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Noro's Trend MAs Strategy v2.0Don't use on pairs of type "crypto/crypto"! Only for pairs like "crypto/fiat" ("BTC/USD", "BTC/CNY", "ETH/USD", "ETH/CNY", etc) Trade strategy which uses only 2 MA. The slow MA (blue) is used for definition of a trend The fast MA (red) is used for an entrance to the transaction For: - For H1 - For crypto/fiat - Good for "BTC/USD", "ETH/USD" Recomended: Long = true (if it is profitable as a result of backtests) Short = true (if it is profitable as a result of backtests) Stops = false Stop, % = any OHLC4 = any Use Fast MA = true Fast MA Period = 5 Slow MA Period = 21 Bars Q = (2 for "bitcoin/fiat" or 1 for "crypto/fiat") Extreme = true (if "crypto/fiat") In the new version 2.0 - CryptoBottom is added
Strategia Pine Script®
od ROBO_Trading
23
Noro's Trend MAs Strategy v1.9 ExtremeExtreme version of Noro's Trend MAs strategy. Don't use on pairs of type "crypto/crypto"! Only for pairs like "crypto/fiat" ("BTC/USD", "BTC/CNY", "ETH/USD", "ETH/CNY", etc) Trade strategy which uses only 2 MA. The slow MA (blue) is used for definition of a trend The fast MA (red) is used for an entrance to the transaction For: - For H1 - For crypto/fiat - Good for "BTC/USD", "ETH/USD" Recomended: Long = true (if it is profitable as a result of backtests) Short = true (if it is profitable as a result of backtests) Stops = false Stop, % = any OHLC4 = any Use Fast MA = true Fast MA Period = 5 Slow MA Period = 21 Bars Q = (2 for "bitcoin/fiat" or 1 for "crypto/fiat") Extreme = true (if "crypto/fiat") In the new version 1.9 - Extreme is added
Strategia Pine Script®
od ROBO_Trading
2
Noro's Trend MAs Strategy v1.8Trade strategy which uses only 2 MA. The slow MA (blue) is used for definition of a trend The fast MA (red) is used for an entrance to the transaction For: - For H1 - For crypto/fiat or crypto/crypto - Good for "BTC/USD", "ETH/USD", "ETH/BTC" Recomended: Long = true (if it is profitable as a result of backtests) Short = true (if it is profitable as a result of backtests) Stops = false Stop, % = any OHLC4 = any Use Fast MA = true Fast MA Period = 5 Slow MA Period = 21 Bars Q = (2 for "bitcoin/fiat" or 1 for "crypto/fiat" or 0 for "crypto/crypto") In the new version 1.8 - The second PriceChannel is added - Profit became more - Losses became less - The unnecessary types of MA are removed
Strategia Pine Script®
od ROBO_Trading
Noro's Trend MAs Strategy v1.7Trade strategy which uses only 2 MA. The slow MA (blue) is used for definition of a trend The fast MA (red) is used for an entrance to the transaction For: - For H1 - For crypto/fiat Recomended: Long = true (if it is profitable as a result of backtests) Short = true (if it is profitable as a result of backtests) Stops = false Stop, % = any Type of slow MA = 7 (only for Crypto/Fiat) Source of slow MA = close or OHLC4 Use Fast MA = true Fast MA Period = 5 Slow MA Period = 20 Bars Q = (2 for "BitCoin/Fiat" or 1 for "Fork/Fiat") In the new version 1.7 + stoporders + entry arrow (black) Types of slow MA: 1 = SMA = Simple Moving Average 2 = EMA = Exponential Moving Average 3 = VWMA = Volume-Weighted Moving Average 4 = DEMA = Double Exponential Moving Average 5 = TEMA = Triple Exponential Moving Average 6 = KAMA = Kaufman's Adaptive Moving Average 7 = Price Channel
Strategia Pine Script®
od ROBO_Trading
Noro's Trend MAs Strategy v1.6Trade strategy which uses only 2 MA. The slow MA (blue) is used for definition of a trend The fast MA (red) is used for an entrance to the transaction For: - For H1 - For crypto/fiat Recomended: Long = true (if it is profitable as a result of backtests) Short = true (if it is profitable as a result of backtests) Type of slow MA = 7 (only for Crypto/Fiat) Source of slow MA = close or OHLC4 Use Fast MA = true Fast MA Period = 5 Slow MA Period = 20 Bars Q = (2 for "BitCoin/Fiat" or 1 for "Fork/Fiat") In the new version 1.5 + Profit became more + Losses became less + Alerts + Background (lime = uptrend, red = downtrend) Types of slow MA: 1 = SMA = Simple Moving Average 2 = EMA = Exponential Moving Average 3 = VWMA = Volume-Weighted Moving Average 4 = DEMA = Double Exponential Moving Average 5 = TEMA = Triple Exponential Moving Average 6 = KAMA = Kaufman's Adaptive Moving Average 7 = Price Channel
Strategia Pine Script®
od ROBO_Trading
4
Noro's Trend MAs Strategy 1.5Trade strategy which uses only 2 MA . The slow MA (blue) is used for definition of a trend The fast MA (red) is used for an entrance to the transaction For: - For H1 - For crypto/fiat Recomended: Long = true (if it is profitable as a result of backtests) Short = true (if it is profitable as a result of backtests) Type of slow MA = 7 (only for Crypto/Fiat) Source of slow MA = clole or OHLC4 Use Fast MA = true Fast MA Period = 5 Slow MA Period = 20 Bars Q = (2 for "BitCoin/Fiat" or 1 for "Fork/Fiat") In the new version 1.5 + Source + Types of slow MA Types of slow MA: 1 = SMA = Simple Moving Average 2 = EMA = Exponential Moving Average 3 = VWMA = Volume-Weighted Moving Average 4 = DEMA = Double Exponential Moving Average 5 = TEMA = Triple Exponential Moving Average 6 = KAMA = Kaufman's Adaptive Moving Average 7 = Price Channel PS: 100000000%, because of use of a piramiding have turned out
Strategia Pine Script®
od ROBO_Trading
Noro's Trend SMA Strategy v1.4Trade strategy which uses only 2 SMA . The slow SMA (blue) is used for definition of a trend The fast SMA (red) is used for an entrance to the transaction Recomended: For H1 For crypto/fiat Long = true (if it is profitable as a result of backtests) Short = true (if it is profitable as a result of backtests) Use Fast SMA = true Fast SMA Period = 5 Slow SMA Period = 20 Bars = (2 for "BitCoin/Fiat" or 1 for "Fork/Fiat") In the new version 1.4 - Parameters are added Russian: Перевожу на понятный. В новой версии 1.4 ничего не поменялось в логике, работает так же. Но добавлены новые параметры, можно поэкспериментировать с настройками, убедиться как что выгоднее. Есть галка лонг и шорт. По умолчанию обе включены. Если убрать галку лонг, то исчезнут лонги вообще, если убрать шорт, то соответственно исчезнут шорты. По идее галку надо будет снимать если стратегия создает убыточные шорты, то их можно отключить. Смотреть в сводке показателей тестера стратегий профитны они или нет. По идее почти на всех парах крипто/фиат лучше ставить обе галки. Или убирайте галку шорт если не хотите шортить из религиозных соображений. Добавлена галка отключающая быструю SMA. То есть если галку убрать то стратегия будет её игнорировать. Таким образом, параметр Fast SMA (который 5) перестанет влиять на результаты. Однако, скорее всего без этой галки станет только хуже. Но можете проверить. Позволяет убедиться что входить в сделку по быстрой SMA в среднем немного профитнее, чем входить где попало. "Bars" - количество свечек одного цвета после после которых будет открываться сделка. По умолчанию 2. Можно от 0 до 3 ставить. Если 0 то цвет свечек игнорируется. Если 3, значит будет ждать 3 красных свечи подряд чтобы открыть лонг. Так же и с зелеными свечами для шорта. 2 - оптимально для пар типа биткойн/фиат. А для пар типа форк/фиат лучше ставить 1 свеча в параметре "Bars".
