Market Trend Levels Non-Repainting [BigBeluga X PineIndicators]This strategy is based on the Market Trend Levels Detector developed by BigBeluga. Full credit for the concept and original indicator goes to BigBeluga.
The Market Trend Levels Detector Strategy is a non-repainting trend-following strategy that identifies market trend shifts using two Exponential Moving Averages (EMA). It also detects key price levels and allows traders to apply multiple filters to refine trade entries and exits.
This strategy is designed for trend trading and enables traders to:
Identify trend direction based on EMA crossovers.
Detect significant market levels using labeled trend lines.
Use multiple filter conditions to improve trade accuracy.
Avoid false signals through non-repainting calculations.
How the Market Trend Levels Detector Strategy Works
1. Core Trend Detection Using EMA Crossovers
The strategy detects trend shifts using two EMAs:
Fast EMA (default: 12 periods) – Reacts quickly to price movements.
Slow EMA (default: 25 periods) – Provides a smoother trend confirmation.
A bullish crossover (Fast EMA crosses above Slow EMA) signals an uptrend , while a bearish crossover (Fast EMA crosses below Slow EMA) signals a downtrend .
2. Market Level Detection & Visualization
Each time an EMA crossover occurs, a trend level line is drawn:
Bullish crossover → A green line is drawn at the low of the crossover candle.
Bearish crossover → A purple line is drawn at the high of the crossover candle.
Lines can be extended to act as support and resistance zones for future price action.
Additionally, a small label (●) appears at each crossover to mark the event on the chart.
3. Trade Entry & Exit Conditions
The strategy allows users to choose between three trading modes:
Long Only – Only enters long trades.
Short Only – Only enters short trades.
Long & Short – Trades in both directions.
Entry Conditions
Long Entry:
A bullish EMA crossover occurs.
The trade direction setting allows long trades.
Filter conditions (if enabled) confirm a valid long signal.
Short Entry:
A bearish EMA crossover occurs.
The trade direction setting allows short trades.
Filter conditions (if enabled) confirm a valid short signal.
Exit Conditions
Long Exit:
A bearish EMA crossover occurs.
Exit filters (if enabled) indicate an invalid long position.
Short Exit:
A bullish EMA crossover occurs.
Exit filters (if enabled) indicate an invalid short position.
Additional Trade Filters
To improve trade accuracy, the strategy allows traders to apply up to 7 additional filters:
RSI Filter: Only trades when RSI confirms a valid trend.
MACD Filter: Ensures MACD histogram supports the trade direction.
Stochastic Filter: Requires %K line to be above/below threshold values.
Bollinger Bands Filter: Confirms price position relative to the middle BB line.
ADX Filter: Ensures the trend strength is above a set threshold.
CCI Filter: Requires CCI to indicate momentum in the right direction.
Williams %R Filter: Ensures price momentum supports the trade.
Filters can be enabled or disabled individually based on trader preference.
Dynamic Level Extension Feature
The strategy provides an optional feature to extend trend lines until price interacts with them again:
Bullish support lines extend until price revisits them.
Bearish resistance lines extend until price revisits them.
If price breaks a line, the line turns into a dotted style , indicating it has been breached.
This helps traders identify key levels where trend shifts previously occurred, providing useful support and resistance insights.
Customization Options
The strategy includes several adjustable settings :
Trade Direction: Choose between Long Only, Short Only, or Long & Short.
Trend Lengths: Adjust the Fast & Slow EMA lengths.
Market Level Extension: Decide whether to extend support/resistance lines.
Filters for Trade Confirmation: Enable/disable individual filters.
Color Settings: Customize line colors for bullish and bearish trend shifts.
Maximum Displayed Lines: Limit the number of drawn support/resistance lines.
Considerations & Limitations
Trend Lag: As with any EMA-based strategy, signals may be slightly delayed compared to price action.
Sideways Markets: This strategy works best in trending conditions; frequent crossovers in sideways markets can produce false signals.
Filter Usage: Enabling multiple filters may reduce trade frequency, but can also improve trade quality.
Line Overlap: If many crossovers occur in a short period, the chart may become cluttered with multiple trend levels. Adjusting the "Display Last" setting can help.
Conclusion
The Market Trend Levels Detector Strategy is a non-repainting trend-following system that combines EMA crossovers, market level detection, and customizable filters to improve trade accuracy.
By identifying trend shifts and key price levels, this strategy can be used for:
Trend Confirmation – Using EMA crossovers and filters to confirm trend direction.
Support & Resistance Trading – Identifying dynamic levels where price reacts.
Momentum-Based Trading – Combining EMA crossovers with additional momentum filters.
This strategy is fully customizable and can be adapted to different trading styles, timeframes, and market conditions.
Full credit for the original concept and indicator goes to BigBeluga.
Strategy
Gradient Trend Filter STRATEGY [ChartPrime/PineIndicators]This strategy is based on the Gradient Trend Filter indicator developed by ChartPrime. Full credit for the concept and indicator goes to ChartPrime.
The Gradient Trend Filter Strategy is designed to execute trades based on the trend analysis and filtering system provided by the Gradient Trend Filter indicator. It integrates a noise-filtered trend detection system with a color-gradient visualization, helping traders identify trend strength, momentum shifts, and potential reversals.
How the Gradient Trend Filter Strategy Works
1. Noise Filtering for Smoother Trends
To reduce false signals caused by market noise, the strategy applies a three-stage smoothing function to the source price. This function ensures that trend shifts are detected more accurately, minimizing unnecessary trade entries and exits.
The filter is based on an Exponential Moving Average (EMA)-style smoothing technique.
It processes price data in three successive passes, refining the trend signal before generating trade entries.
This filtering technique helps eliminate minor fluctuations and highlights the true underlying trend.
2. Multi-Layered Trend Bands & Color-Based Trend Visualization
The Gradient Trend Filter constructs multiple trend bands around the filtered trend line, acting as dynamic support and resistance zones.
The mid-line changes color based on the trend direction:
Green for uptrends
Red for downtrends
A gradient cloud is formed around the trend line, dynamically shifting colors to provide early warning signals of trend reversals.
The outer bands function as potential support and resistance, helping traders determine stop-loss and take-profit zones.
Visualization elements used in this strategy:
Trend Filter Line → Changes color between green (bullish) and red (bearish).
Trend Cloud → Dynamically adjusts color based on trend strength.
Orange Markers → Appear when a trend shift is confirmed.
Trade Entry & Exit Conditions
This strategy automatically enters trades based on confirmed trend shifts detected by the Gradient Trend Filter.
1. Trade Entry Rules
Long Entry:
A bullish trend shift is detected (trend direction changes to green).
The filtered trend value crosses above zero, confirming upward momentum.
The strategy enters a long position.
