Booz StrategyBooz Backtesting : Booz Backtesting is a method for analyzing the performance of your current trading strategy . Booz Backtesting aims to help you generate results and evaluate risk and return without risking real capital.
The Booz Backtesting is the Booz Super Swing Indicator equivalent but gives you the ability to backtest data on different charts.
This is an Indicator created for the purpose of identifying trends in Multiple Markets, it is based on Moving Average Crossover and extra features.
Swing Trading: This function allows you to navigate the entire trend until it is not strong enough, so you can compare it with fixed parameters such as Take Profit and Stop Loss.
Take Profit and Stop Loss function: With this function you will be able to choose the most optimal parameters and see in real time the results in order to choose the best combination of parameters.
Leverage : We have this function for the futures markets where you can check which is the most appropriate leverage for your operation.
Trend Filter: allows you to take multiple entries in the same direction of the market.
If the market crosses below the 200 moving average, it will take only short entries.
If the market crosses above the 200 moving average, it will take only long entries.
Timeframes
Charting from 1 Hour, 4 Hour, Daily, Weekly, Weekly
Markets :Booz Backtesting can be tested in Cryptocurrency, Stocks and Futures markets.
Background Color : at a glance, you can see what cycle the market is in.
Green background : Shows that the market is in a bullish cycle.
Red background: Shows that the market is in a bearish cycle.
Cari dalam skrip untuk "backtest"
Bozz Strategy
Booz Backtesting : Booz Backtesting is a method for analyzing the performance of your current trading strategy . Booz Backtesting aims to help you generate results and evaluate risk and return without risking real capital.
The Booz Backtesting is the Booz Super Swing Indicator equivalent but gives you the ability to backtest data on different charts.
This is an Indicator created for the purpose of identifying trends in Multiple Markets, it is based on Moving Average Crossover and extra features.
Swing Trading: This function allows you to navigate the entire trend until it is not strong enough, so you can compare it with fixed parameters such as Take Profit and Stop Loss.
Take Profit and Stop Loss function: With this function you will be able to choose the most optimal parameters and see in real time the results in order to choose the best combination of parameters.
Leverage : We have this function for the futures markets where you can check which is the most appropriate leverage for your operation.
Trend Filter: allows you to take multiple entries in the same direction of the market.
If the market crosses below the 200 moving average, it will take only short entries.
If the market crosses above the 200 moving average, it will take only long entries.
Timeframes
Charting from 1 Hour, 4 Hour, Daily, Weekly, Weekly
Markets :Booz Backtesting can be tested in Cryptocurrency, Stocks and Futures markets.
Background Color : at a glance, you can see what cycle the market is in.
Green background : Shows that the market is in a bullish cycle.
Red background: Shows that the market is in a bearish cycle.
Twitter
Website
Buy and Hold entry finder StrategyHello everyone!
I proudly present the backtest Strategy Script for my "Buy and Hold entry finder" Script.
It basically shows you the outcome, if you would use my indicator in the past.
The buy signals are limited to 1 order per month.
Order Size: Allows you to choose, how much money you want to invest per month. (Please consider, it will only invest an x amount per Order, but it will not stack the amount you did not invest in an previous month ) (Example in my indicator)
Pyramiding: Just regulates, how often you can open an position.
Commission: Here you can set how much it will cost to open an position at your broker.
I coded a feature that allows you to set a Start Date and an End Date for your backtest. In the end of the backtest the script closes all positions.
If you got any question, feel free to ask in the comments or send me a message.
Sincerely, RS Titan.
SimpleCrossOver_BotThis is a simple example of how you can compile your own strategy
This script contains the code for alerts and for backtesting.
In order to use the backtester, comment out the sections to be used for signals, and comment in the sections to be used on the back tester, and visa versa for using the script for alerts in order to automate your own bot.
Updated TurtlesThis script has been updated to prevent double orders (short/long) from occurring and modifying backtests results.
This is an update to the script that was written a few years ago to prevent double longs/shorts from occurring and skewin backtesting results. Check out the updated indicator here and let me know what you think.
I also added:
- date range inputs if you want to do some backtesting on a particular set of dates.
- the ability to toggle shorting
Line Break StrategyLine Break Strategy
Entry rule:
Long on a bullish line and short on a bearish line.
Backtest:
Profit factors are shown below for three-line break.
Daily time frame, FXCM broker.
EURUSD: 1.267, USDJPY: 1.039, GBPUSD: -0.816, AUDUSD: -0.959
S&P500: -0.783, Nikkei225: 1.099
CrudeOil: 1.03, Gold: 1.196
BTCUSD: -0.883
Reference:
Steve Nison, Beyond Candlesticks - New Japanese Charting Techniques Revealed
Note:
This strategy doesn't work properly on the linebreak chart.
A good example is shown below. The entry prices are not always correct.
If you have signal, but the next candle moves in the opposite direction, the entry price is drawn at the Open of the new candle instead of the Close of the previous candle.
The results of backtest are unreliable due to this reason.
Outsidebar vs Insidebar, Illusion Strategy (by ChartArt)WARNING: This strategy does not work! Please don't trade with this strategy
I'm sharing this strategy for the following three educational reasons:
1. You can easily find 100% strategies, but if they only seem to work 100% on one asset, they actually don't work at all. Therefore never backtest your strategy only on one asset, especially forward testing is useless, because it tends to repeat the old patterns. Your strategy has to work on as many different assets as possible.
2. The pyramiding of orders can have an impact on the strategy. In this case if you manually change the strategy settings by increasing it from 1 to 100 pyramiding orders changes the percent profitable on "UKOIL" monthly from 100% to 90% profitable. On other assets you can see very different results. Allowing much more pyramiding orders in this case results in opening orders where the background color highlights appear.
3. The Tradingview backtest beta version currently does not close the last open trade during the backtest. In this case going long on "UKOIL" near the top in 2011 as this strategy did would result in a big loss in 2015. But since the trade is still open and not canceled out by a new short order it still appears as if this strategy works 100% profitable. Which it doesn't.
Simple DCA Strategy----
### 📌 **Simple DCA Strategy with Backtest Date Filter**
This strategy implements a **Dollar-Cost Averaging (DCA)** approach for long positions, including:
* ✅ **Base Order Entry:** Starts a position with a fixed dollar amount when no position is open.
* 🔁 **Safety Orders:** Buys additional positions when the price drops by a defined percentage, increasing position size with each new entry using a multiplier.
* 🎯 **Take Profit Exit:** Closes all positions when the price reaches a profit target (in % above average entry).
* 🗓️ **Backtest Date Range:** Allows users to specify a custom start and optional end date to run the strategy only within that time window.
* 📊 **Plots:** Visualizes average entry, take profit level, and safety order trigger line.
#### ⚙️ Customizable Inputs:
* Base Order Size (\$)
* Price Deviation for Safety Orders (%)
* Maximum Safety Orders
* Order Size Multiplier
* Take Profit Target (%)
* Start and End Dates for Backtesting
This is a **long-only strategy** and is best used for backtesting performance of DCA-style accumulation under different market conditions.
