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스크립트에서 "bitcoin"에 대해 찾기

ANN MACD (BTC) Logic is correct. But I prefer to say experimental because the sample set is narrow. (300 columns) Let's start: 6 inputs : Volume Change , Bollinger Low Band chg. , Bollinger Mid Band chg., Bollinger Up Band chg. , RSI change , MACD histogram change. 1 output : Future bar change (Historical) Training timeframe : 15 mins (Analysis TF > 4 hours (My opinion)) Learning cycles : 337 Training error: 0.009999 Input columns: 6 Output columns: 1 Excluded columns: 0 Grid Training example rows: 301 Validating example rows: 0 Querying example rows: 0 Excluded example rows: 0 Duplicated example rows: 0 Network Input nodes connected: 6 Hidden layer 1 nodes: 8 Hidden layer 2 nodes: 0 Hidden layer 3 nodes: 0 Output nodes: 1 Learning rate : 0.6 Momentum : 0.8 More info : EDIT : This code is open source under the MIT License. If you have any improvements or corrections to suggest, please send me a pull request via the github repository github.com
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Noldo의
13
Crypto Prices InfoPanel V2Hello traders Following the introduction of ByBit to TradingView ByBit on TradingView I decided to upgrade my previous Bitcoin InfoPanel Bitcoin-Prices-InfoPanel/ Now it's more dynamic (thumbs up) but only work with Bitcoin, Ethereum and Litecoin . If you select any other asset than those 3, the script won't work This is due to a technical limitation on TradingView because I can't do more than 40 security calls per script If you don't know what the security function is, here's a reminder : Security documentation . If you don't know what is TradingView... I cannot do anything for you... Now you can use this panel to have a very cool arbitrage view directly from TradingView and use the info to gamble between brokers (not financial advice) See you all tomorrow for a huge update regarding the Strategy Builder. I'll show you how to connect it to a Backtest system ____________________________________________________________ Feel free to hit the thumbs up as it shows me that I'm not doing this for nothing and will motivate to deliver more quality content in the future. - I'm an officially approved PineEditor/LUA/MT4 approved mentor on codementor. You can request a coaching with me if you want and I'll teach you how to build kick-ass indicators and strategies Jump on a 1 to 1 coaching with me - You can also hire for a custom dev of your indicator/strategy/bot/chrome extension/python
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Daveatt의
3
Moving Average Strategy of BiznesFilosofWhat is brilliant is simple! Therefore, this strategy works very well. It is configured on bitcoin. But you can use it for other tools. Only need to change the settings. Remember that this is not a panacea, but only an assistant! You yourself have to choose which entry and exit points to choose. In more detail about strategy on my channel in YouTube. === Что гениально, то просто! Потому, эта стратегия очень хорошо работает. Настроена она на биткоин. Но можно использовать и для других инструментов. Только нужно поменять настройки. Помните, что это не панацея, а только помощник! Вы сами должны панимать, какие выбирать точки входа и выхода. Более подробно про стратегию на моём канале в Ютуб.
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volondbf의
7
Crypto Indicators #u9tusA set of low timeframe (LTF), medium timeframe (MTF), and high timeframe (HTF) indicators for use in crypto currencies / bitcoin. Traditionally the 10, 20, 50, 100, and 200 SMAs are used in TA. With cryptos, I've found that the 8 EMA, 21, 55, and 128 SMAs backtest better, while no change in length was necessary for the 200. I wanted to combine all these into one indicator to easily add them to a chart layout, hence this script. You can customize the length of each MA to your liking in the settings, or accept the defaults. LTF Indicators: 8 EMA in blue hues, medium line stroke. MTF Indicators: 21, 55 SMA in purple hues, medium line stroke. HTF Indicators: 128, 200 SMA in yellow hues, thick line stroke. Defaults are for daily timeframes and lower; suggest changing up the intervals for weekly and monthly to: 21 -> 30 55 -> 50 128 -> 100 $BTC, $ETH, #ALTS twitter.com (c) @jhaurawachsman 20190515
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jhaurawachsman의
200/150 This a variation to my 120/60 Trend Model for the daily chart on Bitcoin, which has quite reliably been determining the over all trend as well as low risk entries within a longer term trend. It's a combination of 150 & 220 SMA, used on the 1D chart. Once price closes below both SMAs trend is an early bearish signal, while the SMAs flipping to red is later but more reliable bearish signal. For bullish trend it is the same thing just the opposite. Once the "cloud" switches red trend is bearish while once it switches green it's bullish. Bitcoin tends to get rejected by the cloud during bullish and bearish trends. Once Bitcoin pushes through the cloud the trend will typically reverse. Bitcoin trading within or close to the cloud is generally a good long or short entries, depending on the color of the cloud (red: short & green: long).
