: - that QUANDL data is not accurate and differ from Blockchain source data (industry standard), but still can be used in calculations - how to plot a series of data points from an external csv source and compare it with another source - how to accurately estimate Bitcoin Block Height Features: - compare QUANDL Difficulty source (EOD, D1) with external Blockchain Difficulty csv source (EOD, D1, embedded) - show/hide Quandl/Blockchain Difficulty curves - show/hide Blockchain Difficulty candles - show/hide differences (aqua vertical lines) - show/hide time gaps (green vertical lines) - count source differences within data range only or for the whole history - multiply both sources by alpha to match before comparing - floor/round both matched sources when comparing - Blockchain Difficulty offset to align sequences, bars > 0 - count time gaps and missing bars (as result of time gaps) WARNING: - This indicator hits the max 1000 vars limit, adding more plots/vars/data points is not possible - Both QUANDL/Blockchain provide daily EOD data and must be plotted on a daily D1 chart otherwise results will be incorrect - current chart must not have any time gaps inside the range (time gaps outside the range don't affect the calculation). Time gaps check is provided. Otherwise hardcoded Blockchain series will be shifted forward on gaps and the whole sequence become truncated at the end => data comparison/total blocks estimate will be incorrect Examples of valid charts that can run this indicator: COINBASE:BTCUSD,D1 (has 8 time gaps, 34 missing bars outside the range), QUANDL:BCHAIN/DIFF,D1 (has no gaps) Usage: - Description of output plot values from left to right: - c_shifted - 4x blockchain plotcandles ohlc, green/black (default na) - diff - QUANDL Difficulty - c_shifted - Blockchain Difficulty with offset - QUANDL Difficulty multiplied by alpha and rounded - Blockchain Difficulty multiplied by alpha and rounded - is_different, bool - cur bar's source values are different (1) or not (0) - count, number of differences - bars, total number of bars/data points in the range - QUANDL daily blocks - Blockchain daily blocks - QUANDL total blocks - Blockchain total blocks - total_error - difference between total_blocks estimated using both sources as of cur bar, blocks - number_of_gaps - number of time gaps on a chart - missing_bars - number of missing bars as result of time gaps on a chart - Color coding: - Blue - QUANDL data - Red - Blockchain data - Black - Is Different - Aqua - number of differences - Green - number of time gaps - by default the indicator will show lots of vertical aqua lines, 138 differences, 928 bars, total error -370 blocks - to compare the best match of the 2 sources shift Blockchain source 1 bar into the future by setting Blockchain Difficulty offset = 1, leave alpha = 0.01 => this results in no vertical aqua lines, 0 differences, total_error = 0 blocks if you move the mouse inside the range some bars will show total_error = 1 blocks => total_error <= 1 blocks - now uncheck Round Difficulty Values flag => some filled aqua areas, 218 differences. - now set alpha = 1 (use raw source values) instead of 0.01 => lots of filled aqua areas, 871 differences. although there are many differences this still doesn't affect the total_blocks estimate provided Difficulty offset = 1 Methodology: To estimate Bitcoin Block Height we need 3 steps, each step has its own version: - Step 1: Compare QUANDL Difficulty vs Blockchain Difficulty sources and estimate error based on differences - Step 2: Compare QUANDL Hash Rate vs Blockchain Hash Rate sources and estimate error based on differences - Step 3: Estimate Bitcoin Block Height (Total Blocks) using different methods in the most accurate way possible QUANDL doesn't provide block time data, but we can calculate it using the Hash Rate approximation formula: estimated Hash rate/sec H = 2^32 * D / T, where D - Difficulty, T - block time, sec 1. block time (T) can be derived from the formula, since we already know Difficulty (D) and Hash Rate (H) from QUANDL 2. using block time (T) we can estimate daily blocks as daily time / block time 3. block height (total blocks) = cumulative sum of daily blocks of all bars on the chart (that's why having no gaps is important) Notes: - This code uses Pinescript v3 compatibility framework - hash rate is in THash/s, although QUANDL falsely states in description GHash/s! THash = 1000 GHash - you can't read files, can only embed/hardcode raw data in script - both QUANDL and Blockchain sources have no gaps - QUANDL and Blockchain series are different in the following ways: - all QUANDL data is already shifted 1 bar into the future, i.e. prev day's value is shown as cur day's value => Blockchain data must be shifted 1 bar forward to match - all QUANDL diff data > 1 bn (10^12) are truncated and have last 1-2 digits as zeros, unlike Blockchain data => must multiply both values by 0.01 and floor/round the results - QUANDL sometimes rounds, other times truncates those 1-2 last zero digits to get the 3rd last digit => must use both floor/round - you can only shift sequences forward into the future (right), not back into the past (left) using positive offset => only Blockchain source can be shifted - since total_blocks is already a cumulative sum of all prev values on each bar, total_error must be simple delta, can't be also int(cum()) or incremental - all Blockchain values and total_error are na outside the range - move you mouse cursor on the last bar/inside the range to see them TLDR, ver 1.0 Conclusion: QUANDL/Blockchain Difficulty source differences don't affect total blocks estimate, total error <= 1 block with avg 150 blocks/day is negligible Both QUANDL/Blockchain Difficulty sources are equally valid and can be used in calculations. QUANDL is a relatively good stand in for Blockchain industry standard data. Links: QUANDL difficulty source: www.quandl.com QUANDL hash rate source: www.quandl.com Blockchain difficulty source (export data as csv): www.blockchain.com
Pine Script® indicator
by RagingRocketBull
3
Bitcoin Logarithmic Growth Curves for intraday usersI wish to thank @Quantadelic who created this great indicator and leaving it open for others to improve. I have made changes to make it user-friendly for the intraday traders. The changes made have been; 1. Compartmentalized each area of the major Fibonacci level; 2. Added minor Fibonacci levels; 3. Color-coded the support and resistance levels, for better viewing; 4. Zoned each area of the major Fibonacci level; and 5. Created a time-frame display period for quicker loading of the indicator. I have removed a few things to allow the indicator to run quicker; 1. Future projections; and 2. The major higher levels of the Fibonacci, which may be useful when Bitcoin reaches 100k. Enjoy
Pine Script® indicator
by aaahopper
3