Short Entry:
A bearish trend shift is detected (trend direction changes to red).
The filtered trend value crosses below zero, confirming downward momentum.
The strategy enters a short position.
2. Trade Exit Rules
Closing a Long Position:
If a bearish trend shift occurs, the strategy closes the long position.
Closing a Short Position:
If a bullish trend shift occurs, the strategy closes the short position.
The trend shift markers (orange diamonds) act as a confirmation signal, reinforcing the validity of trade entries and exits.
Customization Options
This strategy allows traders to adjust key parameters for flexibility in different market conditions:
Trade Direction: Choose between Long Only, Short Only, or Long & Short .
Trend Length: Modify the length of the smoothing function to adapt to different timeframes.
Line Width & Colors: Customize the visual appearance of trend lines and cloud colors.
Performance Table: Enable or disable the equity performance table that tracks historical trade results.
Performance Tracking & Reporting
A built-in performance table is included to monitor monthly and yearly trading performance.
The table calculates monthly percentage returns, displaying them in a structured format.
Color-coded values highlight profitable months (blue) and losing months (red).
Tracks yearly cumulative performance to assess long-term strategy effectiveness.
Traders can use this feature to evaluate historical performance trends and optimize their strategy settings accordingly.
How to Use This Strategy
Identify Trend Strength & Reversals:
Use the trend line and cloud color changes to assess trend strength and detect potential reversals.
Monitor Momentum Shifts:
Pay attention to gradient cloud color shifts, as they often appear before the trend line changes color.
This can indicate early momentum weakening or strengthening.
Act on Trend Shift Markers:
Use orange diamonds as confirmation signals for trend shifts and trade entry/exit points.
Utilize Cloud Bands as Support/Resistance:
The outer bands of the cloud serve as dynamic support and resistance, helping with stop-loss and take-profit placement.
Considerations & Limitations
Trend Lag: Since the strategy applies a smoothing function, entries may be slightly delayed compared to raw price action.
Volatile Market Conditions: In high-volatility markets, trend shifts may occur more frequently, leading to higher trade frequency.
Optimized for Trend Trading: This strategy is best suited for trending markets and may produce false signals in sideways (ranging) conditions.
Conclusion
The Gradient Trend Filter Strategy is a trend-following system based on the Gradient Trend Filter indicator by ChartPrime. It integrates noise filtering, trend visualization, and gradient-based color shifts to help traders identify strong market trends and potential reversals.
By combining trend filtering with a multi-layered cloud system, the strategy provides clear trade signals while minimizing noise. Traders can use this strategy for long-term trend trading, momentum shifts, and support/resistance-based decision-making.
This strategy is a fully automated system that allows traders to execute long, short, or both directions, with customizable settings to adapt to different market conditions.
Credit for the original concept and indicator goes to ChartPrime.
Simple APF Strategy Backtesting [The Quant Science]Simple backtesting strategy for the quantitative indicator Autocorrelation Price Forecasting. This is a Buy & Sell strategy that operates exclusively with long orders. It opens long positions and generates profit based on the future price forecast provided by the indicator. It's particularly suitable for trend-following trading strategies or directional markets with an established trend.
Main functions
1. Cycle Detection: Utilize autocorrelation to identify repetitive market behaviors and cycles.
2. Forecasting for Backtesting: Simulate trades and assess the profitability of various strategies based on future price predictions.
Logic
The strategy works as follow:
Entry Condition: Go long if the hypothetical gain exceeds the threshold gain (configurable by user interface).
Position Management: Sets a take-profit level based on the future price.
Position Sizing: Automatically calculates the order size as a percentage of the equity.
No Stop-Loss: this strategy doesn't includes any stop loss.
Example Use Case
A trader analyzes a dayli period using 7 historical bars for autocorrelation.
Sets a threshold gain of 20 points using a 5% of the equity for each trade.
Evaluates the effectiveness of a long-only strategy in this period to assess its profitability and risk-adjusted performance.
User Interface
Length: Set the length of the data used in the autocorrelation price forecasting model.
Thresold Gain: Minimum value to be considered for opening trades based on future price forecast.
Order Size: percentage size of the equity used for each single trade.
Strategy Limit
This strategy does not use a stop loss. If the price continues to drop and the future price forecast is incorrect, the trader may incur a loss or have their capital locked in the losing trade.
Disclaimer!
This is a simple template. Use the code as a starting point rather than a finished solution. The script does not include important parameters, so use it solely for educational purposes or as a boilerplate.
TEMA OBOS Strategy PakunTEMA OBOS Strategy
Overview
This strategy combines a trend-following approach using the Triple Exponential Moving Average (TEMA) with Overbought/Oversold (OBOS) indicator filtering.
By utilizing TEMA crossovers to determine trend direction and OBOS as a filter, it aims to improve entry precision.
This strategy can be applied to markets such as Forex, Stocks, and Crypto, and is particularly designed for mid-term timeframes (5-minute to 1-hour charts).
Strategy Objectives
Identify trend direction using TEMA
Use OBOS to filter out overbought/oversold conditions
Implement ATR-based dynamic risk management
Key Features
1. Trend Analysis Using TEMA
Uses crossover of short-term EMA (ema3) and long-term EMA (ema4) to determine entries.
ema4 acts as the primary trend filter.
2. Overbought/Oversold (OBOS) Filtering
Long Entry Condition: up > down (bullish trend confirmed)
Short Entry Condition: up < down (bearish trend confirmed)
Reduces unnecessary trades by filtering extreme market conditions.
3. ATR-Based Take Profit (TP) & Stop Loss (SL)
Adjustable ATR multiplier for TP/SL
Default settings:
TP = ATR × 5
SL = ATR × 2
Fully customizable risk parameters.
4. Customizable Parameters
TEMA Length (for trend calculation)
OBOS Length (for overbought/oversold detection)
Take Profit Multiplier
Stop Loss Multiplier
EMA Display (Enable/Disable TEMA lines)
Bar Color Change (Enable/Disable candle coloring)
Trading Rules
Long Entry (Buy Entry)
ema3 crosses above ema4 (Golden Cross)
OBOS indicator confirms up > down (bullish trend)
Execute a buy position
Short Entry (Sell Entry)
ema3 crosses below ema4 (Death Cross)
OBOS indicator confirms up < down (bearish trend)
Execute a sell position
Take Profit (TP)
Entry Price + (ATR × TP Multiplier) (Default: 5)
Stop Loss (SL)
Entry Price - (ATR × SL Multiplier) (Default: 2)
TP/SL settings are fully customizable to fine-tune risk management.
Risk Management Parameters
This strategy emphasizes proper position sizing and risk control to balance risk and return.