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OBV ATR Strategy (OBV Breakout Channel) bas20230503ผมแก้ไขจาก OBV+SMA อันเดิม ของเดิม ดูที่เส้น SMA สองเส้นตัดกันมั่นห่วยแตกสำหรับที่ผมลองเทรดจริง และหลักการเบรค ได้แรงบันดาลใจ ATR จาก เทพคอย ที่ใช้กับราคา แต่นี้ใช้กับ OBV แทน
และผมใช้เจมินี้ เพื่อแก้ ให้ เป็น strategy เพื่อเช็คย้อนหลังได้ง่ายกว่าเดิม
หลักการง่ายคือถ้ามันขึ้น มันจะขึ้นเรื่อยๆ
เขียน แบบสุภาพ (น่าจะอ่านได้ง่ายกว่าผมเขียน)
สคริปต์นี้ได้รับการพัฒนาต่อยอดจากแนวคิด OBV+SMA Crossover แบบดั้งเดิม ซึ่งจากการทดสอบส่วนตัวพบว่าประสิทธิภาพยังไม่น่าพอใจ กลยุทธ์ใหม่นี้จึงเปลี่ยนมาใช้หลักการ "Breakout" ซึ่งได้รับแรงบันดาลใจมาจากการใช้ ATR สร้างกรอบของราคา แต่เราได้นำมาประยุกต์ใช้กับ On-Balance Volume (OBV) แทน นอกจากนี้ สคริปต์ได้ถูกแปลงเป็น Strategy เต็มรูปแบบ (โดยความช่วยเหลือจาก Gemini AI) เพื่อให้สามารถทดสอบย้อนหลัง (Backtest) และประเมินประสิทธิภาพได้อย่างแม่นยำ
หลักการของกลยุทธ์: กลยุทธ์นี้ทำงานบนแนวคิดโมเมนตัมที่ว่า "เมื่อแนวโน้มได้เกิดขึ้นแล้ว มีโอกาสที่มันจะดำเนินต่อไป" โดยจะมองหาการทะลุของพลังซื้อ-ขาย (OBV) ที่แข็งแกร่งเป็นพิเศษเป็นสัญญาณเข้าเทร
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สคริปต์นี้เป็นกลยุทธ์ (Strategy) ที่ใช้ On-Balance Volume (OBV) ซึ่งเป็นอินดิเคเตอร์ที่วัดแรงซื้อและแรงขายสะสม แทนที่จะใช้การตัดกันของเส้นค่าเฉลี่ย (SMA Crossover) ที่เป็นแบบพื้นฐาน กลยุทธ์นี้จะมองหาการ "ทะลุ" (Breakout) ของพลัง OBV ออกจากกรอบสูงสุด-ต่ำสุดของตัวเองในรอบที่ผ่านมา
สัญญาณกระทิง (Bull Signal): เกิดขึ้นเมื่อพลังการซื้อ (OBV) แข็งแกร่งจนสามารถทะลุจุดสูงสุดของตัวเองในอดีตได้ บ่งบอกถึงโอกาสที่แนวโน้มจะเปลี่ยนเป็นขาขึ้น
สัญญาณหมี (Bear Signal): เกิดขึ้นเมื่อพลังการขาย (OBV) รุนแรงจนสามารถกดดันให้ OBV ทะลุจุดต่ำสุดของตัวเองในอดีตได้ บ่งบอกถึงโอกาสที่แนวโน้มจะเปลี่ยนเป็นขาลง
ส่วนประกอบบนกราฟ (Indicator Components)
เส้น OBV
เส้นหลัก ที่เปลี่ยนเขียวเป็นแดง เป็นทั้งแนวรับและแนวต้าน และ จุด stop loss
เส้นนี้คือหัวใจของอินดิเคเตอร์ ที่แสดงถึงพลังสะสมของ Volume
เมื่อเส้นเป็นสีเขียว (แนวรับ): จะปรากฏขึ้นเมื่อกลยุทธ์เข้าสู่ "โหมดกระทิง" เส้นนี้คือระดับต่ำสุดของ OBV ในอดีต และทำหน้าที่เป็นแนวรับไดนามิก
เมื่อเส้นกลายเป็นสีแดงสีแดง (แนวต้าน): จะปรากฏขึ้นเมื่อกลยุทธ์เข้าสู่ "โหมดหมี" เส้นนี้คือระดับสูงสุดของ OBV ในอดีต และทำหน้าที่เป็นแนวต้านไดนามิก
สัญลักษณ์สัญญาณ (Signal Markers):
Bull 🔼 (สามเหลี่ยมขึ้นสีเขียว): คือสัญญาณ "เข้าซื้อ" (Long) จะปรากฏขึ้น ณ จุดที่ OBV ทะลุขึ้นไปเหนือกรอบด้านบนเป็นครั้งแรก
Bear 🔽 (สามเหลี่ยมลงสีแดง): คือสัญญาณ "เข้าขาย" (Short) จะปรากฏขึ้น ณ จุดที่ OBV ทะลุลงไปต่ำกว่ากรอบด้านล่างเป็นครั้งแรก
วิธีการใช้งาน (How to Use)
เพิ่มสคริปต์นี้ลงบนกราฟราคาที่คุณสนใจ
ไปที่แท็บ "Strategy Tester" ด้านล่างของ TradingView เพื่อดูผลการทดสอบย้อนหลัง (Backtest) ของกลยุทธ์บนสินทรัพย์และไทม์เฟรมต่างๆ
ใช้สัญลักษณ์ "Bull" และ "Bear" เป็นตัวช่วยในการตัดสินใจเข้าเทรด
ข้อควรจำ: ไม่มีกลยุทธ์ใดที่สมบูรณ์แบบ 100% ควรใช้สคริปต์นี้ร่วมกับการวิเคราะห์ปัจจัยอื่นๆ เช่น โครงสร้างราคา, แนวรับ-แนวต้านของราคา และการบริหารความเสี่ยง (Risk Management) ของตัวคุณเองเสมอ
การตั้งค่า (Inputs)
SMA Length 1 / SMA Length 2: ใช้สำหรับพล็อตเส้นค่าเฉลี่ยของ OBV เพื่อดูเป็นภาพอ้างอิง ไม่มีผลต่อตรรกะการเข้า-ออกของ Strategy อันใหม่ แต่มันเป็นของเก่า ถ้าชอบ ก็ใช้ได้ เมื่อ SMA สองเส้นตัดกัน หรือตัดกับเส้น OBV
High/Low Lookback Length: (ค่าพื้นฐาน30/แก้ตรงนี้ให้เหมาะสมกับ coin หรือหุ้น ตามความผันผวน ) คือระยะเวลาที่ใช้ในการคำนวณกรอบสูงสุด-ต่ำสุดของ OBV
ค่าน้อย: ทำให้กรอบแคบลง สัญญาณจะเกิดไวและบ่อยขึ้น แต่อาจมีสัญญาณหลอก (False Signal) เยอะขึ้น
ค่ามาก: ทำให้กรอบกว้างขึ้น สัญญาณจะเกิดช้าลงและน้อยลง แต่มีแนวโน้มที่จะเป็นสัญญาณที่แข็งแกร่งกว่า
แน่นอนครับ นี่คือคำแปลฉบับภาษาอังกฤษที่สรุปใจความสำคัญ กระชับ และสุภาพ เหมาะสำหรับนำไปใช้ในคำอธิบายสคริปต์ (Description) ของ TradingView ครับ
---Translate to English---
OBV Breakout Channel Strategy
This script is an evolution of a traditional OBV+SMA Crossover concept. Through personal testing, the original crossover method was found to have unsatisfactory performance. This new strategy, therefore, uses a "Breakout" principle. The inspiration comes from using ATR to create price channels, but this concept has been adapted and applied to On-Balance Volume (OBV) instead.
Furthermore, the script has been converted into a full Strategy (with assistance from Gemini AI) to enable precise backtesting and performance evaluation.