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swenlink의
1
Mayer Multiple @ Current PriceThough this script is by me, the original idea comes from a podcast I heard where Trace Mayer talks about how he does crypto valuation. It is based on current price against the 200 day moving average. This indicator script will simply plot that value as a label overlayed on your trading view chart. Best long term results occur when acquiring BTC when the multiple is 2.4 or less. For more info, google "mayer multiple" This script/indicator is strictly for educational purposes. It is not exclusive to bitcoin. To get the best look out of your charts I make the following changes. 1.Apply the indicator to your chart. 2. In the tools palette of trading view, when looking at a chart, click "Show Objects Tree" the icon displayed above the trash can. In the objects tree panel, click the preferences icon for "Mayer Multiple @ Current Price" Switch "scale" to "scale Left" 3. Then for your chart preferences (right click on chart background and select "Properties", and be sure the following are checked on the "Scales" tab Left Axis Right Axis Indicator Last Value Indicator Labels Screenshots are not allowed in this view, so I can't post screenshots, but the view above is what it should look like when you are done. For anyone who wants to see the code, here is the code of the script: Use at will, and at your own risk. //@version=3 // Created By Timothy Luce, inspired by Trace Mayer's 200 Day SMA cryptocurrency valuation method study("Mayer Multiple @ Current Price", overlay=true) currentPrice = close currentDay = security(tickerid, "D", sma(close, 200)) mayerMultiple = currentPrice/currentDay plot(mayerMultiple, color=#00ffaa, transp=100) If you want to change the color, change this line: #00ffaa
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midevilone의
rem sim v0.1every alt-coin has similarity. cause of bitcoin. always i want to delete that similarity and read the true(?) value of each coin. and i made some script for that, but not good enough. this one is different. Rem Sim (rs) removes the similarity very effectively. it make avg WaveTrend from nxt, strat, steem, ... and that is the similarity and it show true(?) WaveTrend without similarity. so if the alt-coin move like other alt-coin, the WT almost 0. sorry my bad english. if you dont understand my english. just look at that chart. also you can see source code. -------- 대부분의 알트가 어느정도 비슷한 차트를 가지는데, 그 유사성을 제거하면 어떤 모양인지 궁금해서 만들었어요. 전에 만들었던 비트코인의 영향력을 제거해주는 아이디어는 실제론 별 효용이 없는데 이건 좀 쓸만해보이네요. 웨이브트렌드의 모양으로 보여줍니다.
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ducksjc의
UCS Squeeze Momentum Overlay with AlertsAll credit to the great ucsgears. His original indicator is on this page: I just remixed the visuals and added alerts when price is released from the squeeze. I find it works well on lower timeframes for Forex and Bitcoin. Suggestions for other instruments and timeframes are welcome! When adding alerts use 'On Condition' to get the fastest alerts. Best used in conjunction with the USC_SQZ_Opt Ooscillator from this page: Possibly useful tip: the squeeze code here is great for identifying ranging markets, and can be used with other indicators to stop alerts firing in choppy markets.