Trading Parameters & Considerations
Initial Account Balance: $7,000 (adjustable)
Base Currency: USD
Order Size: 10,000 USD
Pyramiding: 1
Trading Fees: $0.94 per trade
Long Position Margin: 50%
Short Position Margin: 50%
Total Trades (M5 Timeframe): 128
Deep Test Results (2024/11/01 - 2025/02/24)BTCUSD-5M
Total P&L：+1638.20USD
Max equity drawdown：694.78USD
Total trades：128
Profitable trades:44.53
Profit factor:1.45
These settings aim to protect capital while maintaining a balanced risk-reward approach.
Visual Support
TEMA Lines (Three EMAs)
Trend direction is indicated by color changes (Blue/Orange)
ema3 (short-term) and ema4 (long-term) crossover signals potential entries
OBOS Histogram
Green → Strong buying pressure
Red → Strong selling pressure
Blue → Possible trend reversal
Entry & Exit Markers
Blue Arrow → Long Entry Signal
Red Arrow → Short Entry Signal
Take Profit / Stop Loss levels displayed
Strategy Improvements & Uniqueness
This strategy is based on indicators developed by "l_lonthoff" and "jdmonto0", but has been significantly optimized for better entry accuracy, visual clarity, and risk management.
Enhanced Trend Identification with TEMA
Detects early trend reversals using ema3 & ema4 crossover
Reduces market noise for a smoother trend-following approach
Improved OBOS Filtering
Prevents excessive trading
Reduces unnecessary risk exposure
Dynamic Risk Management with ATR-Based TP/SL
Not a fixed value → TP/SL adjusts to market volatility
Fully customizable ATR multiplier settings
(Default: TP = ATR × 5, SL = ATR × 2)
Summary
The TEMA + OBOS Strategy is a simple yet powerful trading method that integrates trend analysis and oscillators.
TEMA for trend identification
OBOS for noise reduction & overbought/oversold filtering
ATR-based TP/SL settings for dynamic risk management
Before using this strategy, ensure thorough backtesting and demo trading to fine-tune parameters according to your trading style.
Non-Repainting Renko Emulation Strategy [PineIndicators]Introduction: The Repainting Problem in Renko Strategies
Renko charts are widely used in technical analysis for their ability to filter out market noise and emphasize price trends. Unlike traditional candlestick charts, which are based on fixed time intervals, Renko charts construct bricks only when price moves by a predefined amount. This makes them useful for trend identification while reducing small fluctuations.
However, Renko-based trading strategies often fail in live trading due to a fundamental issue: repainting .
Why Do Renko Strategies Repaint?
Most trading platforms, including TradingView, generate Renko charts retrospectively based on historical price data. This leads to the following issues:
Renko bricks can change or disappear when new data arrives.
Backtesting results do not reflect real market conditions. Strategies may appear highly profitable in backtests because historical data is recalculated with hindsight.
Live trading produces different results than backtesting. Traders cannot know in advance whether a new Renko brick will form until price moves far enough.
Objective of the Renko Emulator
This script simulates Renko behavior on a standard time-based chart without repainting. Instead of using TradingView’s built-in Renko charting, which recalculates past bricks, this approach ensures that once a Renko brick is formed, it remains unchanged .
Key benefits:
No past bricks are recalculated or removed.
Trading strategies can execute reliably without false signals.
Renko-based logic can be applied on a time-based chart.
How the Renko Emulator Works
1. Parameter Configuration & Initialization
The script defines key user inputs and variables:
brickSize : Defines the Renko brick size in price points, adjustable by the user.
renkoPrice : Stores the closing price of the last completed Renko brick.
prevRenkoPrice : Stores the price level of the previous Renko brick.
brickDir : Tracks the direction of Renko bricks (1 = up, -1 = down).
newBrick : A boolean flag that indicates whether a new Renko brick has been formed.
brickStart : Stores the bar index at which the current Renko brick started.
2. Identifying Renko Brick Formation Without Repainting
To ensure that the strategy does not repaint, Renko calculations are performed only on confirmed bars.
The script calculates the difference between the current price and the last Renko brick level.
If the absolute price difference meets or exceeds the brick size, a new Renko brick is formed.
The new Renko price level is updated based on the number of bricks that would fit within the price movement.
The direction (brickDir) is updated , and a flag ( newBrick ) is set to indicate that a new brick has been formed.
3. Visualizing Renko Bricks on a Time-Based Chart
Since TradingView does not support live Renko charts without repainting, the script uses graphical elements to draw Renko-style bricks on a standard chart.
Each time a new Renko brick forms, a colored rectangle (box) is drawn:
Green boxes → Represent bullish Renko bricks.
Red boxes → Represent bearish Renko bricks.
This allows traders to see Renko-like formations on a time-based chart, while ensuring that past bricks do not change.
Trading Strategy Implementation
Since the Renko emulator provides a stable price structure, it is possible to apply a consistent trading strategy that would otherwise fail on a traditional Renko chart.
1. Entry Conditions
A long trade is entered when:
The previous Renko brick was bearish .
The new Renko brick confirms an upward trend .
There is no existing long position .
A short trade is entered when:
The previous Renko brick was bullish .
The new Renko brick confirms a downward trend .
There is no existing short position .
2. Exit Conditions
Trades are closed when a trend reversal is detected:
Long trades are closed when a new bearish brick forms.
Short trades are closed when a new bullish brick forms.
Key Characteristics of This Approach
1. No Historical Recalculation
Once a Renko brick forms, it remains fixed and does not change.
Past price action does not shift based on future data.
2. Trading Strategies Operate Consistently
Since the Renko structure is stable, strategies can execute without unexpected changes in signals.
Live trading results align more closely with backtesting performance.
3. Allows Renko Analysis Without Switching Chart Types
Traders can apply Renko logic without leaving a standard time-based chart.
This enables integration with indicators that normally cannot be used on traditional Renko charts.
Considerations When Using This Strategy
Trade execution may be delayed compared to standard Renko charts. Since new bricks are only confirmed on closed bars, entries may occur slightly later.
Brick size selection is important. A smaller brickSize results in more frequent trades, while a larger brickSize reduces signals.
Conclusion
This Renko Emulation Strategy provides a method for using Renko-based trading strategies on a time-based chart without repainting. By ensuring that bricks do not change once formed, it allows traders to use stable Renko logic while avoiding the issues associated with traditional Renko charts.
This approach enables accurate backtesting and reliable live execution, making it suitable for trend-following and swing trading strategies that rely on Renko price action.
is_strategyCorrection-Adaptive Trend Strategy (Open-Source)
Core Advantage: Designed specifically for the is_correction indicator, with full transparency and customization options.
Key Features:
Open-Source Code:
✅ Full access to the strategy logic – study how every trade signal is generated.
✅ Freedom to customize – modify entry/exit rules, risk parameters, or add new indicators.
✅ No black boxes – understand and trust every decision the strategy makes.