Hull SuiteHull is its extremely responsive and smooth moving average created by Alan Hull in 2005. Minimal lag and smooth curves made HMA extremely popular TA tool. alanhull.com Script was made to regroup multiple hull variants in one indicator,maintaining flexible customization and intuitive visualization Option to chose between 3 Hull variations Option to chose between 2 visualization modes ( Bands or single line) Option to Paint hull and/or candlesticks according to hulls trend Shortcut for personalizing Line/band thickness,instead of changing every object manually ,there is global option in inputs HMA THMA ( 3HMA) EHMA HMA: Alan Hull EHMA: Slower than hull by default. Raudys, Aistis & Lenčiauskas, Vaidotas & Malčius, Edmundas. (2013). Moving Averages for Financial Data Smoothing ( 403. 34-45. 10.1007/978-3-642-41947-8_4.) Vilnius University, Faculty of Mathematics and Informatics 3HMA (THMA) : Documentation on link below alexgrover
Pine Script® indicator
by InSilico
144
Gann High LowGann High Low is a moving average based trend indicator consisting of two different simple moving averages. The Gann High Low Activator Indicator was described by Robert Krausz in a 1998 issue of Stocks & Commodities Magazine. It is a simple moving average SMA of the previous n period's highs or lows. The indicator tracks both curves (of the highs and the lows). The close of the bar defines which of the two gets plotted. This version is showing the channel that needs to be broken if the trend is going to be changed, and it allows you to chose from the 4 basic averages type for calculation (by definition, Gann High Low Activator uses only simple moving average, but some other averages can give you results that are probably more acceptable for trading in some conditions). Increasing HPeriod and decreasing LPeriod better for short trades, vice versa for long positions.
Pine Script® indicator
by KivancOzbilgic
25
Tillson T3 Moving Average MTFMULTIPLE TIME FRAME version of Tillson T3 Moving Average Indicator Developed by Tim Tillson, the T3 Moving Average is considered superior -1.60% to traditional moving averages as it is smoother, more responsive and thus performs better in ranging market conditions as well. However, it bears the disadvantage of overshooting the price as it attempts to realign itself to current market conditions. It incorporates a smoothing technique which allows it to plot curves more gradual than ordinary moving averages and with a smaller lag. Its smoothness is derived from the fact that it is a weighted sum of a single EMA , double EMA , triple EMA and so on. When a trend is formed, the price action will stay above or below the trend during most of its progression and will hardly be touched by any swings. Thus, a confirmed penetration of the T3 MA and the lack of a following reversal often indicates the end of a trend. The T3 Moving Average generally produces entry signals similar to other moving averages and thus is traded largely in the same manner. Here are several assumptions: If the price action is above the T3 Moving Average and the indicator is headed upward, then we have a bullish trend and should only enter long trades (advisable for novice/intermediate traders). If the price is below the T3 Moving Average and it is edging lower, then we have a bearish trend and should limit entries to short. Below you can see it visualized in a trading platform. Although the T3 MA is considered as one of the best swing following indicators that can be used on all time frames and in any market, it is still not advisable for novice/intermediate traders to increase their risk level and enter the market during trading ranges (especially tight ones). Thus, for the purposes of this article we will limit our entry signals only to such in trending conditions. Once the market is displaying trending behavior, we can place with-trend entry orders as soon as the price pulls back to the moving average (undershooting or overshooting it will also work). As we know, moving averages are strong resistance/support levels, thus the price is more likely to rebound from them and resume its with-trend direction instead of penetrating it and reversing the trend. And so, in a bull trend, if the market pulls back to the moving average, we can fairly safely assume that it will bounce off the T3 MA and resume upward momentum, thus we can go long. The same logic is in force during a bearish trend . And last but not least, the T3 Moving Average can be used to generate entry signals upon crossing with another T3 MA with a longer trackback period (just like any other moving average crossover). When the fast T3 crosses the slower one from below and edges higher, this is called a Golden Cross and produces a bullish entry signal. When the faster T3 crosses the slower one from above and declines further, the scenario is called a Death Cross and signifies bearish conditions. I Personally added a second T3 line with a volume factor of 0.618 (Fibonacci Ratio) and length of 3 (fibonacci number) which can be added by selecting the box in the input section. traders can combine the two lines to have Buy/Sell signals from the crosses. Developed by Tim Tillson
Pine Script® indicator
by KivancOzbilgic
3
Tillson T3 Moving Average by KIVANÇ fr3762Developed by Tim Tillson, the T3 Moving Average is considered superior to traditional moving averages as it is smoother, more responsive and thus performs better in ranging market conditions as well. However, it bears the disadvantage of overshooting the price as it attempts to realign itself to current market conditions. It incorporates a smoothing technique which allows it to plot curves more gradual than ordinary moving averages and with a smaller lag. Its smoothness is derived from the fact that it is a weighted sum of a single EMA , double EMA , triple EMA and so on. When a trend is formed, the price action will stay above or below the trend during most of its progression and will hardly be touched by any swings. Thus, a confirmed penetration of the T3 MA and the lack of a following reversal often indicates the end of a trend. The T3 Moving Average generally produces entry signals similar to other moving averages and thus is traded largely in the same manner. Here are several assumptions: If the price action is above the T3 Moving Average and the indicator is headed upward, then we have a bullish trend and should only enter long trades (advisable for novice/intermediate traders). If the price is below the T3 Moving Average and it is edging lower, then we have a bearish trend and should limit entries to short. Below you can see it visualized in a trading platform. Although the T3 MA is considered as one of the best swing following indicators that can be used on all time frames and in any market, it is still not advisable for novice/intermediate traders to increase their risk level and enter the market during trading ranges (especially tight ones). Thus, for the purposes of this article we will limit our entry signals only to such in trending conditions. Once the market is displaying trending behavior, we can place