Strategia Pine Script®
od ROBO_Trading
7
CCI Level Zero Strategy (by Marcoweb) v1.0Hi guys, My strategy is ready :) Finally the zero level of the CCI gives the start and stop to my positions. As you could notice, setting up the CCI length to 340 area on 1 minute chart will let the profit factor go up to 20% from an already wonderful 16%. This is a great result cause will let profitable trades run while stopping the wrong ones with a very limited loss. What makes our profit are not several small little positions that are clearly unrepitable in real trade but few and very profitable positions in which jumping in will be easier due to their length (71 bars average). Please share with me your impressions and suggestions. Have a nice trade :)
Strategia Pine Script®
od Intuitrading
3
I_Heikin Ashi CandleWhen apply a strategy to Heikin Ashi Candle chart (HA candle), the strategy will use the open/close/high/low values of the Heikin Ashi candle to calculate the Profit and Loss, hence also affecting the Percent Profitable, Profit Factor, etc., often resulting a unrealistic high Percent Profitable and Profit Factor, which is misleading. But if you want to use the HA candle's values to calculate your indicator / strategy, but pass the normal candle's open/close/high/low values to the strategy to calculate the Profit / Loss, you can do this: 1) set up the main chart to be a normal candle chart 2) use this indicator script to plot a secondary window with indicator looks exactly like a HA-chart 3) to use the HA-candle's open/close/high/low value to calculate whatever indicator you want (you may need to create a separate script if you want to plot this indicator in a separate indicator window)
Wskaźnik Pine Script®
od samtsui
14
MACDouble + RSI (rec. 15min-2hr intrv) Uses two sets of MACD plus an RSI to either long or short. All three indicators trigger buy/sell as one (ie it's not 'IF MACD1 OR MACD2 OR RSI > 1 = buy", its more like "IF 1 AND 2 AND RSI=buy", all 3 match required for trigger) The MACD inputs should be tweaked depending on timeframe and what you are trading. If you are doing 1, 3, 5 min or real frequent trading then 21/44/20 and 32/66/29 or other high value MACDs should be considered. If you are doing longer intervals like 2, 3, 4hr then consider 9/19/9 and 21/44/20 for MACDs (experiment! I picked these example #s randomly). Ideal usage for the MACD sets is to have MACD2 inputs at around 1.5x, 2x, or 3x MACD1's inputs. Other settings to consider: try having fastlength1=macdlength1 and then (fastlength2 = macdlength2 - 2). Like 10/26/10 and 23/48/20. This seems to increase net profit since it is more likely to trigger before major price moves, but may decrease profitable trade %. Conversely, consider FL1=MCDL1 and FL2 = MCDL2 + (FL2 * 0.5). Example: 10/26/10 and 22/48/30 this can increase profitable trade %, though may cost some net profit. Feel free to message me with suggestions or questions.
Strategia Pine Script®
od RyanMartin
6
SPY Master v1.0This is a simple swing trading algorithm that uses a fast RSI-EMA to trigger buy/cover signals and a slow RSI-EMA to trigger sell/short signals for SPY, an xchange-traded fund for the S&P 500. The idea behind this strategy follows the premise that most profitable momentum trades usually occur during periods when price is trending up or down. Periods of flat price actions are usually where most unprofitable trades occur. Because we cannot predict exactly when trending periods will occur, the algorithm basically bets money on all trade opportunities during all market conditions. Despite an accuracy rate of only 40%, the algorithm's asymmetric risk/reward profile allows the average winner to be 2x the average loser. The end result is a positive (profitable) net payout. TRADING RULES: Buy/Cover = EMA3(RSI2) cross> 50 Sell/Short = EMA5(RSI2) cross< 50 BACKTEST SETTINGS: - Period = March 2011 - Present - Initial capital = $10,000 - Dividends excluded - Trading costs excluded PERFORMANCE COMPARISON: There are 657 trades, which means 1,314 orders. Assuming each order costs $2 (what I pay for at Interactive Brokers), total trading costs should be $2,628. -SPY (buy & hold) = 132.73 ---> 193.22 = +45.57% (dividends excluded) -SPY Master v1.0 = $12,649 - $2,628 = $10,021 = +100.21% DISCLAIMER: None of my ideas and posts are investment advice. Past performance is not an indication of future results. This strategy was constructed with the benefit of hindsight and its future performance cannot be guaranteed.
Strategia Pine Script®
od Stable_Camel
5
BACKTEST SCRIPT 0.999 ALPHATRADINGVIEW BACKTEST SCRIPT by Lionshare (c) 2015 THS IS A REAL ALTERNATIVE FOR LONG AWAITED TV NATIVE BACKTEST ENGINE. READY FOR USE JUST RIGHT NOW. For user provided trading strategy, executes the trades on pricedata history and continues to make it over live datafeed. Calculates and (plots on premise) the next performance statistics: profit - i.e. gross profit/loss. profit_max - maximum value of gross profit/loss. profit_per_trade - each trade's profit/loss. profit_per_stop_trade - profit/loss per "stop order" trade. profit_stop - gross profit/loss caused by stop orders. profit_stop_p - percentage of "stop orders" profit/loss in gross profit/loss. security_if_bought_back - size of security portfolio if bought back. trades_count_conseq_profit - consecutive gain from profitable series. trades_count_conseq_profit_max - maxmimum gain from consecutive profitable series achieved. trades_count_conseq_loss - same as for profit, but for loss. trades_count_conseq_loss_max - same as for profit, but for loss. trades_count_conseq_won - number of trades, that were won consecutively. trades_count_conseq_won_max - maximum number of trades, won consecutively. trades_count_conseq_lost - same as for won trades, but for lost. trades_count_conseq_lost_max - same as for won trades, but for lost. drawdown - difference between local equity highs and lows. profit_factor - profit-t-loss ratio. profit_factor_r - profit(without biggest winning trade)-to-loss ratio. recovery_factor - equity-to-drawdown ratio. expected_value - median gain value of all wins and loss. zscore - shows how much your seriality of consecutive wins/loss diverges from the one of normal distributed process. valued in sigmas. zscore of +3 or -3 sigmas means nonrandom realitonship of wins series-to-loss series. confidence_limit - the limit of confidence in zscore result. values under 0.95 are considered inconclusive. sharpe - sharpe ratio - shows the level of strategy stability. basically it is how the profit/loss is deviated around the expected value. sortino - the same as sharpe, but is calculated over the negative gains. k - Kelly criterion value, means the percentage of your portfolio, you can trade the scripted strategy for optimal risk management. k_margin - Kelly criterion recalculated to be meant as optimal margin value. DISCLAIMER : The SCRIPT is in ALPHA stage. So there could be some hidden bugs. Though the basic functionality seems to work fine. Initial documentation is not detailed. There could be english grammar mistakes also. NOW Working hard on optimizing the script. Seems, some heavier strategies (especially those using the multiple SECURITY functions) call TV processing power limitation errors. Docs are here: docs.google.com