Built for is_correction:
Filters out false signals during market noise.
Works only in confirmed trends (is_correction = false).
Adaptable for Your Needs:
Change Take Profit/Stop Loss ratios directly in the code.
Add alerts, notifications, or integrate with other tools (e.g., Volume Profile).
For Developers/Traders:
Use the code as a template for your own strategies.
Test modifications risk-free on historical data.
How the Strategy Works:
Main Goal:
Automatically buys when the price starts rising and sells when it starts falling, but only during confirmed trends (ignoring temporary pullbacks).
What You See on the Chart:
📈 Up arrows ▼ (below the candle) = Buy signal.
📉 Down arrows ▲ (above the candle) = Sell signal.
Gray background = Market is in a correction (no trades).
Key Mechanics:
Buy Condition:
Price closes higher than the previous candle + is_correction confirms the main trend (not a pullback).
Example: Red candle → green candle → ▼ arrow → buy.
Sell Condition:
Price closes lower than the previous candle + is_correction confirms the trend (optional: turn off short-selling in settings).
Exit Rules:
Closes trades automatically at:
+0.5% profit (adjustable in settings).
-0.5% loss (adjustable).
Or if a reverse signal appears (e.g., sell signal after a buy).
User-Friendly Settings:
Sell – On (default: ON):
ON → Allows short-selling (selling when price falls).
OFF → Strategy only buys and closes positions.
Revers (default: OFF):
ON → Inverts signals (▼ = sell, ▲ = buy).
%Profit & %Loss:
Adjust these values (0-30%) to increase/decrease profit targets and risk.
Example Scenario:
Buy Signal:
Price rises for 3 days → green ▼ arrow → strategy buys.
Stop loss set 0.5% below entry price.
If price keeps rising → trade closes at +0.5% profit.
Correction Phase:
After a rally, price drops for 1 day → gray background → strategy ignores the drop (no action).
Stop Loss Trigger:
If price drops 0.5% from entry → trade closes automatically.
Key Features:
Correction Filter (is_correction):
Acts as a “noise filter” → avoids trades during temporary pullbacks.
Flexibility:
Disable short-selling, flip signals, or tweak profit/loss levels in seconds.
Transparency:
Open-source code → see exactly how every signal is generated (click “Source” in TradingView).
Tips for Beginners:
Test First:
Run the strategy on historical data (click the “Chart” icon in TradingView).
See how it performed in the past.
Customize It:
Increase %Profit to 2-3% for volatile assets like crypto.
Turn off Sell – On if short-selling confuses you.
Trust the Stop Loss:
Even if you think the price will rebound, the strategy will close at -0.5% to protect your capital.
Where to Find Settings:
Click the strategy name on the top-left of your chart → adjust sliders/toggles in the menu.
Русская Версия
Трендовая стратегия с открытым кодом
Главное преимущество: Полная прозрачность логики и адаптация под ваши нужды.
Особенности:
Открытый исходный код:
✅ Видите всю «кухню» стратегии – как формируются сигналы, когда открываются сделки.
✅ Меняйте правила – корректируйте тейк-профит, стоп-лосс или добавляйте новые условия.
✅ Никаких секретов – вы контролируете каждое правило.
Заточка под is_correction:
Игнорирует ложные сигналы в коррекциях.
Работает только в сильных трендах (is_correction = false).
Гибкая настройка:
Подстройте параметры под свой риск-менеджмент.
Добавьте свои индикаторы или условия для входа.
Для трейдеров и разработчиков:
Используйте код как основу для своих стратегий.
Тестируйте изменения на истории перед реальной торговлей.
Простыми словами:
Почему это удобно:
Открытый код = полный контроль. Вы можете:
Увидеть, как именно стратегия решает купить или продать.
Изменить правила закрытия сделок (например, поставить TP=2% вместо 1.5%).
Добавить новые условия (например, торговать только при высоком объёме).
Примеры кастомизации:
Новички: Меняйте только TP/SL в настройках (без кодинга).
Продвинутые: Добавьте RSI-фильтр, чтобы избегать перекупленности.
Разработчики: Встройте стратегию в свою торговую систему.
Как начать:
Скачайте код из TradingView.
Изучите логику в разделе strategy.entry/exit.
Меняйте параметры в блоке input.* (безопасно!).
Тестируйте изменения и оптимизируйте под свои цели.
Как работает стратегия:
Главная задача:
Автоматически покупает, когда цена начинает расти, и продаёт, когда падает. Но делает это «умно» — только когда рынок в основном тренде, а не во временном откате (коррекции).
Что видно на графике:
📈 Стрелки вверх ▼ (под свечой) — сигнал на покупку.
📉 Стрелки вниз ▲ (над свечой) — сигнал на продажу.
Серый фон — рынок в коррекции (не торгуем).
Как это работает:
Когда покупаем:
Если цена закрылась выше предыдущей и индикатор is_correction показывает «основной тренд» (не коррекция).
Пример: Была красная свеча → стала зелёная → появилась стрелка ▼ → покупаем.
Когда продаём:
Если цена закрылась ниже предыдущей и is_correction подтверждает тренд (опционально, можно отключить в настройках).
Когда закрываем сделку:
Автоматически при достижении:
+0.5% прибыли (можно изменить в настройках).
-0.5% убытка (можно изменить).
Или если появился противоположный сигнал (например, после покупки пришла стрелка продажи).
Настройки для чайников:
«Sell – On» (включено по умолчанию):
Если включено → стратегия будет продавать в шорт.
Если выключено → только покупки и закрытие позиций.
«Revers» (выключено по умолчанию):
Если включить → стратегия будет работать наоборот (стрелки ▼ = продажа, ▲ = покупка).
«%Profit» и «%Loss»:
Меняйте эти цифры (от 0 до 30), чтобы увеличить/уменьшить прибыль и риски.
Пример работы:
Сигнал на покупку:
Цена 3 дня растет → появляется зелёная стрелка ▼ → стратегия покупает.
Стоп-лосс ставится на 0.5% ниже цены входа.
Если цена продолжает расти → сделка закрывается при +0.5% прибыли.
Коррекция:
После роста цена падает на 1 день → фон становится серым → стратегия игнорирует это падение (не закрывает сделку).
Стоп-лосс:
Если цена упала на 0.5% от точки входа → сделка закрывается автоматически.
Важные особенности:
Фильтр коррекций (is_correction):
Это «защита от шума» — стратегия не реагирует на мелкие откаты, работая только в сильных трендах.
Гибкие настройки:
Можно запретить шорты, перевернуть сигналы или изменить уровни прибыли/убытка за 2 клика.
Прозрачность:
Весь код открыт → вы можете увидеть, как формируется каждый сигнал (меню «Исходник» в TradingView).