with-trend entry orders as soon as the price pulls back to the moving average (undershooting or overshooting it will also work). As we know, moving averages are strong resistance/support levels, thus the price is more likely to rebound from them and resume its with-trend direction instead of penetrating it and reversing the trend. And so, in a bull trend, if the market pulls back to the moving average, we can fairly safely assume that it will bounce off the T3 MA and resume upward momentum, thus we can go long. The same logic is in force during a bearish trend . And last but not least, the T3 Moving Average can be used to generate entry signals upon crossing with another T3 MA with a longer trackback period (just like any other moving average crossover). When the fast T3 crosses the slower one from below and edges higher, this is called a Golden Cross and produces a bullish entry signal. When the faster T3 crosses the slower one from above and declines further, the scenario is called a Death Cross and signifies bearish conditions. I Personally added a second T3 line with a volume factor of 0.618 (Fibonacci Ratio) and length of 3 (fibonacci number) which can be added by selecting the box in the input section. traders can combine the two lines to have Buy/Sell signals from the crosses. Developed by Tim Tillson
Pine Script® indicator
by KivancOzbilgic
50
Topfinder Bottomfinder pivot matcher Midas- jayyMidas Technical Analysis: A VWAP Approach to Trading and Investing in Today’s Markets by Andrew Coles, David G. Hawkins Copyright © 2011 by Andrew Coles and David G. Hawkins. Appendix C: TradeStation Code for the MIDAS Topfinder/Bottomfinder Curves ported to tradingview This code is used to assist in adjusting D volume to intersect pivot candle at a pivot candle when using this script: Top Bottom Finder Public version- Jayy found here: The "n" number entered into the TB-F script is the topfinder/bottomfinder starting point or anchor Be sure to enter the correct number in the "Topfinder bottomfinder initiation/anchor candle: 1 for CANDLE low - top finder, 2 for CANDLE high - bottom finder, 3 for CANDLE MIDPOINT (hl2) dialogue box The location of the match point of the pivot candle is extremely important in the: "Match to PIVOT CANDLE: use 1 for CANDLE low, 2 for midtail of the candle below the BODY, 3 for candle BODY low, 4 for CANDLE HIGH, 5 for midpoint of candletail above body, 6 for candle BODY high". Do not confuse body high with candle high. The body low will either be the candle open or close. The body high will be either the open or close. If you expect a trend up the pivot candle is likely the low of the pivot candle ie 1 (2 and 3 are alternatives). In a trend down the high of the pivot candle is often selected ie 4 (5 or 6 are alternatives) If the candle body is aqua increase D volume if it is orange reduce D volume. Adjust iteratively until the candle body turns yellow. That will mean that the TB-F line passes through the pivot candle at the selected point. Jayy
Pine Script® indicator
by jayy
2
Vix FIX / StochRSI StrategyThis strategy is based off of Chris Moody's Vix Fix Indicator . I simply used his indicator and added some rules around it, specifically on entry and exits. Rules : Enter upon a filtered or aggressive entry If there are multiple entry signals, allow pyramiding Exit when there is Stochastic RSI crossover above 80 This works great on a number of stocks. I am keeping a list of stocks with decent Profit Factors and clean equity curves here . Possible ways to use this: Modify this script and setup alerts around the various entries Use as is with different stocks or currency pairs Modify entry / exit points to make it more profitable for even more symbols and currencies
Pine Script® strategy
by timj
42
UCS_Squeeze_Timing-V1There is an important information the Squeeze indicator is missing, which is the Pre Squeeze entry. While the Bollinger band begins to curves out of the KC, The breakout usually happens. There are many instances that the Squeeze indicator will fire, after the Major move, I cant blame the indicator, thats the nature (lagging) of all indicators, and we have to live with it. Therefore pre-squeeze-fire Entry can be critical in timing your entry. Timing it too early could result in stoploss if it turns against you, ( or serious burn on options premium), because we never know when the squeeze will fire with the TTM squeeze, But now We know. Its a little timing tool. Managing position is critical when playing options. I will code the timing signal when I get some time. Updated Versions -
Pine Script® indicator
by UDAY_C_Santhakumar
8
Happy Trigger EliteHAPPY TRIGGER ELITE is a high-performance, structural scalping strategy engineered for precision and explosive growth across high-volatility assets. Developed for the QuantCrawler Discord Community, this strategy bridges the gap between sophisticated pivot analysis and aggressive, high-probability execution. ​At its core, the strategy utilizes a modified LuxAlgo Ghost Engine to detect "Missed Reversals"—critical zones where the market fails to confirm a new high or low, signaling an imminent structural shift. ​🛠️ Key Strategic Pillars ​Structural Ghost Detection: Identifies high-probability reversal points by tracking structural failures rather than just price wicks. ​Dynamic Trailing Logic: Employs a precise "Trail Activation" system designed to lock in profits while giving trades the necessary "breathing room" to reach extended targets. ​Momentum Guard (ATR): Uses an ATR-based volatility filter to ensure the strategy only engages when there is sufficient market participation and "gas in the tank". ​RSI Exhaustion Filter: Prevents "chasing" moves by requiring price to be in an overextended state before a reversal entry is considered. ​🛡️ Institutional-Grade Risk Management ​Built with funded account safety in mind, the strategy includes hard-coded protection features to safeguard your equity: ​Daily Circuit Breaker: An automated shutdown occurs if the user-defined Max Daily Loss is reached, preventing significant drawdowns during choppy market conditions. ​Visual Session Tracking: Automatically identifies peak volume windows, providing a clear visual guide for optimal trading environments. ​Account Buffer Logic: Calibrated to maintain a stable equity curve by balancing aggressive targets with tight risk-to-reward parameters. Credit: LuxAlgo Optimized by: MeliMillionaire247
Pine Script® strategy
by MeliMillionaire247