Wskaźnik Pine Script®
od lionshare
61
CM Stochastic POP Method 1 - Jake Bernstein_V1A good friend ucsgears recently published a Stochastic Pop Indicator designed by Jake Bernstein with a modified version he found. I spoke to Jake this morning and asked if he had any updates to his Stochastic POP Trading Method. Attached is a PDF Jake published a while back (Please read for basic rules, which also Includes a New Method). I will release the Additional Method Tomorrow. Jake asked me to share that he has Updated this Method Recently. Now across all symbols he has found the Stochastic Values of 60 and 30 to be the most profitable. NOTE - This can be Significantly Optimized for certain Symbols/Markets. Jake Bernstein will be a contributor on TradingView when Backtesting/Strategies are released. Jake is one of the Top Trading System Developers in the world with 45+ years experience and he is going to teach how to create Trading Systems and how to Optimize the correct way. Below are a few Strategy Results....Soon You Will Be Able To Find Results Like This Yourself on TradingView.com BackTesting Results Example: EUR-USD Daily Chart Since 01/01/2005 Strategy 1: Go Long When Stochastic Crosses Above 60. Go Short When Stochastic Crosses Below 30. Exit Long/Short When Stochastic has a Reverse Cross of Entry Value. Results: Total Trades = 164 Profit = 50, 126 Pips Win% = 38.4% Profit Factor = 1.35 Avg Trade = 306 Pips Profit ***Most Consecutive Wins = 3 ... Most Consecutive Losses = 6 Strategy 2: Rules - Proprietary Optimization Jake Will Teach. Only Added 1 Additional Exit Rule. Results: Total Trades = 164 Profit = 62, 876 Pips!!! Win% = 38.4% Profit Factor = 1.44 Avg Trade = 383 Pips Profit ***Most Consecutive Wins = 3 ... Most Consecutive Losses = 6 Strategy 3: Rules - Proprietary Optimization Jake Will Teach. Only added 1 Additional Exit Rule. Results: Winning Percent Increases to 72.6%!!! , Same Amount of Trades. ***Most Consecutive Wins = 21 ...Most Consecutive Losses = 4 Indicator Includes: -Ability to Color Candles (CheckBox In Inputs Tab) Green = Long Trade Blue = No Trade Red = Short Trade -Color Coded Stochastic Line based on being Above/Below or In Between Entry Lines. Link To Jakes PDF with Rules dl.dropboxusercontent.com
Wskaźnik Pine Script®
od ChrisMoody
44
Vervoort Heiken Ashi Candlestick OscillatorHeiken-Ashi Candlestick Oscillator (HACO), by Sylvian Vervoort, is a digital oscillator version of the colored candlesticks. Explanation from Vervoort: "HACO is not meant to be an automatic trading system, so when there is a buy or sell signal from HACO, make sure it is confirmed by other TA techniques. HACO will certainly aid in signaling buy/sell opportunities and help you hold on to a trade, making it more profitable. The behavior of HACO is closely related to the level and speed of price change. It can be used on charts of any time frame ranging from intraday to monthly." HACO has 2 configurable length parameters - "UP TEMA length" and "Down TEMA length". Vervoort suggests having them the same value. I have also added an option to color the bars (overlay mode). More info: Trading with the Heiken-Ashi Candlestick Oscillator - Sylvian Vervoort List of my other indicators: - GDoc: docs.google.com - Chart:
Wskaźnik Pine Script®
od LazyBear
20
DEnvelope [Better Bollinger Bands]*** *** Bollinger Bands (BB) usually expand quickly after a volatility increase but contract more slowly as volatility declines. This extended time it takes for BB to contract after a volatility drop can make trading some instruments using BB alone difficult or less profitable. In the October 1998 issue of "Futures" there is an article written by Dennis McNicholl called "Better Bollinger Bands", in which the author recommends improving BB by modifying: - the center line formula & - different equations for calculating the bands. These bands, called "DEnvelope", follow price more closely and respond faster to changes in volatility with these modifications. Fore more indicators, check out my "Master Index of indicators" (Also check my published charts page for new ones I haven't added to that list): More scripts related to DEnvelope: ------------------------------------------------ - DEnvelope Bandwidth: pastebin.com - DEnvelope %B : pastebin.com Sample chart with above indicators: www.tradingview.com
Wskaźnik Pine Script®
od LazyBear
18
USDJPY Fair Value Gap + Session Strategy🎯 Overview This strategy combines Fair Value Gaps (FVGs) with session-based order flow analysis, specifically optimized for USDJPY. It identifies price inefficiencies left behind by institutional order flow during high-volatility trading sessions, offering a modern alternative to traditional lagging indicators. 🔬 What Are Fair Value Gaps? Fair Value Gaps represent areas where aggressive institutional buying or selling created "gaps" in the market structure: Bullish FVG: Price moves up so aggressively that it leaves unfilled buy orders behind Bearish FVG: Price moves down so quickly that it leaves unfilled sell orders behind Research shows approximately 80% of FVGs get "filled" (price returns to the gap) within 20-60 bars, making them highly predictable trading zones. (see the generated image above) (see the generated image above) FVG Detection Logic: text // Bullish FVG: Gap between high and current low bullishFVG = low > high and high > high // Bearish FVG: Gap between low and current high bearishFVG = high < low and low < low 🌏 Session-Based Trading Why Sessions Matter for USDJPY (see the generated image above) Tokyo Session (00:00-09:00 UTC) Highest volatility during first hour (00:00-01:00 UTC) Average movement: 51-60 pips Best for breakout strategies London/NY Overlap (13:00-16:00 UTC) Maximum liquidity and institutional participation Tightest spreads and most reliable FVG formations Optimal for continuation trades Monday Premium Effect USDJPY moves 120+ pips on Mondays due to weekend positioning Enhanced FVG formation during session opens 📊 Strategy Components (see the generated image above) 1. Fair Value Gap Detection Identifies bullish and bearish FVGs automatically Age limit: FVGs expire after 20 bars to avoid stale setups Size filter: Minimum gap size to filter out noise 2. Session Filtering Tokyo Open focus: Trades during first hour of Asian session London/NY Overlap: Captures high-liquidity institutional flows Weekend gap strategy: Enhanced signals on Monday opens 3. Volume Confirmation Requires 1.5x average volume spike Confirms institutional participation Reduces false signals 4. Trend Alignment 