Советы для новичков:
Начните с теста:
Запустите стратегию на исторических данных (кнопка «Свеча» в окне TradingView).
Посмотрите, как она работала в прошлом.
Настройте под себя:
Увеличьте %Profit до 2-3%, если торгуете валюты.
Отключите «Sell – On», если не понимаете шорты.
Доверяйте стоп-лоссу:
Даже если кажется, что цена развернётся — стратегия закроет сделку при -0.5%, защитив ваш депозит.
Где найти настройки:
Кликните на название стратегии в верхнем левом углу графика → откроется меню с ползунками и переключателями.
Важно: Стратегия предоставляет «рыбу» – чтобы она стала «уловистой», адаптируйте её под свой стиль торговли!
Breakouts With Timefilter Strategy [LuciTech]This strategy captures breakout opportunities using pivot high/low breakouts while managing risk through dynamic stop-loss placement and position sizing. It includes a time filter to limit trades to specific sessions.
How It Works
A long trade is triggered when price closes above a pivot high, and a short trade when price closes below a pivot low.
Stop-loss can be set using ATR, prior candle high/low, or a fixed point value. Take-profit is based on a risk-reward multiplier.
Position size adjusts based on the percentage of equity risked.
Breakout signals are marked with triangles, and entry, stop-loss, and take-profit levels are plotted.
moving average filter: Bullish breakouts only trigger above the MA, bearish breakouts below.
The time filter shades the background during active trading hours.
Customization:
Adjustable pivot length for breakout sensitivity.
Risk settings: percentage risked, risk-reward ratio, and stop-loss type.
ATR settings: length, smoothing method (RMA, SMA, EMA, WMA).
Moving average filter (SMA, EMA, WMA, VWMA, HMA) to confirm breakouts.
ADX for BTC [PineIndicators]The ADX Strategy for BTC is a trend-following system that uses the Average Directional Index (ADX) to determine market strength and momentum shifts. Designed for Bitcoin trading, this strategy applies a customizable ADX threshold to confirm trend signals and optionally filters entries using a Simple Moving Average (SMA). The system features automated entry and exit conditions, dynamic trade visualization, and built-in trade tracking for historical performance analysis.
⚙️ Core Strategy Components
1️⃣ Average Directional Index (ADX) Calculation
The ADX indicator measures trend strength without indicating direction. It is derived from the Positive Directional Movement (+DI) and Negative Directional Movement (-DI):
+DI (Positive Directional Index): Measures upward price movement.
-DI (Negative Directional Index): Measures downward price movement.
ADX Value: Higher values indicate stronger trends, regardless of direction.
This strategy uses a default ADX length of 14 to smooth out short-term fluctuations while detecting sustainable trends.
2️⃣ SMA Filter (Optional Trend Confirmation)
The strategy includes a 200-period SMA filter to validate trend direction before entering trades. If enabled:
✅ Long Entry is only allowed when price is above a long-term SMA multiplier (5x the standard SMA length).
✅ If disabled, the strategy only considers the ADX crossover threshold for trade entries.
This filter helps reduce entries in sideways or weak-trend conditions, improving signal reliability.
📌 Trade Logic & Conditions
🔹 Long Entry Conditions
A buy signal is triggered when:
✅ ADX crosses above the threshold (default = 14), indicating a strengthening trend.
✅ (If SMA filter is enabled) Price is above the long-term SMA multiplier.
🔻 Exit Conditions
A position is closed when:
✅ ADX crosses below the stop threshold (default = 45), signaling trend weakening.
By adjusting the entry and exit ADX levels, traders can fine-tune sensitivity to trend changes.
📏 Trade Visualization & Tracking
Trade Markers
"Buy" label (▲) appears when a long position is opened.
"Close" label (▼) appears when a position is exited.
Trade History Boxes
Green if a trade is profitable.
Red if a trade closes at a loss.
Trend Tracking Lines
Horizontal lines mark entry and exit prices.
A filled trade box visually represents trade duration and profitability.
These elements provide clear visual insights into trade execution and performance.
⚡ How to Use This Strategy
1️⃣ Apply the script to a BTC chart in TradingView.
2️⃣ Adjust ADX entry/exit levels based on trend sensitivity.
3️⃣ Enable or disable the SMA filter for trend confirmation.
4️⃣ Backtest performance to analyze historical trade execution.
5️⃣ Monitor trade markers and history boxes for real-time trend insights.
This strategy is designed for trend traders looking to capture high-momentum market conditions while filtering out weak trends.
MACD Volume Strategy for XAUUSD (15m) [PineIndicators]The MACD Volume Strategy is a momentum-based trading system designed for XAUUSD on the 15-minute timeframe. It integrates two key market indicators: the Moving Average Convergence Divergence (MACD) and a volume-based oscillator to identify strong trend shifts and confirm trade opportunities. This strategy uses dynamic position sizing, incorporates leverage customization, and applies structured entry and exit conditions to improve risk management.
⚙️ Core Strategy Components
1️⃣ Volume-Based Momentum Calculation
The strategy includes a custom volume oscillator to filter trade signals based on market activity. The oscillator is derived from the difference between short-term and long-term volume trends using Exponential Moving Averages (EMAs)
Short EMA (default = 5) represents recent volume activity.
Long EMA (default = 8) captures broader volume trends.
Positive values indicate rising volume, supporting momentum-based trades.
Negative values suggest weak market activity, reducing signal reliability.
By requiring positive oscillator values, the strategy ensures momentum confirmation before entering trades.
2️⃣ MACD Trend Confirmation
The strategy uses the MACD indicator as a trend filter. The MACD is calculated as:
Fast EMA (16-period) detects short-term price trends.
Slow EMA (26-period) smooths out price fluctuations to define the overall trend.
Signal Line (9-period EMA) helps identify crossovers, signaling potential trend shifts.
Histogram (MACD – Signal) visualizes trend strength.
The system generates trade signals based on MACD crossovers around the zero line, confirming bullish or bearish trend shifts.
📌 Trade Logic & Conditions
🔹 Long Entry Conditions
A buy signal is triggered when all the following conditions are met:
✅ MACD crosses above 0, signaling bullish momentum.
✅ Volume oscillator is positive, confirming increased trading activity.
✅ Current volume is at least 50% of the previous candle’s volume, ensuring market participation.
🔻 Short Entry Conditions
A sell signal is generated when:
✅ MACD crosses below 0, indicating bearish momentum.
✅ Volume oscillator is positive, ensuring market activity is sufficient.
✅ Current volume is less than 50% of the previous candle’s volume, showing decreasing participation.
This multi-factor approach filters out weak or false signals, ensuring that trades align with both momentum and volume dynamics.
📏 Position Sizing & Leverage
Dynamic Position Calculation:
Qty = strategy.equity × leverage / close price
Leverage: Customizable (default = 1x), allowing traders to adjust risk exposure.