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scarf의
7
Universal Stochastic Fusion (Simplified) — v6What this indicator is This indicator is called Universal Stochastic Fusion (USF). It’s a tool that helps traders see when the market might be too high (overbought) or too low (oversold), and when it might be a good time to buy or sell. ________________________________________ How it works Think of the market like a rubber band. • If the band stretches too far up, it usually snaps back down. • If it stretches too far down, it usually bounces back up. The USF indicator measures this stretch using something called the Stochastic Oscillator (just a fancy way of saying it looks at where the current price sits compared to recent highs and lows). It shows this on a scale from 0 to 100: • Near 100 → market is stretched upward (too hot). • Near 0 → market is stretched downward (too cold). • Around 50 → normal, middle ground. ________________________________________ What’s special about USF 1. Two views at once o It lets you see the market’s stretch on your current chart and on another timeframe (like a daily view). o This way, you can see the short-term and the bigger picture together. 2. Smart levels o Instead of always using the same “too high/too low” levels (like 80 and 20), it can adjust these lines automatically depending on how wild or calm the market is. 3. Buy and Sell signals o When the market looks too low and starts turning up, it can mark a BUY. o When the market looks too high and starts turning down, it can mark a SELL. 4. Extra filter (optional) o It can also use another tool (RSI) to double-check signals, so you don’t get as many false alerts. ________________________________________ How this helps traders • It helps traders avoid buying when prices are already too high. • It helps them spot possible bottoms where prices may bounce back. • It combines short-term and long-term signals so traders don’t get tricked by quick moves. ________________________________________ Where it works This indicator is universal — meaning it works on almost any market: • Stocks (like Apple, Tesla, etc.) • Forex (currencies like EUR/USD) • Crypto (Bitcoin, Ethereum, etc.) • Commodities (Gold, Oil, etc.) • Futures and Indices (S&P 500, Nasdaq, etc.) Because all these markets share the same pattern of prices going up and down too much and then pulling back, the USF can be applied everywhere. ________________________________________ 👉 In short: The Universal Stochastic Fusion is like a heat meter for the market. It tells you when prices might be too hot (good chance to sell) or too cold (good chance to buy), and it works in all markets and timeframes. ________________________________________
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SupertradeOfficial의
Adaptive Trend Following Suite [Alpha Extract]A sophisticated multi-filter trend analysis system that combines advanced noise reduction, adaptive moving averages, and intelligent market structure detection to deliver institutional-grade trend following signals. Utilizing cutting-edge mathematical algorithms and dynamic channel adaptation, this indicator provides crystal-clear directional guidance with real-time confidence scoring and market mode classification for professional trading execution. 🔶 Advanced Noise Reduction Filter Eliminates market noise using sophisticated Gaussian filtering with configurable sigma values and period optimization. The system applies mathematical weight distribution across price data to ensure clean signal generation while preserving critical trend information, automatically adjusting filter strength based on volatility conditions. advancedNoiseFilter(sourceData, filterLength, sigmaParam) => weightSum = 0.0 valueSum = 0.0 centerPoint = (filterLength - 1) / 2 for index = 0 to filterLength - 1 gaussianWeight = math.exp(-0.5 * math.pow((index - centerPoint) / sigmaParam, 2)) weightSum += gaussianWeight valueSum += sourceData * gaussianWeight valueSum / weightSum 🔶 Adaptive Moving Average Core Engine Features revolutionary volatility-responsive averaging that automatically adjusts smoothing parameters based on real-time market conditions. The engine calculates adaptive power factors using logarithmic scaling and bandwidth optimization, ensuring optimal responsiveness during trending markets while maintaining stability during consolidation phases. // Calculate adaptive parameters adaptiveLength = (periodLength - 1) / 2 logFactor = math.max(math.log(math.sqrt(adaptiveLength)) / math.log(2) + 2, 0) powerFactor = math.max(logFactor - 2, 0.5) relativeVol = avgVolatility != 0 ? volatilityMeasure / avgVolatility : 0 adaptivePower = math.pow(relativeVol, powerFactor) bandwidthFactor = math.sqrt(adaptiveLength) * logFactor 🔶 Intelligent Market Structure Analysis Employs fractal dimension calculations to classify market conditions as trending or ranging with mathematical precision. The system analyzes price path complexity using normalized data arrays and geometric path length calculations, providing quantitative market mode identification with configurable threshold sensitivity. 