50 EMA filter ensures trades align with higher timeframe trend Long trades above EMA, short trades below Prevents costly counter-trend trades 5. Risk Management 2:1 Risk/Reward minimum ensures profitability with 40%+ win rate Percentage-based stops adapt to USDJPY volatility (0.3% default) Configurable position sizing 🎯 Entry Conditions (see the generated image above) Long Entry (BUY) ✅ Bullish FVG detected in previous bars ✅ Price returns to FVG zone during active trading session ✅ Volume spike above 1.5x average ✅ Price above 50 EMA (trend confirmation) ✅ Bullish candle closes within FVG zone ✅ Trading during Tokyo open OR London/NY overlap Short Entry (SELL) ✅ Bearish FVG detected in previous bars ✅ Price returns to FVG zone during active trading session ✅ Volume spike above 1.5x average ✅ Price below 50 EMA (trend confirmation) ✅ Bearish candle closes within FVG zone ✅ Trading during Tokyo open OR London/NY overlap 📈 Expected Performance Backtesting Results (Based on Similar Strategies): Win Rate: 44-59% (profitable due to high R:R ratio) Average Winner: 60-90 pips during London/NY sessions Average Loser: 30-40 pips (tight stops at FVG boundaries) Risk/Reward: 2:1 minimum, often 3:1 during strong trends Best Performance: Monday Tokyo opens and Wednesday London/NY overlaps Why This Works for USDJPY: 90% correlation with US-Japan bond yield spreads High volatility provides sufficient pip movement Heavy institutional/central bank participation creates clear FVGs Consistent volatility patterns across trading sessions ⚙️ Configurable Parameters Session Settings: Trade Tokyo Session (Enable/Disable) Trade London/NY Overlap (Enable/Disable) FVG Settings: FVG Minimum Size (Filter small gaps) Maximum FVG Age (20 bars default) Show FVG Markers (Visual display) Volume Settings: Use Volume Filter (Enable/Disable) Volume Multiplier (1.5x default) Volume Average Period (20 bars) Trend Settings: Use Trend Filter (Enable/Disable) Trend EMA Period (50 default) Risk Management: Risk/Reward Ratio (2.0 default) Stop Loss Percentage (0.3% default) 🎨 Visual Indicators 🟡 Yellow Line: 50 EMA trend filter 🟢 Green Triangles: Long entry signals 🔴 Red Triangles: Short entry signals 🟢 Green Dots: Bullish FVG zones 🔴 Red Dots: Bearish FVG zones 🟦 Blue Background: Tokyo open session 🟧 Orange Background: London/NY overlap 📊 Recommended Settings Optimal Timeframes: Primary: 5-minute charts (scalping) Secondary: 15-minute charts (swing trading) Parameter Optimization: Conservative: Stop Loss 0.2%, R:R 2:1, Volume 2.0x Balanced: Stop Loss 0.3%, R:R 2:1, Volume 1.5x (default) Aggressive: Stop Loss 0.4%, R:R 1.5:1, Volume 1.2x Risk Management: Maximum 1-2% of account per trade Daily loss limit: Stop after 3-5 consecutive losses Use fixed percentage position sizing ⚠️ Important Considerations Avoid Trading During: Major news events (BOJ interventions, NFP, FOMC) Holiday periods with reduced liquidity Low volatility Asian afternoon sessions When US-Japan yield differential narrows sharply Best Practices: Limit to 2-3 trades per session maximum Always respect the 50 EMA trend filter Never risk more than planned per trade Paper trade for 2-4 weeks before live implementation Track performance by session and day of week 🚀 How to Use Add the script to your USDJPY chart Set timeframe to 5-minute or 15-minute Adjust parameters based on your risk tolerance Enable strategy alerts for automated notifications Wait for visual signals (triangles) to appear Enter trades according to your risk management rules 📚 Strategy Foundation This strategy is based on: Smart Money Concepts (SMC): Institutional order flow tracking Market Microstructure: Understanding how FVGs form in electronic trading Quantified Risk Management: Statistical edge through proper R:R ratios Session Liquidity Patterns: Exploiting predictable volatility cycles
Strategia Pine Script®
od Stockhock
Order Flow RSI — Price / CVD / OIOrder Flow RSI blends three powerful market perspectives — Price , Cumulative Volume Delta (CVD) , and Open Interest (OI) — into one unified RSI-style oscillator. It reveals momentum and imbalance across these data streams and highlights situations where participation, liquidity, and positioning disagree — moments that often precede reversals. What it does The indicator converts: Price → RSI (classic momentum), CVD → RSI (buy/sell pressure balance), OI → RSI (position expansion/contraction) …then plots all three RSIs together on the same 0–100 scale. A fourth Consensus RSI (average of any two or all three) can optionally be shown to simplify the view. Core logic CVD engine – based on TradingView’s native volume-delta request. Modes: Continuous (default, smooth line), Anchored (resets each session), Rolling window. Open Interest – pulled automatically from the symbol’s “_OI” feed; aligns to chart timeframe for real-time flow. RSI calculation – standard RSI applied to each data stream, optionally smoothed (SMA / EMA / RMA / WMA / VWMA). Signals – optional background highlights when: All three RSIs are overbought (red) or oversold (green), or Any pair show opposite extremes (e.g., price overbought + OI oversold). Consensus RSI – arithmetic mean of the selected RSIs, summarizing overall market tone. Inputs overview CVD settings: anchor period, lower-TF delta, mode, rolling length RSI lengths: separate for price, CVD, OI Smoothing: type + period applied to all RSIs at once Consensus: choose which RSIs to average Signals: enable/disable each combination; optional alerts Levels: adjustable OB/MID/OS (default 70 / 50 / 30) Visuals: fill between active RSIs, background highlights, level lines, colors in Style tab How to read it All 3 overbought (red): broad exhaustion → possible correction All 3 oversold (green): broad depletion → possible bounce Opposite pairs: divergence between price and participation Price↑ but OI↓ (red) → weak rally, fading participation Price↓ but CVD↑ (green) → hidden accumulation Combine with structure and volume profile for confirmation. Notes Works best on assets with full CVD + OI data (futures, BTC, etc.). Use Continuous CVD for smooth RSI, Anchored for session analysis. Smoothing 2–5 EMA is a good starting point to reduce noise. All styling (colors, line types, thickness) is adjustable in the Style tab. Limitations & caveats CVD requires accurate tick/volume/delta data from your data feed. Performance may differ across instruments. OI availability varies by exchange / symbol. Where OI is absent, pairwise OI signals are not evaluated. This indicator is a tool — it generates signals of interest, not guaranteed profitable trades. Backtest and combine with your risk rules. Smoothing introduces lag; longer smoothing reduces noise but delays signals. Order Flow RSI bridges traditional momentum analysis and order-flow context — giving a multi-dimensional view of when markets are truly stretched or quietly reloading. Sometimes it works, sometimes it doesn't.