Adaptive Sizing: The strategy scales position sizes based on account equity and market price.
Slippage & Commission: Built-in slippage (2 points) and commission (0.01%) settings provide realistic backtesting results.
This ensures efficient capital allocation, preventing overexposure in volatile conditions.
🎯 Trade Management & Exits
Take Profit & Stop Loss Mechanism
Each position includes predefined profit and loss targets:
Take Profit: +10% of risk amount.
Stop Loss: Fixed at 10,100 points.
The risk-reward ratio remains balanced, aiming for controlled drawdowns while maximizing trade potential.
Visual Trade Tracking
To improve trade analysis, the strategy includes:
📌 Trade Markers:
"Buy" label when a long position opens.
"Close" label when a position exits.
📌 Trade History Boxes:
Green for profitable trades.
Red for losing trades.
📌 Horizontal Trade Lines:
Shows entry and exit prices.
Helps identify trend movements over multiple trades.
This structured visualization allows traders to analyze past performance directly on the chart.
⚡ How to Use This Strategy
1️⃣ Apply the script to a XAUUSD (Gold) 15m chart in TradingView.
2️⃣ Adjust leverage settings as needed.
3️⃣ Enable backtesting to assess past performance.
4️⃣ Monitor volume and MACD conditions to understand trade triggers.
5️⃣ Use the visual trade markers to review historical performance.
The MACD Volume Strategy is designed for short-term trading, aiming to capture momentum-driven opportunities while filtering out weak signals using volume confirmation.
Balance of Power for US30 4H [PineIndicators]The Balance of Power (BoP) Strategy is a momentum-based trading system for the US30 index on a 4-hour timeframe. It measures the strength of buyers versus sellers in each candle using the Balance of Power (BoP) indicator and executes trades based on predefined threshold crossovers. The strategy includes dynamic position sizing, adjustable leverage, and visual trade tracking.
⚙️ Core Strategy Mechanics
Positive values indicate buying strength.
Negative values indicate selling strength.
Values close to 1 suggest strong bullish momentum.
Values close to -1 indicate strong bearish pressure.
The strategy uses fixed threshold crossovers to determine trade entries and exits.
📌 Trade Logic
Entry Conditions
Long Entry: When BoP crosses above 0.8, signaling strong buying pressure.
Exit Conditions
Position Close: When BoP crosses below -0.8, indicating a shift to selling pressure.
This threshold-based system filters out low-confidence signals and focuses on high-momentum shifts.
📏 Position Sizing & Leverage
Leverage: Adjustable by the user (default = 5x).
Risk Management: Position size adapts dynamically based on equity fluctuations.
📊 Trade Visualization & History Tracking
Trade Markers:
"Buy" labels appear when a long position is opened.
"Close" labels appear when a position is exited.
Trade History Boxes:
Green for profitable trades.
Red for losing trades.
These elements provide clear visual tracking of past trade execution.
⚡ Usage & Customization
1️⃣ Apply the script to a US30 4H chart in TradingView.
2️⃣ Adjust leverage settings as needed.
3️⃣ Review trade signals and historical performance with visual markers.
4️⃣ Enable backtesting to evaluate past performance.
This strategy is designed for momentum-based trading and is best suited for volatile market conditions.
TSI Long/Short for BTC 2HThe TSI Long/Short for BTC 2H strategy is an advanced trend-following system designed specifically for trading Bitcoin (BTC) on a 2-hour timeframe. It leverages the True Strength Index (TSI) to identify momentum shifts and executes both long and short trades in response to dynamic market conditions.
Unlike traditional moving average-based strategies, this script uses a double-smoothed momentum calculation, enhancing signal accuracy and reducing noise. It incorporates automated position sizing, customizable leverage, and real-time performance tracking, ensuring a structured and adaptable trading approach.
🔹 What Makes This Strategy Unique?
Unlike simple crossover strategies or generic trend-following approaches, this system utilizes a customized True Strength Index (TSI) methodology that dynamically adjusts to market conditions.
🔸 True Strength Index (TSI) Filtering – The script refines the TSI by applying double exponential smoothing, filtering out weak signals and capturing high-confidence momentum shifts.
🔸 Adaptive Entry & Exit Logic – Instead of fixed thresholds, it compares the TSI value against a dynamically determined high/low range from the past 100 bars to confirm trade signals.
🔸 Leverage & Risk Optimization – Position sizing is dynamically adjusted based on account equity and leverage settings, ensuring controlled risk exposure.
🔸 Performance Monitoring System – A built-in performance tracking table allows traders to evaluate monthly and yearly results directly on the chart.
📊 Core Strategy Components
1️⃣ Momentum-Based Trade Execution
The strategy generates long and short trade signals based on the following conditions:
✅ Long Entry Condition – A buy signal is triggered when the TSI crosses above its 100-bar highest value (previously set), confirming bullish momentum.
✅ Short Entry Condition – A sell signal is generated when the TSI crosses below its 100-bar lowest value (previously set), indicating bearish pressure.
Each trade execution is fully automated, reducing emotional decision-making and improving trading discipline.
2️⃣ Position Sizing & Leverage Control
Risk management is a key focus of this strategy:
🔹 Dynamic Position Sizing – The script calculates position size based on:
Account Equity – Ensuring trade sizes adjust dynamically with capital fluctuations.
Leverage Multiplier – Allows traders to customize risk exposure via an adjustable leverage setting.
🔹 No Fixed Stop-Loss – The strategy relies on reversals to exit trades, meaning each position is closed when the opposite signal appears.
This design ensures maximum capital efficiency while adapting to market conditions in real time.
3️⃣ Performance Visualization & Tracking
Understanding historical performance is crucial for refining strategies. The script includes:
📌 Real-Time Trade Markers – Buy and sell signals are visually displayed on the chart for easy reference.
📌 Performance Metrics Table – Tracks monthly and yearly returns in percentage form, helping traders assess profitability over time.
📌 Trade History Visualization – Completed trades are displayed with color-coded boxes (green for long trades, red for short trades), visually representing profit/loss dynamics.
📢 Why Use This Strategy?
✔ Advanced Momentum Detection – Uses a double-smoothed TSI for more accurate trend signals.
✔ Fully Automated Trading – Removes emotional bias and enforces discipline.
✔ Customizable Risk Management – Adjust leverage and position sizing to suit your risk profile.
✔ Comprehensive Performance Tracking – Integrated reporting system provides clear insights into past trades.
This strategy is ideal for Bitcoin traders looking for a structured, high-probability system that adapts to both bullish and bearish trends on the 2-hour timeframe.
📌 How to Use: Simply add the script to your 2H BTC chart, configure your leverage settings, and let the system handle trade execution and tracking! 🚀
highs&lowsone of my first strategy: highs&lows
This strategy takes the highest high and the lowest low of a specified timeframe and specified bar count.