The strategy's core principle is momentum-based: "once a trend is established, it is likely to continue." It seeks to enter trades on exceptionally strong breakouts of buying or selling pressure as measured by OBV.
Core Concept
This is a Strategy that uses On-Balance Volume (OBV), an indicator that measures cumulative buying and selling pressure. Instead of relying on a basic Simple Moving Average (SMA) Crossover, this strategy identifies a "Breakout" of the OBV from its own highest-high and lowest-low channel over a recent period.
Bull Signal: Occurs when the buying pressure (OBV) is strong enough to break above its own recent highest high, indicating a potential shift to an upward trend.
Bear Signal: Occurs when the selling pressure (OBV) is intense enough to push the OBV below its own recent lowest low, indicating a potential shift to a downward trend.
On-Screen Components
1. OBV Line
This is the main indicator line, representing the cumulative volume. Its color changes to green when OBV is rising and red when it is falling.
2. Dynamic Support & Resistance Line
This is the thick Green or Red line that appears based on the strategy's current "mode." This line serves as a dynamic support/resistance level and can be used as a reference for stop-loss placement.
Green Line (Support): Appears when the strategy enters "Bull Mode." This line represents the lowest low of the OBV in the recent past and acts as dynamic support.
Red Line (Resistance): Appears when the strategy enters "Bear Mode." This line represents the highest high of the OBV in the recent past and acts as dynamic resistance.
3. Signal Markers
Bull 🔼 (Green Up Triangle): This is the "Long Entry" signal. It appears at the moment the OBV first breaks out above its high-low channel.
Bear 🔽 (Red Down Triangle): This is the "Short Entry" signal. It appears at the moment the OBV first breaks down below its high-low channel.
How to Use
Add this script to the price chart of your choice.
Navigate to the "Strategy Tester" panel at the bottom of TradingView to view the backtesting results for the strategy on different assets and timeframes.
Use the "Bull" and "Bear" signals as aids in your trading decisions.
Disclaimer: No strategy is 100% perfect. This script should always be used in conjunction with other forms of analysis, such as price structure, key price-based support/resistance levels, and your own personal risk management rules.
Inputs
SMA Length 1 / SMA Length 2: These are used to plot moving averages on the OBV for visual reference. They are part of the legacy logic and do not affect the new breakout strategy. However, they are kept for traders who may wish to observe their crossovers for additional confirmation.
High/Low Lookback Length: (Most Important Setting) This determines the period used to calculate the highest-high and lowest-low OBV channel. (Default is 30; adjust this to suit the asset's volatility).
A smaller value: Creates a narrower channel, leading to more frequent and faster signals, but potentially more false signals.
A larger value: Creates a wider channel, leading to fewer and slower signals, which are likely to be more significant.
EMD Trend [InvestorUnknown]EMD Trend is a dynamic trend-following indicator that utilizes Exponential Moving Deviation (EMD) to build adaptive channels around a selected moving average. Designed for traders who value responsive trend signals with built-in volatility sensitivity, this tool highlights directional bias, market regime shifts, and potential breakout opportunities.
How It Works
Instead of using standard deviation, EMD Trend employs the exponential moving average of the absolute deviation from a moving average—producing smoother, faster-reacting upper and lower bounds:
Bullish (Risk-ON Long): Price crosses above the upper EMD band
Bearish (Risk-ON Short): Price crosses below the lower EMD band
Neutral: Price stays within the channel, indicating potential mean reversion or low momentum
Trend direction is defined by price interaction with these bands, and visual cues (color-coded bars and fills) help quickly identify market conditions.
Features
7 Moving Average Types: SMA, EMA, HMA, DEMA, TEMA, RMA, FRAMA
Custom Price Source: Choose close, hl2, ohlc4, or others
EMD Multiplier: Controls the width of the deviation envelope
Bar Coloring: Candles change color based on current trend
Intra-bar Signal Option: Enables faster updates (with optional repainting)
Speculative Zones: Fills highlight aggressive momentum moves beyond EMD bounds
Backtest Mode
Switch to Backtest Mode for performance evaluation over historical data:
Equity Curve Plot: Compare EMD Trend strategy vs. Buy & Hold
Trade Metrics Table: View number of trades, win/loss stats, profits
Performance Metrics Table: Includes CAGR, Sharpe, max drawdown, and more
Custom Start Date: Select from which date the backtest should begin
Trade Sizing: Configure capital and trade percentage per entry
Signal Filters: Choose from Long Only, Short Only, or Both
Alerts
Built-in alerts let you automate entries, exits, and trend transitions:
LONG (EMD Trend) - Trend flips to Long
SHORT (EMD Trend) - Trend flips to Short
RISK-ON LONG - Price crosses above upper EMD band
RISK-OFF LONG - Price crosses back below upper EMD band
RISK-ON SHORT - Price crosses below lower EMD band
RISK-OFF SHORT - Price crosses back above lower EMD band
Use Cases
Trend Confirmation with volatility-sensitive boundaries
Momentum Entry Filtering via breakout zones
Mean Reversion Avoidance in sideways markets
Backtesting & Strategy Building with real-time metrics
Disclaimer
This indicator is intended for informational and educational purposes only. It does not constitute investment advice. Historical performance does not guarantee future results. Always backtest and use in simulation before live trading.
Best SMA FinderThis script, Best SMA Finder, is a tool designed to identify the most robust simple moving average (SMA) length for a given chart, based on historical backtest performance. It evaluates hundreds of SMA values (from 10 to 1000) and selects the one that provides the best balance between profitability, consistency, and trade frequency.
What it does:
The script performs individual backtests for each SMA length using either "Long Only" or "Buy & Sell" logic, as selected by the user. For each tested SMA, it computes:
- Total number of trades
- Profit Factor (total profits / total losses)
- Win Rate
- A composite Robustness Score, which integrates Profit Factor, number of trades (log-scaled), and win rate.
Only SMA configurations that meet the user-defined minimum trade count are considered valid. Among all valid candidates, the script selects the SMA length with the highest robustness score and plots it on the chart.
How to use it:
- Choose the strategy type: "Long Only" or "Buy & Sell"
- Set the minimum trade count to filter out statistically irrelevant results
- Enable or disable the summary stats table (default: enabled)
The selected optimal SMA is plotted on the chart in blue. The optional table in the top-right corner shows the corresponding SMA length, trade count, Profit Factor, Win Rate, and Robustness Score for transparency.
Key Features:
- Exhaustive SMA optimization across 991 values
- Customizable trade direction and minimum trade filters
- In-chart visualization of results via table and plotted optimal SMA
- Uses a custom robustness formula to rank SMA lengths
Use cases:
Ideal for traders who want to backtest and auto-select a historically effective SMA without manual trial-and-error. Useful for swing and trend-following strategies across different timeframes.
📌 Limitations:
- Not a full trading strategy with position sizing or stop-loss logic
- Only one entry per direction at a time is allowed
- Designed for exploration and optimization, not as a ready-to-trade system
This script is open-source and built entirely from original code and logic. It does not replicate any closed-source script or reuse significant external open-source components.
Williams R Zone Scalper v1.0[BullByte]Originality & Usefulness
Unlike standard Williams R cross-over scripts, this strategy layers five dynamic filters—moving-average trend, Supertrend, Choppiness Index, Bollinger Band Width, and volume validation —and presents a real-time dashboard with equity, PnL, filter status, and key indicator values. No other public Pine script combines these elements with toggleable filters and a custom dashboard. In backtests (BTC/USD (Binance), 5 min, 24 Mar 2025 → 28 Apr 2025), adding these filters turned a –2.09 % standalone Williams R into a +5.05 % net winner while cutting maximum drawdown in half.