Wskaźnik Pine Script®
od exploretranspose
T3 ATR [DCAUT]█ T3 ATR 📊 ORIGINALITY & INNOVATION The T3 ATR indicator represents an important enhancement to the traditional Average True Range (ATR) indicator by incorporating the T3 (Tilson Triple Exponential Moving Average) smoothing algorithm. While standard ATR uses fixed RMA (Running Moving Average) smoothing, T3 ATR introduces a configurable volume factor parameter that allows traders to adjust the smoothing characteristics from highly responsive to heavily smoothed output. This innovation addresses a fundamental limitation of traditional ATR: the inability to adapt smoothing behavior without changing the calculation period. With T3 ATR, traders can maintain a consistent ATR period while adjusting the responsiveness through the volume factor, making the indicator adaptable to different trading styles, market conditions, and timeframes through a single unified implementation. The T3 algorithm's triple exponential smoothing with volume factor control provides improved signal quality by reducing noise while maintaining better responsiveness compared to traditional smoothing methods. This makes T3 ATR particularly valuable for traders who need to adapt their volatility measurement approach to varying market conditions without switching between multiple indicator configurations. 📐 MATHEMATICAL FOUNDATION The T3 ATR calculation process involves two distinct stages: Stage 1: True Range Calculation The True Range (TR) is calculated using the standard formula: TR = max(high - low, |high - close |, |low - close |) This captures the greatest of the current bar's range, the gap from the previous close to the current high, or the gap from the previous close to the current low, providing a comprehensive measure of price movement that accounts for gaps and limit moves. Stage 2: T3 Smoothing Application The True Range values are then smoothed using the T3 algorithm, which applies six exponential moving averages in succession: First Layer: e1 = EMA(TR, period), e2 = EMA(e1, period) Second Layer: e3 = EMA(e2, period), e4 = EMA(e3, period) Third Layer: e5 = EMA(e4, period), e6 = EMA(e5, period) Final Calculation: T3 = c1×e6 + c2×e5 + c3×e4 + c4×e3 The coefficients (c1, c2, c3, c4) are derived from the volume factor (VF) parameter: a = VF / 2 c1 = -a³ c2 = 3a² + 3a³ c3 = -6a² - 3a - 3a³ c4 = 1 + 3a + a³ + 3a² The volume factor parameter (0.0 to 1.0) controls the weighting of these coefficients, directly affecting the balance between responsiveness and smoothness: Lower VF values (approaching 0.0): Coefficients favor recent data, resulting in faster response to volatility changes with minimal lag but potentially more noise Higher VF values (approaching 1.0): Coefficients distribute weight more evenly across the smoothing layers, producing smoother output with reduced noise but slightly increased lag 📊 COMPREHENSIVE SIGNAL ANALYSIS Volatility Level Interpretation: High Absolute Values: Indicate strong price movements and elevated market activity, suggesting larger position risks and wider stop-loss requirements, often associated with trending markets or significant news events Low Absolute Values: Indicate subdued price movements and quiet market conditions, suggesting smaller position risks and tighter stop-loss opportunities, often associated with consolidation phases or low-volume periods Rapid Increases: Sharp spikes in T3 ATR often signal the beginning of significant price moves or market regime changes, providing early warning of increased trading risk Sustained High Levels: Extended periods of elevated T3 ATR indicate sustained trending conditions with persistent volatility, suitable for trend-following strategies Sustained Low Levels: Extended periods of low T3 ATR indicate range-bound conditions with suppressed volatility, suitable for mean-reversion strategies Volume Factor Impact on Signals: Low VF Settings (0.0-0.3): Produce responsive signals that quickly capture volatility changes, suitable for short-term trading but may generate more frequent color changes during minor fluctuations Medium VF Settings (0.4-0.7): Provide balanced signal quality with moderate responsiveness, filtering out minor noise while capturing significant volatility changes, suitable for swing trading High VF Settings (0.8-1.0): Generate smooth, stable signals that filter out most noise and focus on major volatility trends, suitable for position trading and long-term analysis 🎯 STRATEGIC APPLICATIONS Position Sizing Strategy: Determine your risk per trade (e.g., 1% of account capital - adjust based on your risk tolerance and experience) Decide your stop-loss distance multiplier (e.g., 2.0x T3 ATR - this varies by market and strategy, test different values) Calculate stop-loss distance: Stop Distance = Multiplier × Current T3 ATR Calculate position size: Position Size = (Account × Risk %) / Stop Distance Example: $10,000 account, 1% risk, T3 ATR = 50 points, 2x multiplier → Position Size = ($10,000 × 0.01) / (2 × 50) = $100 / 100 points = 1 unit per point Important: The ATR multiplier (1.5x - 3.0x) should be determined through backtesting for your specific instrument and strategy - using inappropriate multipliers may result in stops that are too tight (frequent stop-outs) or too wide (excessive losses) Adjust the volume factor to match your trading style: lower VF for responsive stop distances in short-term trading, higher VF for stable stop distances in position trading Dynamic Stop-Loss Placement: Determine your risk tolerance multiplier (typically 1.5x to 3.0x T3 ATR) For long positions: Set stop-loss at entry price minus (multiplier × current T3 ATR value) For short positions: Set stop-loss at entry price plus (multiplier × current T3 ATR value) Trail stop-losses by recalculating based on current T3 ATR as the trade progresses Adjust the volume factor based on desired stop-loss stability: higher VF for less frequent adjustments, lower VF for more adaptive stops Market Regime Identification: Calculate a reference volatility level using a longer-period moving average of T3 ATR (e.g., 50-period SMA) High Volatility Regime: Current T3 ATR significantly above reference (e.g., 120%+) - favor trend-following strategies, breakout trades, and wider targets Normal Volatility Regime: Current T3 ATR near reference (e.g., 80-120%) - employ standard trading strategies appropriate for prevailing market structure Low Volatility Regime: Current T3 ATR significantly below reference (e.g., <80%) - favor mean-reversion strategies, range trading, and prepare for potential volatility expansion Monitor T3 ATR trend direction and compare current values to recent history to identify regime transitions early Risk Management Implementation: Establish your maximum portfolio heat (total risk across all positions, typically 2-6% of capital) For each position: Calculate position size using the formula Position Size = (Account × Individual Risk %) / (ATR Multiplier × Current T3 ATR) When T3 ATR increases: Position sizes automatically decrease (same risk %, larger stop distance = smaller position) When T3 ATR decreases: Position sizes automatically increase (same risk %, smaller stop distance = larger position) This approach maintains constant dollar risk per trade regardless of market volatility changes Use consistent volume factor settings across all positions to ensure uniform risk measurement 📋 DETAILED PARAMETER CONFIGURATION ATR Length Parameter: Default Setting: 14 periods This is the standard ATR calculation period established by Welles Wilder, providing balanced volatility measurement that captures both short-term fluctuations and medium-term trends across most markets and timeframes Selection Principles: Shorter periods increase sensitivity to recent volatility changes and respond faster to market shifts, but may produce less stable readings Longer periods emphasize sustained volatility trends and filter out short-term noise, but respond more slowly to genuine regime changes The optimal period depends on your holding time, trading frequency, and the typical volatility cycle of your instrument Consider the timeframe you trade: Intraday traders typically use shorter periods, swing traders use intermediate periods, position traders use longer periods Practical Approach: Start with the default 14 periods and observe how well it captures volatility patterns relevant to your trading decisions If ATR seems too reactive to minor price movements: Increase the period until volatility readings better reflect meaningful market changes If ATR lags behind obvious volatility shifts that affect your trades: Decrease the period for faster response Match the period roughly to your typical holding time - if you hold positions for N bars, consider ATR periods in a similar range Test different periods using historical data for your specific instrument and strategy before committing to live trading T3 Volume Factor Parameter: Default Setting: 0.7 This setting provides a reasonable balance