MES 15m High Win Rate Mean ReversionCore Idea It assumes: Most 15-minute moves in normal conditions revert back toward fair value. Fair value = VWAP + 20-period mean It is not a trend strategy. It bets against short-term overextension. Market Environment It Wants This system performs best when: Market is rotational Volatility is moderate No major macro catalyst Institutions are rebalancing inventory It avoids: Strong breakout days Expansion after news Persistent trend sessions Step-By-Step Logic 1️⃣ Volatility Compression Filter It checks: ATR (14) Compared to its 30-bar average If ATR is too high → no trade. This attempts to skip news days and expansion regimes. 2️⃣ Extreme Detection On the 15-minute chart: It calculates: 20-period mean 2 standard deviation Bollinger Bands VWAP A trade triggers only when: For Long: Price touches lower 2σ band Price is below VWAP For Short: Price touches upper 2σ band Price is above VWAP This defines “statistical stretch.” 3️⃣ Position Structure 6 MES contracts 5 point stop (~$150 risk) 6–6.5 point target (~$180–$195 reward) Max 2 trades per day One trade per direction Why It Has Higher Win Rate Because: It trades exhaustion, not continuation. It enters after price is statistically stretched. Target is smaller than stop multiple systems. It avoids high volatility regimes. Mean reversion strategies win often because markets rotate more than they trend. What It Is Not It is not: A breakout system A momentum system A trend following model A high daily payout generator It is a: Low-frequency, moderate-edge, capital-preservation framework. Risk Characteristics From your backtest: Win rate ≈ 60% Profit factor ≈ 1.7 Max drawdown ≈ $435 Low trade count That is healthy. But understand: When trend days hit, it will lose. If volatility regime changes structurally, edge degrades. Strengths Smooth equity curve Compatible with prop trailing drawdown Emotionally manageable Predictable trade frequency Weaknesses Underperforms in trending months Can have clusters of 3–4 losses Needs volatility filter to stay safe Won’t consistently produce $350 every day Psychological Fit This system fits traders who: Prefer frequent small wins Can accept occasional flat weeks Care more about survival than speed Avoid revenge trading
Pine Script® strategy
by spagnolomatteo21
Structural Volatility Expansion StrategyStructural Volatility Expansion Strategy Purpose This strategy studies the relationship between confirmed market structure breaks and volatility regime shifts. Its objective is to participate in directional expansions that occur after structural confirmation, while filtering out low-volatility consolidations and false breakouts. The script is intended for research and systematic evaluation, not predictive claims. Methodology The model combines three interacting components: 1. Confirmed Structural Break Logic Market structure is derived using confirmed pivot highs and pivot lows. A bullish structural break is defined as a close above the most recent confirmed pivot high. A bearish structural break is defined as a close below the most recent confirmed pivot low. Pivots require full bar confirmation, which prevents forward-looking bias and repainting. This approach differs from simple rolling highest/lowest calculations by using structurally validated turning points. 2. Volatility Regime Classification Volatility is measured using ATR relative to its moving average baseline. Two regimes are defined: Compression: ATR below its historical baseline. Expansion: ATR above its historical baseline. Trades are only allowed during expansion phases. This attempts to reduce participation during statistically lower-momentum environments. 3. Liquidity Sweep Filter Breakouts that wick beyond structural levels but fail to close beyond them are treated as liquidity sweeps and are excluded. This reduces exposure to stop-run reversals where structure appears broken intrabar but fails on close. 4. Higher Timeframe Alignment Directional bias is determined using a higher timeframe moving average. Long entries require higher timeframe close above its MA. Short entries require higher timeframe close below its MA. Lookahead is disabled to avoid repainting. This introduces multi-timeframe confirmation without using future data. Risk Management Default strategy properties: Initial capital: 10,000 Position sizing: 2% of equity per trade Commission: 0.04% Slippage: 2 ticks Pyramiding: Disabled Stops are ATR-based and targets use a fixed risk-reward multiple (default 2:1). The position sizing is intentionally conservative and does not exceed commonly accepted sustainable risk thresholds. Backtesting Transparency When evaluating results: Use markets with sufficient liquidity. Ensure a dataset that generates a meaningful number of trades (ideally 100+). Keep default commission and slippage settings unchanged. Avoid optimizing inputs solely to maximize historical performance. Performance results are dependent on instrument, timeframe, and historical period tested. This script does not guarantee profitability and should be forward-tested before any live use. Intended Use This strategy is designed for: Studying structural continuation patterns Researching volatility regime transitions Comparing breakout performance during expansion vs compression Systematic strategy development It is not intended as financial advice. Originality Notes The script: Uses confirmed pivot-based structure rather than raw lookback highs/lows Filters entries by volatility regime classification Excludes wick-only structural violations Applies non-repainting higher timeframe bias Uses realistic transaction cost modeling The logic emphasizes interaction between structure and volatility rather than indicator stacking. Limitations & Responsible Use This strategy has several important limitations: Lag From Pivot Confirmation Structural pivots require confirmation, which introduces delay. Signals may occur after a portion of the move has already developed. ATR Sensitivity Volatility classification depends on ATR relative to its baseline. During regime transitions, expansion signals may appear slightly late or briefly revert to compression. Trend Dependency The strategy performs best during directional market phases. Extended sideways environments may reduce performance even with volatility filtering. Higher Timeframe Influence The higher timeframe moving average is a smoothing mechanism and may not capture sudden macro shifts immediately. Market Specific Behavior Different asset classes (crypto, forex, equities, indices) exhibit different volatility cycles. Parameters may require testing across multiple datasets rather than optimization for a single instrument. Backtest Limitations Historical testing does not account for: Liquidity variations Execution delays Psychological decision-making factors Structural market changes over time Forward testing and risk control are recommended before any real capital deployment. Suggested Evaluation Approach For objective evaluation: Test across multiple years of data. Use instruments with consistent liquidity. Maintain realistic commission and slippage settings. Avoid curve-fitting inputs to a specific historical window. Compare results across trending and ranging environments. Risk Disclaimer This script is provided for research and educational purposes only. It does not constitute investment advice. All trading involves risk, and past performance does not guarantee future results.