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What This Script Does
- Monitors Williams R (length 14) for overbought/oversold reversals.
- Applies up to five dynamic filters to confirm trend strength and volatility direction:
- Moving average (SMA/EMA/WMA/HMA)
- Supertrend line
- Choppiness Index (CI)
- Bollinger Band Width (BBW)
- Volume vs. its 50-period MA
- Plots blue arrows for Long entries (R crosses above –80 + all filters green) and red arrows for Short entries (R crosses below –20 + all filters green).
- Optionally sets dynamic ATR-based stop-loss (1.5×ATR) and take-profit (2×ATR).
- Shows a dashboard box with current position, equity, PnL, filter status, and real-time Williams R / MA/volume values.
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Backtest Summary (BTC/USD(Binance), 5 min, 24 Mar 2025 → 28 Apr 2025)
• Total P&L : +50.70 USD (+5.05 %)
• Max Drawdown : 31.93 USD (3.11 %)
• Total Trades : 198
• Win Rate : 55.05 % (109/89)
• Profit Factor : 1.288
• Commission : 0.01 % per trade
• Slippage : 0 ticks
Even in choppy March–April, this multi-filter approach nets +5 % with a robust risk profile, compared to –2.09 % and higher drawdown for Williams R alone.
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Williams R Alone vs. Multi-Filter Version
• Total P&L :
– Williams R alone → –20.83 USD (–2.09 %)
– Multi-Filter → +50.70 USD (+5.05 %)
• Max Drawdown :
– Williams R alone → 62.13 USD (6.00 %)
– Multi-Filter → 31.93 USD (3.11 %)
• Total Trades : 543 vs. 198
• Win Rate : 60.22 % vs. 55.05 %
• Profit Factor : 0.943 vs. 1.288
---
Inputs & What They Control
- wrLen (14): Williams R look-back
- maType (EMA): Trend filter type (SMA, EMA, WMA, HMA)
- maLen (20): Moving-average period
- useChop (true): Toggle Choppiness Index filter
- ciLen (12): CI look-back length
- chopThr (38.2): CI threshold (below = trending)
- useVol (true): Toggle volume-above-average filter
- volMaLen (50): Volume MA period
- useBBW (false): Toggle Bollinger Band Width filter
- bbwMaLen (50): BBW MA period
- useST (false): Toggle Supertrend filter
- stAtrLen (10): Supertrend ATR length
- stFactor (3.0): Supertrend multiplier
- useSL (false): Toggle ATR-based SL/TP
- atrLen (14): ATR period for SL/TP
- slMult (1.5): SL = slMult × ATR
- tpMult (2.0): TP = tpMult × ATR
---
How to Read the Chart
- Blue arrow (Long): Williams R crosses above –80 + all enabled filters green
- Red arrow (Short) : Williams R crosses below –20 + all filters green
- Dashboard box:
- Top : position and equity
- Next : cumulative PnL in USD & %
- Middle : green/white dots for each filter (green=passing, white=disabled)
- Bottom : Williams R, MA, and volume current values
---
Usage Tips
- Add the script : Indicators → My Scripts → Williams R Zone Scalper v1.0 → Add to BTC/USD chart on 5 min.
- Defaults : Optimized for BTC/USD.
- Forex majors : Raise `chopThr` to ~42.
- Stocks/high-beta : Enable `useBBW`.
- Enable SL/TP : Toggle `useSL`; stop-loss = 1.5×ATR, take-profit = 2×ATR apply automatically.
---
Common Questions
- * Why not trade every Williams R reversal?*
Raw Williams R whipsaws in sideways markets. Choppiness and volume filters reduce false entries.
- *Can I use on 1 min or 15 min?*
Yes—adjust ATR length or thresholds accordingly. Defaults target 5 min scalping.
- *What if all filters are on?*
Fewer arrows, higher-quality signals. Expect ~10 % boost in average win size.
---
Disclaimer & License
Trading carries risk of loss. Use this script “as is” under the Mozilla Public License 2.0 (mozilla.org). Always backtest, paper-trade, and adjust risk settings to your own profile.
---
Credits & References
- Pine Script v6, using TradingView’s built-in `ta.supertrend()`.
- TradingView House Rules: www.tradingview.com
Goodluck!
BullByte
Daily Bollinger Band StrategyOverview of the Daily Bollinger Band Strategy
1. Strategy Overview and Features
This strategy is a tool for backtesting a trading method that uses Bollinger Bands. It is *not* a tool for automated trading.
1-1. Main Display Items
The main chart displays the Bollinger Bands and the 200-day moving average.
It also shows the entry and exit points along with the position size (in units of 100 shares).
1-2. Summary of Trading Rules
For long (buy) strategies, the trade enters when the price crosses above the +1σ line of the Bollinger Bands, aiming to ride an upward trend. The position is exited when the price crosses below the middle band.
For short (sell) strategies, the trade enters when the price crosses below the -1σ line of the Bollinger Bands, aiming to ride a downward trend. The position is exited when the price crosses above the middle band.
1-3. Strategic Enhancements
The strategy uses the slope of the 200-day moving average to determine the trend direction and enter trades accordingly. This improves the win rate and payoff ratio.
Additionally, to reduce the probability of ruin, the risk per trade is limited to 1.0% of capital, and position sizing is adjusted using ATR (a volatility indicator).
2. Trading Rules
2-1. Chart Type
Only daily charts are used.
2-2. Indicators Used
(1) Bollinger Bands** (used for entry and exit signals)
- Period: Fixed at 80 days
- Upper and lower bands: Fixed at ±1σ
(2) Moving Average** (used to determine trend direction)
- Period: Fixed at 200 days
- Trend direction is judged based on whether the difference from the previous day is positive (upward) or negative (downward)
2-3. Buy Rules
Setup:
- Price crosses above the +1σ line from below
- Both the middle band and 200-day moving average are upward sloping
Entry:
- Buy at the next day’s market open using a market order
Exit:
- If the price crosses below the middle band, sell at the next day’s open using a market order
2-4. Sell Rules
Setup:
- Price crosses below the -1σ line from above
- Both the middle band and 200-day moving average are downward sloping
Entry:
- Sell at the next day’s market open using a market order
Exit:
- If the price crosses above the middle band, buy back at the next day’s open using a market order
2-5. Risk Management Rules
- Risk per trade: 1.0% of total capital (acceptable loss = capital × 1.0%)
- Position size: Acceptable loss ÷ 2ATR (rounded down to the nearest unit of 100 shares)
2-6. Other Notes
- No brokerage fees
- No pyramiding
- No partial exits
- No reverse positions (no “stop-and-reverse” trades)
3. Strategy Parameters
The following settings can be specified:
3-1. Period Settings
- Start date: Set the start date for the backtest period
- Stop date: Set the end date for the backtest period
3-2. Display of Trend and Signals
- Show trend: When checked, the background color of the bars is light red for an uptrend and light blue for a downtrend
- Show signal: When checked, entry and exit signals are displayed (note: signals are executed at the next day’s open, so there is a one-day lag in the display)
3-3. Capital Management Settings
- Funds: Capital available for trading (in JPY)
- Risk rate: Specify what percentage of the capital to risk per trade
Settings in the “Properties” tab are not used in this strategy.