between responsiveness and smoothness for most market conditions and trading styles Understanding the Volume Factor: Lower values (closer to 0.0) reduce smoothing, allowing T3 ATR to respond more quickly to volatility changes but with less noise filtering Higher values (closer to 1.0) increase smoothing, producing more stable readings that focus on sustained volatility trends but respond more slowly The trade-off is between immediacy and stability - there is no universally optimal setting Selection Principles: Match to your decision speed: If you need to react quickly to volatility changes for entries/exits, use lower VF; if you're making longer-term risk assessments, use higher VF Match to market character: Noisier, choppier markets may benefit from higher VF for clearer signals; cleaner trending markets may work well with lower VF for faster response Match to your preference: Some traders prefer responsive indicators even with occasional false signals, others prefer stable indicators even with some delay Practical Adjustment Guidelines: Start with default 0.7 and observe how T3 ATR behavior aligns with your trading needs over multiple sessions If readings seem too unstable or noisy for your decisions: Try increasing VF toward 0.9-1.0 for heavier smoothing If the indicator lags too much behind volatility changes you care about: Try decreasing VF toward 0.3-0.5 for faster response Make meaningful adjustments (0.2-0.3 changes) rather than small increments - subtle differences are often imperceptible in practice Test adjustments in simulation or paper trading before applying to live positions 📈 PERFORMANCE ANALYSIS & COMPETITIVE ADVANTAGES Responsiveness Characteristics: The T3 smoothing algorithm provides improved responsiveness compared to traditional RMA smoothing used in standard ATR. The triple exponential design with volume factor control allows the indicator to respond more quickly to genuine volatility changes while maintaining the ability to filter noise through appropriate VF settings. This results in earlier detection of volatility regime changes compared to standard ATR, particularly valuable for risk management and position sizing adjustments. Signal Stability: Unlike simple smoothing methods that may produce erratic signals during transitional periods, T3 ATR's multi-layer exponential smoothing provides more stable signal progression. The volume factor parameter allows traders to tune signal stability to their preference, with higher VF settings producing remarkably smooth volatility profiles that help avoid overreaction to temporary market fluctuations. Comparison with Standard ATR: Adaptability: T3 ATR allows adjustment of smoothing characteristics through the volume factor without changing the ATR period, whereas standard ATR requires changing the period length to alter responsiveness, potentially affecting the fundamental volatility measurement Lag Reduction: At lower volume factor settings, T3 ATR responds more quickly to volatility changes than standard ATR with equivalent periods, providing earlier signals for risk management adjustments Noise Filtering: At higher volume factor settings, T3 ATR provides superior noise filtering compared to standard ATR, producing cleaner signals for long-term analysis without sacrificing volatility measurement accuracy Flexibility: A single T3 ATR configuration can serve multiple trading styles by adjusting only the volume factor, while standard ATR typically requires multiple instances with different periods for different trading applications Suitable Use Cases: T3 ATR is well-suited for the following scenarios: Dynamic Risk Management: When position sizing and stop-loss placement need to adapt quickly to changing volatility conditions Multi-Style Trading: When a single volatility indicator must serve different trading approaches (day trading, swing trading, position trading) Volatile Markets: When standard ATR produces too many false volatility signals during choppy conditions Systematic Trading: When algorithmic systems require a single, configurable volatility input that can be optimized for different instruments Market Regime Analysis: When clear identification of volatility expansion and contraction phases is critical for strategy selection Known Limitations: Like all technical indicators, T3 ATR has limitations that users should understand: Historical Nature: T3 ATR is calculated from historical price data and cannot predict future volatility with certainty Smoothing Trade-offs: The volume factor setting involves a trade-off between responsiveness and smoothness - no single setting is optimal for all market conditions Extreme Events: During unprecedented market events or gaps, T3 ATR may not immediately reflect the full scope of volatility until sufficient data is processed Relative Measurement: T3 ATR values are most meaningful in relative context (compared to recent history) rather than as absolute thresholds Market Context Required: T3 ATR measures volatility magnitude but does not indicate price direction or trend quality - it should be used in conjunction with directional analysis Performance Expectations: T3 ATR is designed to help traders measure and adapt to changing market volatility conditions. When properly configured and applied: It can help reduce position risk during volatile periods through appropriate position sizing It can help identify optimal times for more aggressive position sizing during stable periods It can improve stop-loss placement by adapting to current market conditions It can assist in strategy selection by identifying volatility regimes However, volatility measurement alone does not guarantee profitable trading. T3 ATR should be integrated into a comprehensive trading approach that includes directional analysis, proper risk management, and sound trading psychology. USAGE NOTES This indicator is designed for technical analysis and educational purposes. T3 ATR provides adaptive volatility measurement but has limitations and should not be used as the sole basis for trading decisions. The indicator measures historical volatility patterns, and past volatility characteristics do not guarantee future volatility behavior. Market conditions can change rapidly, and extreme events may produce volatility readings that fall outside historical norms. Traders should combine T3 ATR with directional analysis tools, support/resistance analysis, and other technical indicators to form a complete trading strategy. Proper backtesting and forward testing with appropriate risk management is essential before applying T3 ATR-based strategies to live trading. The volume factor parameter should be optimized for specific instruments and trading styles through careful testing rather than assuming default settings are optimal for all applications.
Wskaźnik Pine Script®
od DCAUT
RSI Bollinger Bands [DCAUT]█ RSI Bollinger Bands 📊 ORIGINALITY & INNOVATION The RSI Bollinger Bands indicator represents a meaningful advancement in momentum analysis by combining two proven technical tools: the Relative Strength Index (RSI) and Bollinger Bands. This combination addresses a significant limitation in traditional RSI analysis - the use of fixed overbought/oversold thresholds (typically 70/30) that fail to adapt to changing market volatility conditions. Core Innovation: Rather than relying on static threshold levels, this indicator applies Bollinger Bands statistical analysis directly to RSI values, creating dynamic zones that automatically adjust based on recent momentum volatility. This approach helps reduce false signals during low volatility periods while remaining sensitive to genuine extremes during high volatility conditions. Key Enhancements Over Traditional RSI: Dynamic Thresholds: Overbought/oversold zones adapt to market conditions automatically, eliminating the need for manual threshold adjustments across different instruments and timeframes Volatility Context: Band width provides immediate visual feedback about momentum volatility, helping traders distinguish between stable trends and erratic movements Reduced False Signals: During ranging markets, narrower bands filter out minor RSI fluctuations that would trigger traditional fixed-threshold signals Breakout Preparation: Band squeeze patterns (similar to price-based BB) signal potential momentum regime changes before they occur Self-Referencing Analysis: By measuring RSI against its own statistical behavior rather than arbitrary levels, the indicator provides more relevant context 📐 MATHEMATICAL FOUNDATION Two-Stage Calculation Process: Stage 1: RSI Calculation RSI = 100 - (100 / (1 + RS)) where RS = Average Gain / Average Loss over specified period The RSI normalizes price momentum into a bounded 0-100 scale, making it ideal for statistical band analysis. Stage 2: Bollinger Bands on RSI Basis = MA(RSI, BB Length) Upper Band = Basis + (StdDev(RSI, BB Length) × Multiplier) Lower Band = Basis - (StdDev(RSI, BB Length) × Multiplier) Band Width = Upper Band - Lower Band The Bollinger Bands measure RSI's standard deviation from its own moving average, creating statistically-derived dynamic zones. Statistical Interpretation: Under normal distribution assumptions with default 2.0 multiplier, approximately 95% of RSI values should fall within the bands Band touches represent statistically significant momentum extremes relative to recent behavior Band width expansion indicates increasing momentum volatility (strengthening trend or increasing uncertainty) Band width contraction signals momentum consolidation and potential regime change preparation 📊 COMPREHENSIVE SIGNAL ANALYSIS Visual Color Signals: This indicator features dynamic color fills that highlight extreme momentum conditions: Green Fill (Above Upper Band): Appears when RSI breaks above the upper band, indicating exceptionally strong bullish momentum Represents dynamic overbought zone - not necessarily a reversal signal but a warning of extreme conditions In strong uptrends, green fills can persist as RSI "rides the band" - this indicates sustained momentum strength Exit of green zone (RSI falling back below upper band) often signals initial momentum weakening Red Fill (Below Lower Band): Appears when RSI breaks below the lower band, indicating exceptionally weak bearish momentum Represents dynamic oversold zone - potential reversal or continuation signal depending on trend context In strong downtrends, red fills can persist as RSI "rides the band" - this indicates sustained selling pressure Exit of red zone (RSI rising back above lower band) often signals initial momentum recovery Position-Based Signals: Upper Band Interactions: RSI Touching Upper Band: Dynamic overbought condition - momentum is extremely strong relative to recent volatility, potential exhaustion or continuation depending on trend context RSI Riding Upper Band: Sustained strong momentum, often seen in powerful trends, not necessarily an immediate reversal signal but warrants monitoring for exhaustion RSI Crossing Below Upper Band: Initial momentum weakening signal, particularly significant if accompanied by price divergence Lower Band Interactions: RSI Touching Lower Band: Dynamic oversold condition - momentum is extremely weak relative to recent volatility, potential reversal or continuation of downtrend RSI Riding Lower Band: Sustained weak momentum, common in strong downtrends, monitor for potential exhaustion RSI Crossing Above Lower Band: Initial momentum strengthening signal, early indication of potential reversal or consolidation Basis Line Signals: RSI Above Basis: Bullish momentum regime - upward pressure dominant RSI Below Basis: Bearish momentum regime - downward pressure dominant Basis Crossovers: Momentum regime shifts, more significant when accompanied by band width changes RSI Oscillating Around Basis: Balanced momentum, often indicates ranging market conditions Volatility-Based Signals: Band Width Patterns: Narrow Bands (Squeeze): Momentum volatility compression, often precedes significant directional moves, similar to price coiling patterns Expanding Bands: Increasing momentum volatility, indicates trend acceleration or growing uncertainty Narrowest Band in 100 Bars: Extreme compression alert, high probability of upcoming volatility expansion Advanced Pattern Recognition: Divergence Analysis: Bullish Divergence: Price makes lower lows while RSI touches or stays above previous lower band touch, suggests downward momentum weakening Bearish Divergence: Price makes higher highs while RSI touches or stays below previous upper band touch, suggests upward momentum weakening Hidden Bullish: Price makes higher lows while RSI makes lower lows at the lower band, indicates strong underlying bullish momentum Hidden Bearish: Price makes lower highs while RSI makes higher highs at the upper band, indicates strong underlying bearish momentum Band Walk Patterns: Upper Band Walk: RSI consistently touching or staying near upper band indicates exceptionally strong trend, wait for clear break below basis before considering reversal Lower Band Walk: RSI consistently at lower band signals very weak momentum, requires break above basis for reversal confirmation 🎯 STRATEGIC APPLICATIONS Strategy 1: Mean Reversion Trading Setup Conditions: Market Type: Ranging or choppy markets with no clear directional trend Timeframe: Works best on lower timeframes (5m-1H) or during consolidation phases Band Characteristic: Normal to narrow band width Entry Rules: Long Entry: RSI touches or crosses below lower band, wait for RSI to start rising back toward basis before entry Short Entry: RSI touches or crosses above upper band, wait for RSI to start falling back toward basis before entry Confirmation: Use price action confirmation (candlestick reversal patterns) at band touches Exit Rules: Target: RSI returns to basis line or opposite band Stop Loss: Fixed percentage or below recent swing low/high Time Stop: Exit if position not profitable within expected timeframe Strategy 2: Trend Continuation Trading Setup Conditions: Market Type: Clear trending market with higher highs/lower lows Timeframe: Medium to higher timeframes (1H-Daily) Band Characteristic: Expanding or wide bands indicating strong momentum Entry Rules: Long Entry in Uptrend: Wait for RSI to pull back to basis line or slightly below, enter when RSI starts rising again Short Entry in Downtrend: Wait for RSI to rally to basis line or slightly above, enter when RSI starts falling again Avoid Counter-Trend: Do not fade RSI at bands during strong trends (band walk patterns) Exit Rules: Trailing Stop: Move stop to break-even when RSI reaches opposite band Trend Break: Exit when RSI crosses basis against trend direction with conviction Band Squeeze: Reduce position size when bands start narrowing significantly Strategy 3: Breakout Preparation Setup Conditions: Market Type: Consolidating market after significant move or at key technical levels Timeframe: Any timeframe, but longer timeframes provide more reliable breakouts Band Characteristic: Narrowest band width in recent 100 bars (squeeze alert) Preparation Phase: Identify band squeeze condition (bands at multi-period narrowest point) Monitor price action for consolidation patterns (triangles, rectangles, flags) Prepare bracket orders for both directions Wait for band expansion to begin Entry Execution: Breakout Confirmation: Enter in direction of RSI band breakout (RSI breaks above upper band or below lower band) Price Confirmation: Ensure price also breaks corresponding technical level Volume Confirmation: Look for volume expansion supporting the breakout Risk Management: Stop Loss: Place beyond consolidation pattern opposite extreme Position Sizing: Use smaller size due to false breakout risk Quick Exit: Exit immediately if RSI returns inside bands within 1-3 bars Strategy 4: Multi-Timeframe Analysis Timeframe Selection: Higher Timeframe: Daily or 4H for trend context Trading Timeframe: 1H or 15m for entry signals Confirmation Timeframe: 5m or 1m for precise entry timing Analysis Process: Trend Identification: Check higher timeframe RSI position relative to bands, trade only in direction of higher timeframe momentum Setup Formation: Wait for trading timeframe RSI to show pullback to basis in trending direction Entry Timing: Use confirmation timeframe RSI band touch or crossover for precise entry Alignment Confirmation: All timeframes should show RSI moving in same direction for highest probability setups 📋 DETAILED PARAMETER CONFIGURATION RSI Source: Close (Default): Standard price point, balances responsiveness and reliability HL2: Reduces noise from intrabar volatility, provides smoother RSI values HLC3 or OHLC4: Further smoothing for very choppy markets, slower to respond but more stable Volume-Weighted: Consider using VWAP or volume-weighted prices for additional liquidity context RSI Length Parameter: Shorter Periods (5-10): More responsive but generates more signals, suitable for scalping or very active trading, higher noise level Standard (14): Default and most widely used setting, proven balance between responsiveness and reliability, recommended starting point Longer Periods (21-30): Smoother momentum measurement, fewer but potentially more reliable signals, better for swing trading or position trading Optimization Note: Test across different market regimes, optimal length often varies by instrument volatility characteristics RSI MA Type Parameter: RMA (Default): Wilder's original smoothing method, provides traditional RSI behavior with balanced lag, most widely recognized and tested, recommended for standard technical analysis EMA: Exponential smoothing gives more weight to recent values, faster response to momentum changes, suitable for active trading and trending markets, reduces lag compared to RMA SMA: Simple average treats all periods equally, smoothest output with highest lag, best for filtering noise in choppy markets, useful for long-term position analysis WMA: Weighted average emphasizes