It will then takes the average between these two extremes to create a center line.
This creates a range of high middle and low.
Then the strategy takes the current market movement
which is the direct average(no specified timeframe and specified bar count) of the current high and low.
Using this "current market movement" within the range of high middle and low it determins when to buy and then sell the asset.
*********note***************
-this strategy is (bullish)
-works good with most futures assets that have volatility/ decent movement
(might add more details if I forget any)
(work in progress)
3x Supertrend (for Vietnamese stock market and vn30f1m)The 4Vietnamese 3x Supertrend Strategy is an advanced trend-following trading system developed in Pine Script™ and designed for publication on TradingView as an open-source strategy under the Mozilla Public License 2.0. This strategy leverages three Supertrend indicators with different ATR lengths and multipliers to identify optimal trade entries and exits while dynamically managing risk.
Key Features:
Option to build and hold long term positions with entry stop order. Try this to avoid market complex movement and retain long term investment style's benefits.
Advanced Entry & Exit Optimization: Includes configurable stop-loss mechanisms, pyramiding, and exit conditions tailored for different market scenarios.
Dynamic Risk Management: Implements features like selective stop-loss activation, trade window settings, and closing conditions based on trend reversals and loss management.
This strategy is particularly suited for traders seeking a systematic and rule-based approach to trend trading. By making it open-source, we aim to provide transparency, encourage community collaboration, and help traders refine and optimize their strategies for better performance.
License:
This script is released under the Mozilla Public License 2.0, allowing modifications and redistribution while maintaining open-source integrity.
Happy trading!
Statistical Arbitrage Pairs Trading - Long-Side OnlyThis strategy implements a simplified statistical arbitrage (" stat arb ") approach focused on mean reversion between two correlated instruments. It identifies opportunities where the spread between their normalized price series (Z-scores) deviates significantly from historical norms, then executes long-only trades anticipating reversion to the mean.
Key Mechanics:
1. Spread Calculation: The strategy computes Z-scores for both instruments to normalize price movements, then tracks the spread between these Z-scores.
2. Modified Z-Score: Uses a robust measure combining the median and Median Absolute Deviation (MAD) to reduce outlier sensitivity.
3. Entry Signal: A long position is triggered when the spread’s modified Z-score falls below a user-defined threshold (e.g., -1.0), indicating extreme undervaluation of the main instrument relative to its pair.
4. Exit Signal: The position closes automatically when the spread reverts to its historical mean (Z-score ≥ 0).
Risk management:
Trades are sized as a percentage of equity (default: 10%).
Includes commissions and slippage for realistic backtesting.
Tutorial - Adding sessions to strategiesA simple script to illustrate how to add sessions to trading strategies.
In this interactive tutorial, you'll learn how to add trading sessions to your strategies using Pine Script. By the end of this session (pun intended!), you'll be able to create custom trading windows that adapt to changing market conditions.
What You'll Learn:
Defining Trading Sessions: Understand how to set up specific time frames for buying and selling, tailored to your unique trading style.
RSI-Based Entry Signals: Discover how to use the Relative Strength Index (RSI) as a trigger for buy and sell signals, helping you capitalize on market trends.
Combining Session Logic with Trading Decisions: Learn how to integrate session-based logic into your strategy, ensuring that trades are executed only during designated times.
By combining these elements, we create an interactive strategy that:
1. Generates buy and sell signals based on RSI levels.
2. Checks if the market is open during a specific trading session (e.g., 1300-1700).
3. Executes trades only when both conditions are met.
**Tips & Variations:**
* Experiment with different RSI periods, thresholds, and sessions to optimize your strategy for various markets and time frames.
* Consider adding more advanced logic, such as stop-losses or position sizing, to further refine your trading approach.
Get ready to take your Pine Script skills to the next level!
~Description partially generated with Llama3_8B
Mean Reversion Pro Strategy [tradeviZion]Mean Reversion Pro Strategy : User Guide
A mean reversion trading strategy for daily timeframe trading.
Introduction
Mean Reversion Pro Strategy is a technical trading system that operates on the daily timeframe. The strategy uses a dual Simple Moving Average (SMA) system combined with price range analysis to identify potential trading opportunities. It can be used on major indices and other markets with sufficient liquidity.
The strategy includes:
Trading System
Fast SMA for entry/exit points (5, 10, 15, 20 periods)
Slow SMA for trend reference (100, 200 periods)
Price range analysis (20% threshold)
Position management rules
Visual Elements
Gradient color indicators
Three themes (Dark/Light/Custom)
ATR-based visuals
Signal zones
Status Table
Current position information
Basic performance metrics
Strategy parameters
Optional messages
📊 Strategy Settings
Main Settings
Trading Mode
Options: Long Only, Short Only, Both
Default: Long Only
Position Size: 10% of equity
Starting Capital: $20,000
Moving Averages
Fast SMA: 5, 10, 15, or 20 periods
Slow SMA: 100 or 200 periods
Default: Fast=5, Slow=100
🎯 Entry and Exit Rules
Long Entry Conditions
All conditions must be met:
Price below Fast SMA
Price below 20% of current bar's range
Price above Slow SMA
No existing position
Short Entry Conditions
All conditions must be met:
Price above Fast SMA
Price above 80% of current bar's range
Price below Slow SMA
No existing position
Exit Rules
Long Positions
Exit when price crosses above Fast SMA
No fixed take-profit levels
No stop-loss (mean reversion approach)
Short Positions
Exit when price crosses below Fast SMA
No fixed take-profit levels
No stop-loss (mean reversion approach)
💼 Risk Management
Position Sizing
Default: 10% of equity per trade
Initial capital: $20,000
Commission: 0.01%
Slippage: 2 points
Maximum one position at a time
Risk Control
Use daily timeframe only
Avoid trading during major news events
Consider market conditions
Monitor overall exposure
📊 Performance Dashboard
The strategy includes a comprehensive status table displaying:
Strategy Parameters
Current SMA settings
Trading direction
Fast/Slow SMA ratio
Current Status
Active position (Flat/Long/Short)
Current price with color coding
Position status indicators
Performance Metrics
Net Profit (USD and %)
Win Rate with color grading
Profit Factor with thresholds
Maximum Drawdown percentage
Average Trade value
📱 Alert Settings
Entry Alerts
Long Entry (Buy Signal)
Short Entry (Sell Signal)
Exit Alerts
Long Exit (Take Profit)
Short Exit (Take Profit)
Alert Message Format
Strategy name
Signal type and direction
Current price
Fast SMA value
Slow SMA value
💡 Usage Tips
Consider starting with Long Only mode
Begin with default settings
Keep track of your trades
Review results regularly
Adjust settings as needed
Follow your trading plan
⚠️ Disclaimer
This strategy is for educational and informational purposes only. It is not financial advice. Always:
Conduct your own research
Test thoroughly before live trading
Use proper risk management
Consider your trading goals
Monitor market conditions
Never risk more than you can afford to lose
📋 Release Notes
14 January 2025
Added New Fast & Slow SMA Options:
Fibonacci-based periods: 8, 13, 21, 144, 233, 377
Additional period: 50
Complete Fast SMA options now: 5, 8, 10, 13, 15, 20, 21, 34, 50
Complete Slow SMA options now: 100, 144, 200, 233, 377
Bug Fixes:
Fixed Maximum Drawdown calculation in the performance table
Now using strategy.max_drawdown_percent for accurate DD reporting
Previous version showed incorrect DD values
Performance metrics now accurately reflect trading results
Performance Note:
Strategy tested with Fast/Slow SMA 13/377
Test conducted with 10% equity risk allocation
Daily Timeframe
For Beginners - How to Modify SMA Levels:
Find this line in the code:
fastLength = input.int(title="Fast SMA Length", defval=5, options= )
To add a new Fast SMA period: Add the number to the options list, e.g.,
To remove a Fast SMA period: Remove the number from the options list
For Slow SMA, find:
slowLength = input.int(title="Slow SMA Length", defval=100, options= )
Modify the options list the same way
⚠️ Note: Keep the periods that make sense for your trading timeframe
💡 Tip: Test any new combinations thoroughly before live trading
"Trade with Discipline, Manage Risk, Stay Consistent" - tradeviZion
Phase Cross Strategy with Zone### Introduction to the Strategy
Welcome to the **Phase Cross Strategy with Zone and EMA Analysis**. This strategy is designed to help traders identify potential buy and sell opportunities based on the crossover of smoothed oscillators (referred to as "phases") and exponential moving averages (EMAs). By combining these two methods, the strategy offers a versatile tool for both trend-following and short-term trading setups.