4. Backtest Results (Example)
Here are the backtest results conducted by the author:
- Target Stocks: All components of the Nikkei 225
- Test Period: January 4, 2000 – December 30, 2024
- Data Points: 12,886
- Win Rate: 33.45%
- Net Profit: ¥82,132,380
- Payoff Ratio: 2.450
- Expected Value: ¥6,373.8
- Risk Rate: 1.0%
- Probability of Ruin: 0.00%
---
デイリー・ボリンジャーバンド・ストラテジーの概要
1. ストラテジーの概要と特徴
このストラテジーは、ボリンジャーバンドを使ったトレード手法のバックテストを行うツールです。自動売買を行うツールではありません。
1-1. 主な表示項目
メインチャートにボリンジャーバンドと 200日移動平均線を表示します。
また、エントリーと手仕舞いのタイミングと数量（100株単位）も表示されます。
1-2. トレードルールの概要
買い戦略の場合、ボリンジャーバンドの +1σ 超えでエントリーして上昇トレンドに乗り、ミドルバンドを割ったら決済します。
売り戦略の場合、ボリンジャーバンドの -1σ 割りでエントリーして下降トレンドに乗り、ミドルバンドを上抜けたら決済します。
1-3. ストラテジーの工夫点
200日移動平均線の傾きを見てトレンド方向にエントリーをしています。こうして勝率とペイオフレシオの成績を向上しています。
また、破産確率を抑えるために、リスク資金比率を 1.0% にして、ATR（ボラティリティ指標） を使って注文数を調整しています。
2. 売買ルール
2-1. 使用するチャート
日足チャートに限定します
2-2. 使用する指標
(1) ボリンジャーバンド（仕掛けと手仕舞いのシグナルに使用）
期間は80日に固定
上下バンドは ±1σ に固定
(2) 移動平均線（トレンドの方向を見るために使用）
期間は200日に固定
移動平均の値の前日との差がプラスのとき上向き、マイナスのとき下向きと判断
2-3. 買いのルール
セットアップ：ボリンジャーバンドの +1σ を価格が下から上に交差 かつ ミドルバンドと 200日移動平均線が上向き
仕掛け：翌日の寄り付きに成行で買う
手仕舞い：ボリンジャーバンドのミドルバンドを価格が上から下に交差したら、翌日の寄り付きに成行で売る
2-4. 売りのルール
セットアップ：ボリンジャーバンドの -1σ を価格が上から下に交差 かつ ミドルバンドと 200日移動平均線が下向き
仕掛け：翌日の寄り付きに成行で売る
手仕舞い：ボリンジャーバンドのミドルバンドを価格が下から上に交差したら、翌日の寄り付きに成行で買い戻す
2-5. 資金管理のルール
リスク資金比率：資産の 1.0%（許容損失 = 資産 × 1.0%）
注文数：許容損失 ÷ 2ATR（単元株数未満は切り捨て）
2-6. その他
仲介手数料：なし
ピラミッディング：なし
分割決済：なし
ドテン：しない
3. ストラテジーのパラメーター
次の項目が指定できます。
3-1. 期間の設定
Staer date : バックテストの検証期間の開始日を指定します
Stop date : バックテストの検証期間の終了日を指定します
3-2. トレンドとシグナルの表示
Show trend : チェックを入れると、バーの背景色が、トレンドが上昇のときは薄い赤で、下落のときは薄い青で表示されます
Show signal : チェックを入れると、エントリーと手仕舞いのシグナルを表示します（シグナルの出た翌日の寄り付きに売買をするので表示に1日のずれがあります）
3-3. 資金管理用の設定
Funds : トレード用の資金(円)
Risk rate : 許容損失を資金の何%にするかで指定します
「プロパティタブ」で設定する値は、このストラテジーでは有効ではありません。
4. バックテストの結果（例）
作者がバックテストを実施した結果をお知らせします。
対象銘柄：日経225構成銘柄すべて
対象期間：2000年1月4日～2024年12月30日
データ件数：12,886
勝率：33.45%
純利益：82,132,380
ペイオフレシオ：2.450
期待値：6,373.8
リスク資金比率：1.0%
破産確率：0.00%
Bull Flag (9:30-12:00 Only) [One-Liner Fix]🚀 Bull Flag Breakout Strategy | Intraday Momentum (9:30-12:00) 🔥📈
💡 Designed for Intraday Traders who love momentum breakouts and want to automate Bull Flag setups with volume confirmation! This strategy detects strong bullish moves, measures pullbacks, and triggers trades when the first candle makes a new high—ensuring maximum momentum.
⸻
🏆 Why This Strategy?
✅ Bull Flag Pattern Automation – No need to manually spot pullbacks! 🎯
✅ Smart Volume Confirmation – Only enter trades when breakout volume is strong! 📊
✅ Morning Session Focused (9:30 - 12:00 EST) – Trade when momentum is at its peak! ⏰
✅ Customizable ATR & Risk Settings – Adjust pullback %, stop-loss, and take-profit! 🛠️
✅ Backtest-Friendly – See how the strategy performs over time! 🔍
⸻
🎯 How It Works
📌 Step 1: Detects a Bullish Impulse Bar
🔹 Large green candle 🚀
🔹 Candle range > ATR multiplier
🔹 Volume > Average volume threshold
📌 Step 2: Confirms a Valid Pullback
🔸 Pullback must stay within % range of the impulse move 📉
🔸 If the pullback is too deep or takes too long, the setup is ignored ⛔
📌 Step 3: First Candle to Make a New High 📈
🔹 When a candle breaks the previous high and volume confirms, go long! 💰
🔹 Stop-Loss set at pullback low
🔹 Take-Profit at Risk:Reward (R:R) Target 🎯
⸻
🔥 Best For
💎 Scalpers & Day Traders – Capture short-term breakout momentum! ⚡
📊 Backtesters – Optimize ATR, volume, and pullback rules for best performance! 🧪
⏳ Morning Momentum Traders – Focus on 9:30-12:00 AM EST for higher probability setups!
⸻
🚨 Important Notes
🔹 This strategy is not financial advice! 📜
🔹 Always backtest & paper trade before using real money! 📉📈
🔹 Volatility varies – Customize settings based on your trading style! 🔧
🚀 Like this script? Give it a try & let us know how it works for you! 🔥👊
⸻
Ultimate Stochastics Strategy by NHBprod Use to Day Trade BTCHey All!
Here's a new script I worked on that's super simple but at the same time useful. Check out the backtest results. The backtest results include slippage and fees/commission, and is still quite profitable. Obviously the profitability magnitude depends on how much capital you begin with, and how much the user utilizes per order, but in any event it seems to be profitable according to backtests.
This is different because it allows you full functionality over the stochastics calculations which is designed for random datasets. This script allows you to:
Designate ANY period of time to analyze and study
Choose between Long trading, short trading, and Long & Short trading
It allows you to enter trades based on the stochastics calculations
It allows you to EXIT trades using the stochastics calculations or take profit, or stop loss, Or any combination of those, which is nice because then the user can see how one variable effects the overall performance.
As for the actual stochastics formula, you get control, and get to SEE the plot lines for slow K, slow D, and fast K, which is usually not considered.
You also get the chance to modify the smoothing method, which has not been done with regular stochastics indicators. You get to choose the standard simple moving average (SMA) method, but I also allow you to choose other MA's such as the HMA and WMA.
Lastly, the user gets the option of using a custom trade extender, which essentially allows a buy or sell signal to exist for X amount of candles after the initial signal. For example, you can use "max bars since signal" to 1, and this will allow the indicator to produce an extra sequential buy signal when a buy signal is generated. This can be useful because it is possible that you use a small take profit (TP) and quickly exit a profitable trade. With the max bars since signal variable, you're able to reenter on the next candle and allow for another opportunity.