Pine Script® strategy
by JaxonJackFX
VWAP and Previous Day Closing VWAP1. Understanding the Two Lines Current VWAP (The Dynamic Curve): This represents the average price paid throughout the current session, weighted by volume. It moves as new trades come in. Previous Day’s Closing VWAP (The Flat Level): This is a fixed horizontal line representing where the institutional "average price" finished yesterday. It serves as a major psychological anchor point for the current day. 2. Common Trading Strategies The Mean Reversion (The "Rubber Band") If the price gaps up or moves significantly away from both the current VWAP and the Previous Day's VWAP early in the morning, traders often look for a "reversion to the mean." The Logic: Large institutions rarely like to buy significantly above the day's average price. The Trade: If the price starts losing momentum far above the VWAP lines, traders may look for a short position back down toward the Current VWAP. The "Value" Retest The Previous Day’s Closing VWAP often acts as a support or resistance zone. Support: If the price opens above yesterday's VWAP, drops down to touch it, and then bounces, it confirms that buyers are defending "yesterday's value." Resistance: If the price opens below it and fails to break above it, the market is signaling bearishness. The Crossover Signal When the Current VWAP crosses over or under the Previous Day’s Closing VWAP, it indicates a shift in trend strength. Bullish: Current VWAP crosses above Previous Day's VWAP. This suggests today's buyers are more aggressive than yesterday's average. Bearish: Current VWAP crosses below Previous Day's VWAP. This suggests today's selling pressure is heavier than yesterday's average. 3. Best Practices & Pro-Tips Timeframes: This indicator is most effective on 1-minute, 5-minute, or 15-minute charts. On a Daily (D) chart, the lines will disappear or look like single dots because VWAP is calculated intraday. Volume is Key: VWAP is only as strong as the volume behind it. If a bounce off the VWAP happens on low volume, it’s less reliable than a bounce on high volume. The "No-Trade Zone": Many professional traders avoid taking long positions when the price is below the current VWAP, as they are essentially "buying at a premium" relative to the day's average sellers.
Pine Script® indicator
by sandip4evr
ADR en Ticks Historique (6E) - SyncThis indicator calculates the Average Daily Range (ADR) in ticks for the Euro FX Futures contract (6E) with consistent historical display across all timeframes. Key Features: Precise tick calculation: uses the 0.00005 tick size specific to the 6E contract (Euro FX standard 125,000 EUR) Multi-timeframe synchronization: displays the same ADR value on daily, H1, M30, or any other intraday timeframe Historical navigation: ADR automatically adjusts when you move back in time on the chart, enabling precise backtesting of your strategies Customizable period: default 10 days, adjustable to your needs (14, 20, 30 days, etc.) Why This Indicator? Classic ADR indicators only display the real-time value in a static table. This one plots a historical curve that evolves over time, allowing you to see the ADR that was actually available at each moment in the past. Usage: Ideal for EUR/USD futures (6E) traders who want to: Backtest their strategies with realistic ADR data Assess historical market volatility Define profit targets and stop-losses based on average ADR Technical Note: The indicator automatically detects your timeframe and applies the appropriate synchronization between daily and intraday data to ensure consistent calculations.
Pine Script® indicator
by fabriceviguier
Singular Spectrum Decomposition [LuxAlgo]The Singular Spectrum Decomposition indicator is a powerful analytical tool that decomposes price action into distinct, interpretable components—Trend, Periodic cycles, and Noise—using the Singular Spectrum Analysis (SSA) methodology. It provides traders with a clear view of underlying market structures and offers a jump-free, extrapolated trend forecast based on Linear Recurrence Relations (LRR). Warning: This decomposition is displayed retrospectively ; historical values observed are subject to repainting . 🔶 USAGE The indicator operates by analyzing a specific window of recent price data to extract its most significant internal dynamics. It splits the "messy" raw price into four visual layers: Trend (Overlay): The primary low-frequency component, plotted directly on the price chart. This represents the core directional bias of the asset. Long Term Periodic (P1): The most dominant cyclical component, typically representing major swings or seasonalities. Short Term Periodic (P2): The second most dominant cycle, capturing faster oscillations and intermediate pullbacks. Noise: The high-frequency residual data that lacks a consistent pattern, useful for identifying market volatility or "washout" periods. 🔹 Cycle Exhaustion (P1/P2 Extremes) Traders can monitor the separate indicator pane to identify when cyclical components (P1 and P2) reach historical extremes. When the Long Term Periodic (P1) line begins to curve back toward the zero line after a prolonged extension, it often signals "cycle exhaustion," suggesting that the current swing is losing momentum and a reversal or consolidation may be imminent. 🔹 Trend-Forecast Confluence & Mean Reversion The dashed Trend extrapolation acts as a projected path for the market's core bias. If the current market price is significantly far from the solid Trend line while the forecast indicates a flattening or reversal, traders can look for mean-reversion opportunities. A price returning to a rising Trend forecast confirms the trend's strength, while a price crossing through a flat Trend forecast suggests a structural shift. 🔹 Timing Entries with Dashboard Metrics The "Average Period" displayed on the dashboard provides a mathematical blueprint for entry timing. For example, if the Short Term (P2) Average Period is 20 bars, a trader might look for long entries approximately 10 bars after a peak (the expected trough). By aligning these peak-to-trough measurements with the Trend's direction, users can improve the precision of their entries within a trending market. 🔹 Filtering Fakeouts with the Noise Component The Noise component helps distinguish between high-conviction moves and market "static." A sharp price breakout accompanied by a relatively flat Noise component suggests a sustainable, structurally supported move. Conversely, if a breakout occurs while the Noise component is spiking aggressively, it may indicate a "washout" or a liquidity-driven fakeout that lacks a fundamental trend shift. 🔶 DETAILS The script implements a full SSA pipeline: Embedding (creating a trajectory matrix), Singular Value Decomposition (via eigendecomposition of the covariance matrix), and Diagonal Averaging (reconstructed the time series). 🔹 Jump-Free Extrapolation A common issue with LRR-based forecasts is a vertical "jump" at the connection point between historical data and the forecast. This tool solves this by calculating the relative deltas of the LRR projection and anchoring them to the final value of the smoothed SSA reconstruction. This ensures a seamless visual transition while maintaining the mathematical integrity of the projected trajectory. 🔹 Dashboard Metrics The indicator includes a real-time dashboard that calculates the "Average Period" of the periodic components using zero-crossing detection. This allows traders to quantify the frequency of cycles (e.g., a 40-bar cycle vs. a 15-bar cycle) without manual measurement. 🔶 SETTINGS Window Length (L): The embedding window. Larger values capture longer cycles and provide a smoother trend, but may increase lag in the decomposition. Buffer Length (N): The number of recent bars used for the static decomposition. Forecast Length: The number of bars to extrapolate the Trend component into the future. Show Trend on Price: Toggles the visibility of the reconstructed trend line on the main chart. Show Periodic/Noise: Toggles the visibility of the individual sub-components in the indicator pane. Show Extrapolation: Enables or disables the dashed forecast line for the trend. Dashboard Settings: Controls the visibility, position, and size of the metrics table.