🔶 Multi-Component Momentum Analysis Integrates RSI and CCI oscillators with advanced Z-score normalization for statistical significance testing. Each momentum component receives independent analysis with customizable periods and significance levels, creating a robust consensus system that filters false signals while maintaining sensitivity to genuine momentum shifts. // Z-score momentum analysis rsiAverage = ta.sma(rsiComponent, zAnalysisPeriod) rsiDeviation = ta.stdev(rsiComponent, zAnalysisPeriod) rsiZScore = (rsiComponent - rsiAverage) / rsiDeviation if math.abs(rsiZScore) > zSignificanceLevel rsiMomentumSignal := rsiComponent > 50 ? 1 : rsiComponent < 50 ? -1 : rsiMomentumSignal ❓How It Works 🔶 Dynamic Channel Configuration Calculates adaptive channel boundaries using three distinct methodologies: ATR-based volatility, Standard Deviation, and advanced Gaussian Deviation analysis. The system automatically adjusts channel multipliers based on market structure classification, applying tighter channels during trending conditions and wider boundaries during ranging markets for optimal signal accuracy. dynamicChannelEngine(baselineData, channelLength, methodType) => switch methodType "ATR" => ta.atr(channelLength) "Standard Deviation" => ta.stdev(baselineData, channelLength) "Gaussian Deviation" => weightArray = array.new_float() totalWeight = 0.0 for i = 0 to channelLength - 1 gaussWeight = math.exp(-math.pow((i / channelLength) / 2, 2)) weightedVariance += math.pow(deviation, 2) * array.get(weightArray, i) math.sqrt(weightedVariance / totalWeight) 🔶 Signal Processing Pipeline Executes a sophisticated 10-step signal generation process including noise filtering, trend reference calculation, structure analysis, momentum component processing, channel boundary determination, trend direction assessment, consensus calculation, confidence scoring, and final signal generation with quality control validation. 🔶 Confidence Transformation System Applies sigmoid transformation functions to raw confidence scores, providing 0-1 normalized confidence ratings with configurable threshold controls. The system uses steepness parameters and center point adjustments to fine-tune signal sensitivity while maintaining statistical robustness across different market conditions. 🔶 Enhanced Visual Presentation Features dynamic color-coded trend lines with adaptive channel fills, enhanced candlestick visualization, and intelligent price-trend relationship mapping. The system provides real-time visual feedback through gradient fills and transparency adjustments that immediately communicate trend strength and direction changes. 🔶 Real-Time Information Dashboard Displays critical trading metrics including market mode classification (Trending/Ranging), structure complexity values, confidence scores, and current signal status. The dashboard updates in real-time with color-coded indicators and numerical precision for instant market condition assessment. 🔶 Intelligent Alert System Generates three distinct alert types: Bullish Signal alerts for uptrend confirmations, Bearish Signal alerts for downtrend confirmations, and Mode Change alerts for market structure transitions. Each alert includes detailed messaging and timestamp information for comprehensive trade management integration. 🔶 Performance Optimization Utilizes efficient array management and conditional processing to maintain smooth operation across all timeframes. The system employs strategic variable caching, optimized loop structures, and intelligent update mechanisms to ensure consistent performance even during high-volatility market conditions. This indicator delivers institutional-grade trend analysis through sophisticated mathematical modelling and multi-stage signal processing. By combining advanced noise reduction, adaptive averaging, intelligent structure analysis, and robust momentum confirmation with dynamic channel adaptation, it provides traders with unparalleled trend following precision. The comprehensive confidence scoring system and real-time market mode classification make it an essential tool for professional traders seeking consistent, high-probability trend following opportunities with mathematical certainty and visual clarity.
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AlphaExtract의
2