Let me know if you have any questions! Please take a look at the performance report and let me know your thoughts! :)
Hyperbolic Tangent SuperTrend [InvestorUnknown]The Hyperbolic Tangent SuperTrend (HTST) is designed for technical analysis, particularly in markets with assets that have lower prices or price ratios. This indicator leverages the Hyperbolic Tangent Moving Average (HTMA), a custom moving average calculated using the hyperbolic tangent function, to smooth price data and reduce the impact of short-term volatility.
Hyperbolic Tangent Moving Average (HTMA):
The indicator's core uses a hyperbolic tangent function to calculate a smoothed average of the price. The HTMA provides enhanced trend-following capabilities by dampening the impact of sharp price swings and maintaining a focus on long-term market movements.
The hyperbolic tangent function (tanh) is commonly used in mathematical fields like calculus, machine learning and signal processing due to its properties of “squashing” inputs into a range between -1 and 1. The function provides a non-linear transformation that can reduce the impact of extreme values while retaining a certain level of smoothness.
tanh(x) =>
e_x = math.exp(x)
e_neg_x = math.exp(-x)
(e_x - e_neg_x) / (e_x + e_neg_x)
The HTMA is calculated by taking the difference between the price and its simple moving average (SMA), applying a multiplier to control sensitivity, and then transforming it using the hyperbolic tangent function.
htma(src, len, mul) =>
tanh_src = tanh((src - ta.sma(src, len)) * mul) * ta.stdev(src, len) + ta.sma(src, len)
htma = ta.sma(tanh_src, len)
Important Note: The Hyperbolic Tangent function becomes less accurate with very high prices. For assets priced above 100,000, the results may deteriorate, and for prices exceeding 1 million, the function may stop functioning properly. Therefore, this indicator is better suited for assets with lower prices or lower price ratios.
SuperTrend Calculation:
In addition to the HTMA, the indicator includes an Average True Range (ATR)-based SuperTrend calculation, which helps identify uptrends and downtrends in the market. The SuperTrend is adjusted dynamically using the HTMA to avoid false signals in fast-moving markets.
The ATR period and multiplier are customizable, allowing users to fine-tune the sensitivity of the trend signals.
pine_supertrend(src, calc_price, atrPeriod, factor) =>
atr = ta.atr(atrPeriod)
upperBand = src + factor * atr
lowerBand = src - factor * atr
prevLowerBand = nz(lowerBand )
prevUpperBand = nz(upperBand )
lowerBand := lowerBand > prevLowerBand or calc_price < prevLowerBand ? lowerBand : prevLowerBand
upperBand := upperBand < prevUpperBand or calc_price > prevUpperBand ? upperBand : prevUpperBand
int _direction = na
float superTrend = na
prevSuperTrend = superTrend
if na(atr )
_direction := 1
else if prevSuperTrend == prevUpperBand
_direction := calc_price > upperBand ? -1 : 1
else
_direction := calc_price < lowerBand ? 1 : -1
superTrend := _direction == -1 ? lowerBand : upperBand
Inbuilt Backtest Mode:
The HTST includes an inbuilt backtest mode that enables users to test the indicator's performance against historical data, similar to TradingView strategies.
The backtest mode allows you to compare the performance of different indicator settings with a simple buy and hold strategy to assess its effectiveness in different market conditions.
Hint Table for Display Modes:
The indicator includes a Hint Table that recommends the best pane to use for different display modes. For example, it suggests using the "Overlay" mode in the same pane as the price action, while the "Backtest Mode" is better suited for a separate pane. This ensures a more organized and clear visual experience.
The Hint Table appears as a small table at the bottom of the chart with easy-to-follow recommendations, ensuring the best setup for both visual clarity and indicator functionality.
With these features, the Hyperbolic Tangent SuperTrend Indicator offers traders a versatile and customizable tool for analyzing price trends while providing additional functionalities like backtesting and display mode hints for optimal usability.
Trend Deviation strategy - BTC [IkkeOmar]Intro:
This is an example if anyone needs a push to get started with making strategies in pine script. This is an example on BTC, obviously it isn't a good strategy, and I wouldn't share my own good strategies because of alpha decay.
This strategy integrates several technical indicators to determine market trends and potential trade setups. These indicators include:
Directional Movement Index (DMI)
Bollinger Bands (BB)
Schaff Trend Cycle (STC)
Moving Average Convergence Divergence (MACD)
Momentum Indicator
Aroon Indicator
Supertrend Indicator
Relative Strength Index (RSI)
Exponential Moving Average (EMA)
Volume Weighted Average Price (VWAP)
It's crucial for you guys to understand the strengths and weaknesses of each indicator and identify synergies between them to improve the strategy's effectiveness.
Indicator Settings:
DMI (Directional Movement Index):
Length: This parameter determines the number of bars used in calculating the DMI. A higher length may provide smoother results but might lag behind the actual price action.
Bollinger Bands:
Length: This parameter specifies the number of bars used to calculate the moving average for the Bollinger Bands. A longer length results in a smoother average but might lag behind the price action.
Multiplier: The multiplier determines the width of the Bollinger Bands. It scales the standard deviation of the price data. A higher multiplier leads to wider bands, indicating increased volatility, while a lower multiplier results in narrower bands, suggesting decreased volatility.
Schaff Trend Cycle (STC):
Length: This parameter defines the length of the STC calculation. A longer length may result in smoother but slower-moving signals.
Fast Length: Specifies the length of the fast moving average component in the STC calculation.
Slow Length: Specifies the length of the slow moving average component in the STC calculation.
MACD (Moving Average Convergence Divergence):
Fast Length: Determines the number of bars used to calculate the fast EMA (Exponential Moving Average) in the MACD.
Slow Length: Specifies the number of bars used to calculate the slow EMA in the MACD.
Signal Length: Defines the number of bars used to calculate the signal line, which is typically an EMA of the MACD line.
Momentum Indicator:
Length: This parameter sets the number of bars over which momentum is calculated. A longer length may provide smoother momentum readings but might lag behind significant price changes.
Aroon Indicator:
Length: Specifies the number of bars over which the Aroon indicator calculates its values. A longer length may result in smoother Aroon readings but might lag behind significant market movements.
Supertrend Indicator:
Trendline Length: Determines the length of the period used in the Supertrend calculation. A longer length results in a smoother trendline but might lag behind recent price changes.
Trendline Factor: Specifies the multiplier used in calculating the trendline. It affects the sensitivity of the indicator to price changes.
RSI (Relative Strength Index):
Length: This parameter sets the number of bars over which RSI calculates its values. A longer length may result in smoother RSI readings but might lag behind significant price changes.
EMA (Exponential Moving Average):
Fast EMA: Specifies the number of bars used to calculate the fast EMA. A shorter period results in a more responsive EMA to recent price changes.
Slow EMA: Determines the number of bars used to calculate the slow EMA. A longer period results in a smoother EMA but might lag behind recent price changes.
VWAP (Volume Weighted Average Price):
Default settings are typically used for VWAP calculations, which consider the volume traded at each price level over a specific period. This indicator provides insights into the average price weighted by trading volume.
backtest range and rules:
You can specify the start date for backtesting purposes.
You can can select the desired trade direction: Long, Short, or Both.
Entry and Exit Conditions:
LONG:
DMI Cross Up: The Directional Movement Index (DMI) indicates a bullish trend when the positive directional movement (+DI) crosses above the negative directional movement (-DI).
Bollinger Bands (BB): The price is below the upper Bollinger Band, indicating a potential reversal from the upper band.