Pine Script® indicator
by LuxAlgo
Z-Score (Normal Distribution ) with AlertsStatistical Edge: Z-Score (Normal Distribution) Indicator Concept & Logic The Z-Score Indicator is a statistical tool used to measure how many standard deviations a price is from its mean (Simple Moving Average). By applying the principles of Normal Distribution (The Gaussian Curve) to market data, this indicator identifies whether a price move is "normal" or "extreme" relative to its recent history. In a theoretical Normal Distribution: 68.2% of data points fall within ±1 Standard Deviation (SD). 95.4% of data points fall within ±2 SD. 99.7% of data points fall within ±3 SD. When the Z-Score crosses these thresholds, it indicates that the current price action is statistically rare, often signaling potential exhaustion or a high-momentum breakout. Key Features Z-Score Line (Blue): Tracks the real-time deviation of price from the mean. ±2.0 Threshold (Dashed Lines): Represents the 95% confidence interval. Prices reaching this zone are considered "Overextended" and often see a return to the mean (Mean Reversion). ±3.0 Threshold (Solid Lines): Represents the 99.7% extreme zone. Movements here are rare and suggest either an imminent sharp reversal or the start of a "Black Swan" parabolic trend. Statistical Zones: Color-coded fills (Red for high extreme, Green for low extreme) for quick visual scanning. How to Trade with Z-Score Mean Reversion: Look for the Z-Score to penetrate the +2 or +3 levels and then cross back toward the zero line (Mean). This often signals that the "stretch" is over and price is returning to balance. Trend Strength: A Z-Score that stays consistently above +2 (or below −2) without returning to zero indicates a very strong momentum trend. Do not fight the trend in these "fat tail" events. Divergence: Watch for price making a higher high while the Z-Score makes a lower high at the +2 level; this suggests the momentum is weakening despite the price increase. Technical Settings Period (Length): The lookback period for calculating the Mean and Standard Deviation (Default: 20). Source: Usually set to Close, but can be adjusted for different strategies. Disclaimer Financial markets do not always follow a perfect Normal Distribution (they often exhibit "Leptokurtosis" or fat tails). Statistical indicators should be used as a confluence tool alongside Price Action, Volume, and other technical analysis methods. Past performance does not guarantee future results.
Pine Script® indicator
by GodeyeThelasthope
MA - ALMA 34/50/144/233 [BySel]OPTIMIZATION OF THE GAUSSIAN FILTER IN FIBONACCI REGRESSION SPACE I present the methodological construction of an indicator system based on the Arnaud Legoux Moving Average (ALMA) using Fibonacci period parameters (34, 50, 144, 233). This is not merely the selection of random numbers, but rather a synthesis between Digital Signal Processing (DSP) theory and Fractal Market Geometry. We will dissect the mathematical structure of the Gaussian filter and explain why applying it across Fibonacci timeframes creates such an effective market measurement reference framework. Here, we must conduct a deep analysis of two metaphysical hyperparameters: Offset and Sigma ($\sigma$). In the source code under discussion, alma_offset = 0.85 and alma_sigma = 6. These are revolutionary values. In traditional statistics, the peak of the normal distribution lies at the center (offset = 0.5), which produces lag equivalent to an SMA. By shifting the peak of the weighting function to the right (Offset = 0.85), we are performing an intentional “phase shift,” assigning the greatest weight to the most recent data while not entirely eliminating the influence of past data as in the crude approach of relying solely on closing prices. Mathematically, the value 0.85 approaches the Nyquist limit to ensure responsiveness without causing overshoot—that is, without being disrupted by instantaneous random fluctuations. The Sigma parameter = 6 serves to control the bandwidth width of the filter. A large Sigma makes the weighting curve narrower, concentrating energy at the Offset point, transforming ALMA into an extremely sharp low-pass filter that eliminates most high-frequency noise which conventional moving averages fail to suppress. Notably, the use of Fibonacci numbers as the filtering window length ($L$) creates the potential for wave resonance. The 144 period is not only four times the 34 period arithmetically, but within Elliott wave structure it represents the dominance of a higher-degree wave over a lower-degree wave. ALMA 144 and ALMA 233 function as fractal “shorelines,” where price returns to rebalance before continuing the trend. Thanks to ALMA’s low-lag characteristic, these dynamic support lines are far more precise than the traditional SMA 200 or EMA 200, as they accurately reflect the current center of mass of capital flow rather than the arithmetic average of distant historical data. Below is the concise Technical Guideline for traders and quantitative analysts when applying the ALMA Fibonacci system (34/50/144/233) in the stock market. GUIDELINE FOR USING THE ALMA FIBONACCI SYSTEM (34/50/144/233) Core Principle: The system employs a Gaussian filter (ALMA) to minimize lag, combined with Fibonacci numerical periods to identify the market’s energy layers. 1. Component Identification (Vector Roles) ALMA 34 (Blue – Fast Signal): Represents Short-term Momentum. Used to trigger entries and monitor immediate thrust. ALMA 50 (Red – Baseline): Represents Medium-term Flow. This is the first dynamic support zone during pullbacks. ALMA 144 (Teal – Trend Line): Represents Trend Structure. It delineates the boundary between Bull and Bear markets. ALMA 233 (Brownish-red – Boundary Line): Represents Major Support/Resistance. This is the “hard floor” or “hard ceiling” of the long-term trend. 