BTC/USD 3-Min Binary Prediction [v7.2 EN]BTC/USD 3-Minute Binary Prediction Indicator v7.2 - Complete Guide Overview This is an advanced technical analysis indicator designed for Bitcoin/USD binary options trading with 3-minute expiration times. The system aims for an 83% win rate by combining multiple analysis layers and pattern recognition. How It Works Core Prediction Logic - Timeframe: Predicts whether BTC price will be ±$25 higher (HIGH) or lower (LOW) after 3 minutes - Entry Signals: Generates HIGH/LOW signals when confidence exceeds threshold (default 75%) - Verification: Automatically tracks and displays win/loss statistics in real-time 5-Layer Filter System The indicator uses a sophisticated scoring system (0-100 points): 1. Trend Filter (25 points) - Analyzes EMA alignments and price momentum 2. Leading Indicators (25 points) - RSI and MACD divergence analysis 3. Volume Confirmation (20 points) - Detects unusual volume patterns 4. Support/Resistance (15 points) - Identifies key price levels 5. Momentum Alignment (15 points) - Measures acceleration and deceleration Pattern Recognition Automatically detects and visualizes: - Double Tops/Bottoms - Reversal patterns - Triangles - Ascending, descending, symmetrical - Channels - Trending price channels - Candlestick Patterns - Engulfing, hammer, hanging man Multi-Timeframe Analysis - Uses 1-minute and 5-minute data for confirmation - Aligns multiple timeframes for higher probability trades - Monitors trend consistency across timeframes Key Features Display Panels 1. Statistics Panel (Top Right) - Overall win rate percentage - Hourly performance (wins/losses) - Daily performance - Current system status 2. Analysis Panel (Left Side) - Market trend analysis - RSI status (overbought/oversold) - Volume conditions - Filter scores for each component - Final HIGH/LOW/WAIT decision Visual Signals - Green Triangle (↑) = HIGH prediction - Red Triangle (↓) = LOW prediction - Yellow Background = Entry opportunity - Blue Background = Waiting for result Configuration Options Basic Settings - Range Width: Target price movement (default $50 = ±$25) - Min Confidence: Minimum confidence to enter (default 75%) - Max Daily Trades: Risk management limit (default 5) Filters (Can be toggled on/off) - Trend Filter - Volume Confirmation - Support/Resistance Filter - Momentum Alignment Display Options - Show/hide signals, statistics, analysis - Minimal Mode for cleaner charts - EMA line visibility Important Risk Warnings Binary Options Trading Risks: 1. High Risk Product - Binary options are extremely risky and banned in many countries 2. Not Investment Advice - This tool is for educational/analytical purposes only 3. No Guaranteed Returns - Past performance doesn't predict future results 4. Capital at Risk - You can lose your entire investment in seconds Technical Limitations: - Requires stable internet connection - Performance varies with market conditions - High volatility can reduce accuracy - Not suitable for news events or low liquidity periods Best Practices 1. Paper Trade First - Test thoroughly on demo accounts 2. Risk Management - Never risk more than 1-2% per trade 3. Market Conditions - Works best in normal volatility conditions 4. Avoid Major Events - Don't trade during major news releases 5. Monitor Performance - Track your actual results vs displayed statistics Setup Instructions 1. Add to TradingView chart (BTC/USD preferred) 2. Use 30-second or 1-minute chart timeframe 3. Adjust settings based on your risk tolerance 4. Monitor F-Score (should be >65 for entries) 5. Wait for clear HIGH/LOW signals with high confidence Alert Configuration The indicator provides three alert types: - HIGH Signal alerts - LOW Signal alerts - General entry opportunity alerts Legal Disclaimer Binary options trading may not be legal in your jurisdiction. Many countries including the USA, Canada, and EU nations have restrictions or outright bans on binary options. Always check local regulations and consult with financial advisors before trading. Remember: This is a technical analysis tool, not a money-printing machine. Successful trading requires discipline, risk management, and continuous learning. The displayed statistics are historical and don't guarantee future performance.
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Hunk77의
BTC Power-Law Decay Channel Oscillator (0–100)🟠 BTC Power-Law Decay Channel Oscillator (0–100) This indicator calculates Bitcoin’s position inside its long-term power-law decay channel and normalizes it into an easy-to-read 0–100 oscillator. 🔎 Concept Bitcoin’s long-term price trajectory can be modeled by a log-log power-law channel. A baseline is fitted, then an upper band (excess/euphoria) and a lower band (capitulation/fear). The oscillator shows where the current price sits between those bands: 0 = near the lower band (historical bottoms) 100 = near the upper band (historical tops) 📊 How to Read Oscillator > 80 → euphoric excess, often cycle tops Oscillator < 20 → capitulation, often cycle bottoms Works best on weekly or bi-weekly timeframes. ⚙️ Adjustable Parameters Anchor date: starting point for the power-law fit (default: 2011). Smoothing days: moving average applied to log-price (default: 365 days). Upper / Lower multipliers: scale the bands to align with historical highs and lows. ✅ Best Use Combine with other cycle signals (dominance ratios, macro indicators, sentiment). Designed for long-term cycle analysis, not intraday trading.