Momentum Indicator: Momentum is positive, suggesting increasing buying pressure.
MACD (Moving Average Convergence Divergence): The MACD line is above the signal line, indicating bullish momentum.
Supertrend Indicator: The Supertrend indicator signals an uptrend.
Schaff Trend Cycle (STC): The STC indicates a bullish trend.
Aroon Indicator: The Aroon indicator signals a bullish trend or crossover.
When all these conditions are met simultaneously, the strategy considers it a favorable opportunity to enter a long trade.
SHORT:
DMI Cross Down: The Directional Movement Index (DMI) indicates a bearish trend when the negative directional movement (-DI) crosses above the positive directional movement (+DI).
Bollinger Bands (BB): The price is above the lower Bollinger Band, suggesting a potential reversal from the lower band.
Momentum Indicator: Momentum is negative, indicating increasing selling pressure.
MACD (Moving Average Convergence Divergence): The MACD line is below the signal line, signaling bearish momentum.
Supertrend Indicator: The Supertrend indicator signals a downtrend.
Schaff Trend Cycle (STC): The STC indicates a bearish trend.
Aroon Indicator: The Aroon indicator signals a bearish trend or crossover.
When all these conditions align, the strategy considers it an opportune moment to enter a short trade.
Disclaimer:
THIS ISN'T AN OPTIMAL STRATEGY AT ALL! It was just an old project from when I started learning pine script!
The backtest doesn't promise the same results in the future, always do both in-sample and out-of-sample testing when backtesting a strategy. And make sure you forward test it as well before implementing it!
Furthermore this strategy uses both trend and mean-reversion systems, that is usually a no-go if you want to build robust trend systems .
Don't hesitate to comment if you have any questions or if you have some good notes for a beginner.
R:R Trading System FrameworkFirst off, huge thanks to @fikira! He was able to adapt what I built to work much more efficiently, allowing for more strategies to be used simultaneously. Simply put, I could not have gotten to this point without you. Thanks for what you do for the TV community. Second, I am fairly new to pinescript writing, so I welcome criticism, thoughtful input and improvement suggestions. I would love to grow this concept into something even better, if possible. So please let me know if you have any ideas for improvement. However I do juggle a lot of different things outside of TV, so implementations may be delayed.
I have decided, at this time, not to add alerts. First, because I feel most people looking to adapt this framework can add their own pretty easily. Also, given how customized the framework is currently, while also attempting to account for all the possible ways in which people may want alerts to function after they customize it, it seems best to leave them out as it doesn't exactly fit the idea of a framework.
For best viewing, I recommend hovering over the script's name > ... > Visual order > Bring to front. Also I found hollow candles with mono-toned colors (like pictured) are more visually appealing for me personally. I HIGHLY RECOMMEND USING WITH BAR REPLAY TO BETTER UNDERSTAND THE FRAMEWORK'S FUNCTIONALITY.
▶️ WHAT THIS FRAMEWORK IS
- A huge collection of concepts and capabilities for those trying to better understand, learn, or teach pinescript.
- A system designed to showcase Risk:Reward concepts more holistically by providing all of the most popular components of retail trading to include backtesting, trade visual plotting, position tracking, market condition shifts, and useful info while positioned to help highlight changes in your risk:reward based decision-making processes.
- A system that can showcase individual strategies regardless of trade direction, allowing you to develop hedging strategies without having multiple indicators that do not correlate with each other.
- Designed around the idea that you trade less numbers of assets but manage your positions and risk based on multiple concurrently running strategies to manage your risk exposure and reward potential.
- An attempt to combine all the things you need to execute with an active trading management style.
- A framework that uses backtested results (in this case the number of averaged bars it takes to hit key levels) in real-time to inform your risk:reward decision-making while in-trade (in this case in your Trade Tracking Table using dynamic color to show how you might be early, on-time, or late compared to the average amount of backtested time it normally takes to hit that specific key level).
▶️ WHAT THIS FRAMEWORK IS NOT
- A complete trading product. DO NOT USE as-is. It is a FRAMEWORK for you to generate ideas of your own and fairly easily implement your own triggering conditions in the appropriate sections of the script.
▶️ USE CASES
- If you decide you like the Stop, Target, Trailing Stop, and Risk:Reward components as-is, then just understanding how to plug in your Entry and Bullish / Bearish conditions (Triangles) and adjust the input texts to match your custom naming will be all you need to make it your own!
- If you want to adapt certain components, then this system gives you a great starting point to adapt your different concepts and ideas from.
▶️ SYSTEM COMPONENTS
- Each of the system's components are described via tooltips both in the input menu and in the tables' cells.
- Each label on the chart displays the corresponding price at those triggered conditions on hover with tooltips.
- The Trailing Stop only becomes active once it is above the Entry Price for that trade, and brightens to show it is active. The STOP line (right of price) moves once it takes over for the Entry Stop representing the level of the Trailing Stop at that time for that trade.
- The Lines / Labels to the right of price will brighten once price is above for Longs or below for Shorts. The Trade Tracking Table cells will add ☑️ once price is above for Longs or below for Shorts.
- The brighter boxes on the chart show the trades that occurred based on your criteria and are color coded for all components of each trade type to ensure your references are consistent. (Defaults are TV built-in strategies)
- The lighter boxes on the chart show the highest and lowest price levels reached during those trades, to highlight areas where improvements can be made or additional considerations can be accounted for by either adjusting Entry triggers or Bullish / Bearish triggers.
- Default Green and Red Triangles (Bullish / Bearish) default to having the same triggering condition as the Entry it corresponds to. This is to highlight either a pyramiding concept, early exit, or you can change to account for other things occurring during your trades which could help you with Stop and Target management/considerations.
TradingView and many of its community members have done a lot for me, so this is my attempt to give back.
Heikin Ashi Candle Startegy for Long PositionThis strategy utilize Heikin-Ashi candlestick chart.
Heikin-Ashi technique is a Japanese candlestick-based technical trading tool that uses candlestick charts to represent and visualize market price data.
Heikin-Ashi candle is essentially taking an average of the movement.
There is a tendency with Heikin-Ashi for the candles to stay red during a downtrend and green during an uptrend.
This strategy only apply for long trading position.
The idea is trader will waiting 3 green candles for validation period (confirmation) before entering long position.
Different timeframe will result different result.
Number of validation period can be changed to see different result
This strategy has parameter for take profit percentage, trailing stop and stop loss.
User can set maximum active position to minimize risk and qty order.
This tool is useful for user who wants to backtest Heikin-Ashi trading strategy.
Script will emit alert when long position is opened and closed.
Warning of Backtesting
Backtesting is backward-looking. As the name implies, you are testing how something would have worked if you traded it perfectly in the past.
Past performance does not indicate future performance and you should not assume it does.
Backtesting assumes you never miss-fire, that you get in and out at the exactly perfect moment each time.
Backtesting assumes you have perfect liquidity, and your limit orders fill at a specific, pre-defined price every time (either the open, close, low, high, or some average of these).
Disclaimer
Do your own research and consider fundamental price of asset.
The indicators provided on this script is for educational purposes only.
Author does not offer advisory or brokerage services, nor does it recommend or advise users to buy or sell particular stocks or securities.
Please examined script and give feedback for further improvement.
Script are open to public, everyone see and clone source code or just apply to chart. Please make comment for improvement.
Configurable Multi MA Crossover Voting SystemThis strategy goes long when all fast moving averages that you have defined are above their counterpart slow moving averages.