2. Trading Strategy (Setup) A. Laminar Flow State (Strong Trend): Identification: The lines are perfectly ordered: Price > 34 > 50 > 144 > 233 (for an uptrend) and expand evenly like a fan. Action: Only look for LONG (Buy) positions. Entry: When price pulls back to ALMA 34 or at deepest to ALMA 50, followed by a bullish confirmation candle. Do not short in this structure. B. Singular Attraction State (Mean Reversion – Bottom/Top Catching): Identification: Price moves too far away from the ALMA bundle (the distance between Price and ALMA 34 becomes excessive). Action: Take partial profits. Wait for price to be drawn back toward a reasonable equilibrium zone between ALMA 50 and ALMA 144. Reversal attempt: Only consider when price touches ALMA 144 or 233 and that ALMA line still maintains an upward slope. C. Turbulent Flow State (Sideways Market): Identification: The four ALMA lines intertwine, flatten out, and the distance between them is very narrow. Action: STAY OUT (NO TRADE). This is a high-noise zone; the Gaussian filter suppresses false signals but does not create directional edge. 3. Risk Management Rules Stop Loss: Place just below ALMA 144 for short-term trades (Swing trade). Place just below ALMA 233 for position trades. Note: If a candle closes decisively below ALMA 233, the market structure has broken (Structural Break), and the position must be exited. Exit: Early exit: When price closes below ALMA 34 (momentum loss). Standard exit: When ALMA 34 crosses below ALMA 50 (confirmed capital flow reversal). 4. Important Notes (Scientific Note) Lag: This ALMA system has significantly lower lag compared to equivalent SMA/EMA. Therefore, crossover signals here are more reliable and less prone to whipsaw. Fractal Property: It can be applied on all timeframes (H1, H4, D1). However, the highest accuracy is on the D1 (Daily) timeframe for the stock market, as it filters out intraday noise.
Pine Script® indicator
by Bysel
Holy Grail by Linda Bradford Raschke Holy Grail - Linda Raschke (v6) Trend-following pullback strategy inspired by Linda Bradford Raschke & Larry Connors' classic "Holy Grail" setup from Street Smarts: High Probability Short-Term Trading Strategies. Captures high-probability continuations in strong trends by entering on low-risk pullbacks to the 20-period EMA after ADX confirms trend strength. Overview: This open-source Pine v6 strategy implements the famous "Holy Grail" setup — ironically named for its elegant simplicity. It uses only two core indicators (14-period ADX + 20-period EMA/SMA) to identify strong trends and enter on the resumption after a pullback. Designed for swing and intraday trading on trending instruments like indices (DAX, Dow, NQ, ES), forex majors, or stocks. The strategy: Filters for strong, rising trends (ADX > 30 and increasing) Waits for price to touch the 20 MA during a retracement Places simulated stop-entry orders (buy above high / sell below low of the touch bar) Applies tight initial stops + ATR-based trailing to let winners run Includes an additional exit when trend momentum fades (ADX < user-defined weak level) Best suited for 15-min to daily timeframes in volatile, directional markets. Concepts & Core Rules (from Street Smarts): Trend Strength Filter : 14-period ADX must be > threshold (default 30) and rising (ADX > ADX ) to confirm a strong trend — avoids choppy/range-bound conditions. Pullback Identification : In uptrends (close > MA), price retraces to touch the 20 MA (low ≤ MA). In downtrends (close < MA), price rallies to touch (high ≥ MA). Entry : Buy-stop above the high of the pullback bar (longs) or sell-stop below the low (shorts) — simulates breakout confirmation of trend resumption. Risk Management : Initial stop at the pullback bar's extreme (low for longs, high for shorts). Trailing stop activates using ATR multiplier. Exits : No fixed targets — trail profits + close position if ADX falls below a "weak" level (default 25), indicating potential trend exhaustion. This implementation adds modern touches: optional EMA vs SMA, ATR trailing, background trend coloring, and setup labels for easy visual confirmation. How to Use : Add to chart (works on any symbol/timeframe; best on trending ones like indices or forex). Look for green background + "HG L" label (long setup) or red background + "HG S" label (short setup). The strategy places orders on the next bar after a valid pullback — review backtest results in the Strategy Tester tab. Adjust inputs for your market/timeframe (e.g., lower ADX threshold on lower timeframes if needed). Important: This is not financial advice. Always backtest thoroughly, forward-test on demo, and use proper risk management (1-2% per trade max). Inputs : ADX Length (default 14) ADX Threshold (default 30) — must exceed and rise ADX Exit Weak (default 25) — closes when trend fades EMA Length (default 20) Use EMA instead of SMA (toggle) Trailing ATR Multiplier (default 2.5) ATR Length for trailing (default 14) Plots & Visuals : Orange 20 MA line "HG L" / "HG S" labels on setup bars Green/red background tint during strong trend conditions Notes & Limitations : Simulation Note: Pine Script cannot place persistent broker-style stop orders across bars; entries use limit ≈ stop-entry on the next bar (close approximation — many traders place manual stops in live trading). Prefers first pullback after ADX rise (highest probability); later pullbacks may work but are not filtered here. Performs best in trending, volatile conditions — avoid ranging/choppy markets (ADX filter helps). No pyramiding (one position at a time); no fixed R:R targets (focus on trailing winners). Backtest results vary by symbol/timeframe — optimize cautiously and avoid curve-fitting. Inspired by public domain rules from Street Smarts (1996) — this is an independent adaptation with Pine v6 improvements for clarity and flexibility. If you find this useful, consider liking/favoriting. Feedback welcome — happy to add alerts, fixed targets, or "first pullback only" logic in future updates! Original open-source release — feel free to study/modify.