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Darkoin_trading의
BTC(Sats Stacking) - CDC Action zone filterType: Indicator (Pine v6) • Category: Strategy Tools / DCA • Overlay: Yes Overview This indicator simulates fixed-amount Bitcoin DCA (dollar-cost averaging) and lets you apply a CDC Action Zone filter to only buy in specific market conditions. It plots EMA(12/26) lines with a shaded zone (green when fast > slow, red when slow > fast), shows buy markers on the chart when a DCA event actually executes, and displays a concise performance table. The simulation tracks real invested capital (sum of your buys), not hypothetical equity injections, and reports PnL vs invested capital. Key features DCA frequency: Everyday, Every week, or Every month CDC filter: Buy on all days, only when CDC is Green (trend-up above fast EMA), or only when Red (trend-down below fast EMA) Execution price: Choose to buy at bar close or next bar open Capital controls: Fixed DCA amount per event, optional max budget cap Currency support: Portfolio currency label plus optional FX conversion (by symbol or manual rate) Chart visuals: Buy markers on candles; EMA(12/26) lines with shaded “action zone” Metrics table: Invested capital, buys executed, BTC accumulated, average price per BTC (quote), equity (portfolio), PnL% vs invested, and CAGR How it works CDC state: Green = EMA(fast) > EMA(slow) and price ≥ EMA(fast) Red = EMA(fast) < EMA(slow) and price < EMA(fast) DCA trigger: Fires on new day/week/month boundaries (timeframe-agnostic). Buy execution: When a DCA event occurs and passes the CDC filter and budget check, the script spends the fixed amount and adds the corresponding BTC at the chosen execution price. Inputs (highlights) Simulation Symbol (blank = current chart), Buy at close/open, DCA amount, Max total invested DCA Schedule Everyday / Every week / Every month CDC Action Zone Filter mode (All / Green only / Red only), Price source, Fast/Slow EMA lengths (defaults 12/26) Currency / Conversion Portfolio currency label, Convert on/off, By symbol (e.g., OANDA:USDTHB) or Manual rate Backtest Range Optional start/end dates Style Show EMA lines and zone, colors and opacities, buy marker size and color Display Show qty/price labels on buys, show metrics table, number formatting Metrics Invested capital: Sum of all DCA spends in your portfolio currency Equity (portfolio): BTC holdings marked to market and converted back if FX is enabled PnL % vs invested: (Equity / Invested - 1) × 100 CAGR: Based on elapsed time from first in-range bar to the latest bar Average price per BTC (quote): Spend in quote currency divided by BTC accumulated Notes This is an indicator, not a broker-connected strategy. It simulates buys and displays results without placing orders. For more realistic fills, use Buy at next bar open. If your portfolio currency differs from the symbol’s quote currency, enable Convert and supply a conversion symbol or manual rate. EMA shading is purely visual; the filter logic uses the same EMA definitions. Attribution & License Inspired by the DCA idea and community simulations; CDC filtering implemented with standard EMA(12/26) logic. License: MPL-2.0 (see code header). Author: MiSuNoJo Disclaimer This tool is for research and education only and is not financial advice. Past performance does not guarantee future results. Use at your own risk.
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MiSuNoJo의
BTC_Hull Suite StrategyOverview BTC_Hull Suite Strategy is a trend-following system designed to keep drawdowns modest while staying exposed during genuine uptrends. It uses the Hull Moving Average (HMA) for fast, low-lag trend turns, a long-term SMA filter to avoid chop, and a percentage trailing stop to protect gains. 🔧 What the strategy includes - Hull Moving Average (HMA) with configurable length (default 55) - SMA filter (default 130) to trade only with higher-timeframe bias - Trailing stop in percent (default 5%) based on the running peak of close - Execution model: signals are evaluated on the previous bar and entries are placed at the next bar’s open (TradingView default) 📈 How it works: ✅ Entry (Long): Detects a bullish Hull turn by comparing the current HMA to its value 3 bars ago: h > h3 and h <= h3 → HMA just turned up on the prior bar The SMA filter must confirm: close > sma If both are true (and within the date window), a long is opened next bar at the open ❌ Exit: Hull turn down: h < h3 and h >= h3 , or Trailing stop: price closes below peak * (1 – trailingPct) Either condition closes the position at the current bar’s close Notes: pyramiding = 1 → allows one add-on (maximum two concurrent long positions) Position sizing defaults to 20% of equity per entry (adjustable in Properties) Who is this for? This strategy is tailored for Bitcoin traders (spot or perpetuals) who want a rules-based, low-lag trend system with built-in drawdown protection. It works best on Daily or 4H charts, but parameters can be adapted for other timeframes. ⚠️ Disclaimer This strategy is provided for educational and research purposes only. It is not financial advice. Markets are risky — always test on your own data, include realistic fees/slippage, and forward-test before using real capital.
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Trading_Alpha01의