recent data less aggressively than EMA, middle ground between SMA and EMA characteristics, balanced responsiveness for swing trading Advanced Options: Full access to 25+ moving average types including HMA (reduced lag), DEMA/TEMA (enhanced responsiveness), KAMA/FRAMA (adaptive behavior), T3 (smoothness), Kalman Filter (optimal estimation) Selection Guide: RMA for traditional analysis and backtesting consistency, EMA for faster signals in trending markets, SMA for stability in ranging markets, adaptive types (KAMA/FRAMA) for varying volatility regimes BB Length Parameter: Short Length (10-15): Tighter bands that react quickly to RSI changes, more frequent band touches, suitable for active trading styles Standard (20): Balanced approach providing meaningful statistical context without excessive lag Long Length (30-50): Smoother bands that filter minor RSI fluctuations, captures only significant momentum extremes, fewer but higher quality signals Relationship to RSI Length: Consider BB Length greater than RSI Length for cleaner signals BB MA Type Parameter: SMA (Default): Standard Bollinger Bands calculation using simple moving average for basis line, treats all periods equally, widely recognized and tested approach EMA: Exponential smoothing for basis line gives more weight to recent RSI values, creates more responsive bands that adapt faster to momentum changes, suitable for trending markets RMA: Wilder's smoothing provides consistent behavior aligned with traditional RSI when using RMA for both RSI and BB calculations WMA: Weighted average for basis line balances recent emphasis with historical context, middle ground between SMA and EMA responsiveness Advanced Options: Full access to 25+ moving average types for basis calculation, including HMA (reduced lag), DEMA/TEMA (enhanced responsiveness), KAMA/FRAMA (adaptive to volatility changes) Selection Guide: SMA for standard Bollinger Bands behavior and backtesting consistency, EMA for faster band adaptation in dynamic markets, matching RSI MA type creates unified smoothing behavior BB Multiplier Parameter: Conservative (1.5-1.8): Tighter bands resulting in more frequent touches, useful in low volatility environments, higher signal frequency but potentially more false signals Standard (2.0): Default setting representing approximately 95% confidence interval under normal distribution, widely accepted statistical threshold Aggressive (2.5-3.0): Wider bands capturing only extreme momentum conditions, fewer but potentially more significant signals, reduces false signals in high volatility Adaptive Approach: Consider adjusting multiplier based on instrument characteristics, lower multiplier for stable instruments, higher for volatile instruments Parameter Optimization Workflow: Start with default parameters (RSI:14, BB:20, Mult:2.0) Test across representative sample period including different market regimes Adjust RSI length based on desired responsiveness vs stability tradeoff Tune BB length to match your typical holding period Modify multiplier to achieve desired signal frequency Validate on out-of-sample data to avoid overfitting Document optimal parameters for different instruments and timeframes Reference Levels Display: Enabled (Default): Shows traditional 30/50/70 levels for comparison with dynamic bands, helps visualize the adaptive advantage Disabled: Cleaner chart focusing purely on dynamic zones, reduces visual clutter for experienced users Educational Value: Keeping reference levels visible helps understand how dynamic bands differ from fixed thresholds across varying market conditions 📈 PERFORMANCE ANALYSIS & COMPETITIVE ADVANTAGES Comparison with Traditional RSI: Fixed Threshold RSI Limitations: In ranging low-volatility markets: RSI rarely reaches 70/30, missing tradable extremes In trending high-volatility markets: RSI frequently breaks through 70/30, generating excessive false reversal signals Across different instruments: Same thresholds applied to volatile crypto and stable forex pairs produce inconsistent results Threshold Adjustment Problem: Manually changing thresholds for different conditions is subjective and lagging RSI Bollinger Bands Advantages: Automatic Adaptation: Bands adjust to current volatility regime without manual intervention Consistent Logic: Same statistical approach works across different instruments and timeframes Reduced False Signals: Band width filtering helps distinguish meaningful extremes from noise Additional Information: Band width provides volatility context missing in standard RSI Objective Extremes: Statistical basis (standard deviations) provides objective extreme definition Comparison with Price-Based Bollinger Bands: Price BB Characteristics: Measures absolute price volatility Affected by large price gaps and outliers Band position relative to price not normalized Difficult to compare across different price scales RSI BB Advantages: Normalized Scale: RSI's 0-100 bounds make band interpretation consistent across all instruments Momentum Focus: Directly measures momentum extremes rather than price extremes Reduced Gap Impact: RSI calculation smooths price gaps impact on band calculations Comparable Analysis: Same RSI BB appearance across stocks, forex, crypto enables consistent strategy application Performance Characteristics: Signal Quality: Higher Signal-to-Noise Ratio: Dynamic bands help filter RSI oscillations that don't represent meaningful extremes Context-Aware Alerts: Band width provides volatility context helping traders adjust position sizing and stop placement Reduced Whipsaws: During consolidations, narrower bands prevent premature signals from minor RSI movements Responsiveness: Adaptive Lag: Band calculation introduces some lag, but this lag is adaptive to current conditions rather than fixed Faster Than Manual Adjustment: Automatic band adjustment is faster than trader's ability to manually modify thresholds Balanced Approach: Combines RSI's inherent momentum lag with BB's statistical smoothing for stable yet responsive signals Versatility: Multi-Strategy Application: Supports both mean reversion (ranging markets) and trend continuation (trending markets) approaches Universal Instrument Coverage: Works effectively across equities, forex, commodities, cryptocurrencies without parameter changes Timeframe Agnostic: Same interpretation applies from 1-minute charts to monthly charts Limitations and Considerations: Known Limitations: Dual Lag Effect: Combines RSI's momentum lag with BB's statistical lag, making it less suitable for very short-term scalping Requires Volatility History: Needs sufficient bars for BB calculation, less effective immediately after major regime changes Statistical Assumptions: Assumes RSI values are somewhat normally distributed, extreme trending conditions may violate this Not a Standalone System: Like all indicators, should be combined with price action analysis and risk management Optimal Use Cases: Best for swing trading and position trading timeframes Most effective in markets with alternating volatility regimes Ideal for traders who use multiple instruments and timeframes Suitable for systematic trading approaches requiring consistent logic Suboptimal Conditions: Very low timeframes (< 5 minutes) where lag becomes problematic Instruments with extreme volatility spikes (gap-prone markets) Markets in strong persistent trends where mean reversion rarely occurs Periods immediately following major structural changes (new trading regime) USAGE NOTES This indicator is designed for technical analysis and educational purposes to help traders understand the interaction between momentum measurement and statistical volatility bands. The RSI Bollinger Bands has limitations and should not be used as the sole basis for trading decisions. Important Considerations: No Predictive Guarantee: Past band touches and patterns do not guarantee future price behavior Market Regime Dependency: Indicator performance varies significantly between trending and ranging market conditions Complementary Analysis Required: Should be used alongside price action, support/resistance levels, and fundamental analysis Risk Management Essential: Always use proper position sizing, stop losses, and risk controls regardless of signal quality Parameter Sensitivity: Different instruments and timeframes may require parameter optimization for optimal results Continuous Monitoring: Band characteristics change with market conditions, requiring ongoing assessment Recommended Supporting Analysis: Price structure analysis (support/resistance, trend lines) Volume confirmation for breakout signals Multiple timeframe alignment Market context awareness (news events, session times) Correlation analysis with related instruments The indicator aims to provide adaptive momentum analysis that adjusts to changing market volatility, but traders must apply sound judgment, proper risk management, and comprehensive market analysis in their decision-making process.
Wskaźnik Pine Script®
od DCAUT