Long position is closed when profit or loss target is hit and at least one of the fast moving averages is below its counterpart slow moving average.
The format of the config is simple. The format is : FASTxSLOW,FASTxSLOW,...
Example : If you want 2 moving averages fast=9,slow=14 and fast=20,slow=50 you define it like this : 9x14,20x50
Another example : 5x10,10x15,15x20 => means 3 moving average setups : first wih fast=5/slow=10, second with fast=10/slow=15, last with fast=15/slow=20
You can chose the type of moving average : SMA, WMA, VWMA (i got issues with EMA/RMA so i removed them)
You can chose the source of the moving average : high, close, hl2 etc.
You can chose the period on which ATR is calculated and ATR profit/loss factors.
Profit is calculated like : buy_price + atr_factor*atr
Loss is calculated like : buy_price - atr_factor*atr
Performance in backtest is variable depending on the timeframe, the options and the market.
Performance in backtest suggests it works better for higher timeframes like 1d, 4h etc.
Disclaimer
Please remember that past performance may not be indicative of future results.
Due to various factors, including changing market conditions, the strategy may no longer perform as well as in historical backtesting.
This post and the script don’t provide any financial advice.
[astropark] Moon Phases [strategy]Dear Followers,
today I'm glad to present you an indicator which calculates Moon Phases and let's you backtest the simplest strategy over it: buy/sell on full moon and do the opposite on new moon.
This is a public free indicator based on the public one by @paaax:
I added my usual backtesting logic, plus some more customization inputs for easy coloring.
The lower the timeframe you backtest on, the more backtesting data are effective.
Enjoy!
-- astropark
Noro's SILA v1.6L StrategyBacktesting
Backtesting (for all the time of existence of couple) only with software configurations to default (without optimization of parameters):
US = Uptrend-Sensivity
DS = Downtrend-Sensivity
It is recommended and by default:
- the normal market requires US=DS (for example US=5, DS=5)
- very bear market requires US DS, (for example US=5, DS=0)
- very bull market requires US DS, (US=0, DS=5)
Cryptocurrencies it is very bull market (US=0, DS=5)
Backtesting BTC/FIAT
D1 timeframe
identical parameters for all pairs
BTC/USD (Bitstamp) profit of +41805%
BTC/EUR (BTC-e) profit of +1147%
BTC/RUB (BTC-e) profit of +1162%
BTC/JPY (Bitflyer) profit of +215%
BTC/CNY (BTCChina) profit of 54948%
Backtesting ALTCOIN/BTC
D1 timeframe
identical parameters for all pairs
the exchange Poloniex
top-10 of cryptocurrencies on capitalization at the time of this text
NA = TradingView can't make backtest because of too low price of this cryptocurrency, or on the website there are no quotations of this cryptocurrency
ETH/BTC (Etherium) profit of +11690%
XRP/BTC (Ripple) loss of-100%
LTC/BTC (Litecoin) NA
ETC/BTC (Etherium Classic) profit of +214%
NEM/BTC loss of-49%
DASH/BTC profit of +106%
IOTA/BTC NA
XMR/BTC (Monero) profit of +96%
STRAT/BTC (Stratis) loss of-31%
ALTCOIN/ALTCOIN - not recomended
I don't need your money, I need reputation and likes.
Naive Bayes Candlestick Pattern Classifier v1.1 BETAAn intermezzo on why i made this script publication..
A : Candlestick Pattern took hours to backtest, why not using Machine Learning techniques?
B : Machine Learning, no that's gonna be really heavy bro!
A : Not really, because we use Naive Bayes.
B : The simplest, yet powerful machine learning algorithm to separate (a.k.a classify) multivariate data.
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Hello, everyone!
After deep research in extracting meaningful information from the market, I ended up building this powerful machine learning indicator based on the evolution of Bayesian Statistics. This indicator not only leverages the simplicity of Naive Bayes but also extends its application to candlestick pattern analysis, making it an invaluable tool for traders who are looking to enhance their technical analysis without spending countless hours manually backtesting each pattern on each market!.
What most interesting part is actually after learning all of likely useless methods like fibonacci, supply and demand, volume profile, etc. We always ended up back to basic like support and resistance and candlestick patterns, but with a slight twist on strategy algorithm design and statistical approach. Thus, the only reason why i made this, because i exactly know that you guys will ended up in this position as time goes by.
The essence of this indicator lies in its ability to automate the recognition and statistical evaluation of various candlestick patterns. Traditionally, traders have relied on visual inspection and manual backtesting to determine the effectiveness of patterns like Bullish Engulfing, Bearish Engulfing, Harami variations, Hammer formations, and even more complex multi-candle patterns such as Three White Soldiers, Three Black Crows, Dark Cloud Cover, and Piercing Pattern. However, these conventional methods are both time-consuming and prone to subjective bias.
To address these challenges, I employed Naive Bayes—a probabilistic classifier that, despite its simplicity, offers robust performance in various domains. Naive Bayes assumes that each feature is independent of the others given the class label, which, although a strong assumption, works remarkably well in practice, especially when the dataset is large like market data and the feature space is high-dimensional. In our case, each candlestick pattern acts as a feature that can be statistically evaluated based on its historical performance. The indicator calculates a probability that a given pattern will lead to a price reversal, by comparing the pattern’s close price to the highest or lowest price achieved in a lookahead window.
One of the standout features of this script is its flexibility. Each candlestick pattern is not only coded into the system but also comes with individual toggles to enable or disable them based on your trading strategy. This means you can choose to focus on single-candle patterns like Bullish Engulfing or more complex multi-candle formations such as Three White Soldiers, without modifying the core code. The built-in customization options allow you to adjust colors and labels for each pattern, giving you the freedom to tailor the visual output to your preference. This level of customization ensures that the indicator integrates seamlessly into your existing TradingView setup.
Moreover, the indicator isn’t just about pattern recognition—it also incorporates outcome-based learning. Every time a pattern is detected, it looks ahead a predefined number of bars to evaluate if the expected reversal actually materialized. This outcome is then stored in arrays, and over time, the script dynamically calculates the probability of success for each pattern. These probabilities are presented in a real-time updating table on your chart, which shows not only the percentage probability but also the count of historical occurrences. With this information at your fingertips, you can quickly gauge the reliability of each pattern in your chosen market and timeframe.
Another significant advantage of this approach is its speed and efficiency. While more complex machine learning models like neural networks might require heavy computational resources and longer training times, the Naive Bayes classifier in this script is lightweight, instantaneous and can be updated on the fly with each new bar. This real-time capability is essential for modern traders who need to make quick decisions in fast-paced markets.
Furthermore, by automating the process of backtesting, the indicator frees up your time to focus on other aspects of trading strategy development. Instead of manually analyzing hundreds or even thousands of candles, you can rely on the statistical power of Naive Bayes to provide you with insights on which patterns are most likely to result in profitable moves. This not only enhances your efficiency but also helps to eliminate the cognitive biases that often plague manual analysis.
In summary, this indicator represents a fusion of traditional candlestick analysis with modern machine learning techniques. It harnesses the simplicity and effectiveness of Naive Bayes to deliver a dynamic, real-time evaluation of various candlestick patterns. Whether you are a seasoned trader looking to refine your technical analysis or a beginner eager to understand market dynamics, this tool offers a powerful, customizable, and efficient solution. Welcome to a new era where advanced statistical methods meet practical trading insights—happy trading and may your patterns always be in your favor!
Note : On this current released beta version, you must manually adjust reversal percentage move based on each market. Further updates may include automated best range detection and probability.