Pine Script® strategy
by uzair2join
SentinelIndexOverview The Sentinel Macro Index is a comprehensive macro-sentiment oscillator designed to provide a high-level view of the S&P 500's underlying health. Instead of focusing on pure price action, this indicator synthesizes critical macro-economic variables and institutional flow patterns to identify "regime shifts" in the market. How it Works The index aggregates and normalizes several key pillars of market strength: Liquidity Dynamics: Tracks M2 money supply trends and central bank liquidity pulses. Credit & Yield Spreads: Monitors the yield curve and credit stress levels to gauge risk appetite. Institutional Shadow Flow: Uses proprietary volume-weighting to identify where "Smart Money" is positioning relative to retail sentiment. Insider Ratio Integration: Incorporates a calibrated baseline to filter out market noise. Key Features Dynamic Histogram: The color-coded bars represent the aggregate Macro Score. Bullish/Bearish Divergence: Identify when the price is making new highs while the Sentinel Score is declining—a classic sign of institutional distribution. Overbought/Oversold Thresholds: Helps identify exhausted trends where macro fundamentals no longer support the current price action. How to Read the Indicator Positive (Green/High): Strong macro tailwinds. Institutional accumulation and favorable liquidity conditions. Negative (Red/Low): Macro headwinds. Liquidity withdrawal or credit stress. The "Zero" Line: Acts as a pivot point. Crossing the zero line often signals a medium-to-long term change in market regime. Disclaimer This indicator is for educational and research purposes only. It does not constitute financial advice. Past performance of macro correlations is not indicative of future results.
Pine Script® indicator
by luigiloconsole72
Improved McGinley DynamicImproved McGinley Dynamic Description The McGinley Dynamic is an adaptive moving average originally developed by John R. McGinley. Unlike SMA or EMA, which use fixed smoothing, McGinley adjusts dynamically to market speed. This version includes implementation refinements and stability safeguards ensuring consistent behavior in Pine Script, along with suggested adaptations for practical trading use. Key Features The McGinley Dynamic indicator incorporates a smoothing factor that changes based on market volatility. This adaptive behavior is designed to move more slowly in upward markets (to help traders ride the trend longer), but speeds up when prices fall, reflecting the market's tendency for quicker downside moves. The core formula is: md = md + (close - md ) / (N * math.pow(close / md , 4 Implementation Notes Some public implementations of the McGinley Dynamic suffer from numerical instability under certain price conditions. This version improves consistency by adding ratio clamping, na handling and stable initialization logic. md := nz(md ) == 0 ? ta.sma(src, length) : nz(md ) + (src - nz(md )) / (length * math.pow(math.max(math.min(src / nz(md ), 2.0), 0.5), 4)) How to Use (Classic Interpretation) Traditionally, used like a moving average to spot support/resistance and align with prevailing price direction. How I Use It — Resonant Timeframe (“The Pain”) This interpretation does not treat the McGinley Dynamic as universally meaningful on all timeframes. Instead, timeframe selection is based on empirical respect — observing where price consistently interacts with the McGinley in a structurally meaningful way. Method Look for the Resonant Timeframe. They are evaluated by checking if price historically: Treats McGinley as support or dynamic equilibrium Interacts near candle body lows or within lower wicks. Shows repeatable structural respect Timeframes with random interaction are ignored. This is not parameter curve fitting we do not assume McGinley works equally well on every timeframe or instrument. No tuning is performed to optimize past results. “The Pain” Due to its recursive and adaptive formula, McGinley often behaves like a dynamic equilibrium level. This makes McGinley act as a pain threshold: the level where weak hands capitulate and new participants step in. A decisive break and acceptance below the McGinley on a resonant timeframe indicate that the prior support structure has failed, allowing price to search for a new equilibrium. Use for Short Limit Buy and general Positioning McGinley is particularly useful for placing short limit buy orders near its line during pullbacks in uptrends, or for general directional positioning (holding above it = bullish bias). It is not a standalone entry trigger or filter — it serves as a reference level within a broader system. It is advisable to use the McGinley Dynamic in conjunction with other indicators to confirm signals and manage risks. Recommended Settings The indicator is controlled by a single parameter, Length (N): Rule of Thumb: To emulate a 20-day EMA, John McGinley suggested using an N value of 10 (half the period). Recommended Timeframe Daily or above. 🇯🇵 日本語概要（Japanese Summary） McGinley インジケーターは、価格の変動に自動的に適応する移動平均で、従来の移動平均線が抱える「遅れ」や「過剰反応」を抑えることを目的としています。市場の速度に応じて計算式が調整されるため、急激な値動きでも滑らかなラインを維持しつつ、価格により密着した動きを示します。その結果、トレンドの把握やノイズの軽減に役立つ、より実用的な平均線として利用されます。 中文概要（Chinese Summary） McGinley 指標是一種能自動適應價格變化速度的移動平均線，旨在減少傳統均線常見的「延遲」與「過度反應」問題。其公式會根據市場波動調整，使線條在劇烈走勢中仍保持平滑，同時更貼近實際價格。這種特性使 McGinley 成為一種更能反映真實趨勢、並有效降低雜訊的實用型平均線工具。 Disclaimer: This script is a research tool for market structure analysis and educational purposes only. It does not constitute financial advice. Trading involves risk.
Pine Script® indicator
by et20tradeview