### Key Features
1. **Phase Cross Signals**:
- The strategy uses two smoothed oscillators:
- **Leading Phase**: A simple moving average (SMA) with an upward offset.
- **Lagging Phase**: An exponential moving average (EMA) with a downward offset.
- Buy and sell signals are generated when these phases cross over or under each other, visually represented on the chart with green (buy) and red (sell) labels.
2. **Phase Zone Visualization**:
- The area between the two phases is filled with a green or red zone, indicating bullish or bearish conditions:
- Green zone: Leading phase is above the lagging phase (potential uptrend).
- Red zone: Leading phase is below the lagging phase (potential downtrend).
3. **EMA Analysis**:
- Includes five commonly used EMAs (13, 26, 50, 100, and 200) for additional trend analysis.
- Crossovers of the EMA 13 and EMA 26 act as secondary buy/sell signals to confirm or enhance the phase-based signals.
4. **Customizable Parameters**:
- You can adjust the smoothing length, source (price data), and offset to fine-tune the strategy for your preferred trading style.
### What to Pay Attention To
1. **Phases and Zones**:
- Use the green/red phase zone as an overall trend guide.
- Avoid taking trades when the phases are too close or choppy, as it may indicate a ranging market.
2. **EMA Trends**:
- Align your trades with the longer-term trend shown by the EMAs. For example:
- In an uptrend (price above EMA 50 or EMA 200), prioritize buy signals.
- In a downtrend (price below EMA 50 or EMA 200), prioritize sell signals.
3. **Signal Confirmation**:
- Consider combining phase cross signals with EMA crossovers for higher-confidence trades.
- Look for confluence between the phase signals and EMA trends.
4. **Risk Management**:
- Always set stop-loss and take-profit levels to manage risk.
- Use the phase and EMA zones to estimate potential support/resistance areas for exits.
5. **Whipsaws and False Signals**:
- Be cautious in low-volatility or sideways markets, as the strategy may generate false signals.
- Use additional indicators or filters to avoid entering trades during unclear market conditions.
### How to Use
1. Add the strategy to your chart in TradingView.
2. Adjust the input settings (e.g., smoothing length, offsets) to suit your trading preferences.
3. Enable the strategy tester to evaluate its performance on historical data.
4. Combine the signals with your own analysis and risk management plan for best results.
This strategy is a versatile tool, but like any trading method, it requires proper understanding and discretion. Always backtest thoroughly and trade with discipline. Let me know if you need further assistance or adjustments to the strategy!
Adaptive Trend Flow Strategy with Filters for SPXThe Adaptive Trend Flow Strategy with Filters for SPX is a complete trading algorithm designed to identify traits and offer actionable alerts for the SPX index. This Pine Script approach leverages superior technical signs and user-described parameters to evolve to marketplace conditions and optimize performance.
Key Features and Functionality
Dynamic Trend Detection: Utilizes a dual EMA-based totally adaptive method for fashion calculation.
The script smooths volatility the usage of an EMA filter and adjusts sensitivity through the sensitivity enter. This allows for real-time adaptability to market fluctuations.
Trend Filters for Precision:
SMA Filter: A Simple Moving Average (SMA) guarantees that trades are achieved best while the rate aligns with the shifting average trend, minimizing false indicators.
MACD Filter: The Moving Average Convergence Divergence (MACD) adds some other layer of confirmation with the aid of requiring alignment among the MACD line and its sign line.
Signal Generation:
Long Signals: Triggered when the fashion transitions from bearish to bullish, with all filters confirming the pass.
Short Signals: Triggered while the trend shifts from bullish to bearish, imparting opportunities for final positions.
User Customization:
Adjustable parameters for EMAs, smoothing duration, and sensitivity make certain the strategy can adapt to numerous buying and selling patterns.
Enable or disable filters (SMA or MACD) based totally on particular market conditions or consumer possibilities.
Leverage and Position Sizing: Incorporates a leverage aspect for dynamic position sizing.
Automatically calculates the exchange length based on account fairness and the leverage element, making sure hazard control is in area.
Visual Enhancements: Plots adaptive fashion ranges (foundation, top, decrease) for actual-time insights into marketplace conditions.
Color-coded bars and heritage to visually represent bullish or bearish developments.
Custom labels indicating crossover and crossunder occasions for clean sign visualization.
Alerts and Automation: Configurable alerts for each lengthy and quick indicators, well matched with automated buying and selling structures like plugpine.Com.
JSON-based alert messages consist of account credentials, motion type, and calculated position length for seamless integration.
Backtesting and Realistic Assumptions: Includes practical slippage, commissions, and preliminary capital settings for backtesting accuracy.
Leverages excessive-frequency trade sampling to make certain strong strategy assessment.
How It Works
Trend Calculation: The method derives a principal trend basis with the aid of combining fast and gradual EMAs. It then uses marketplace volatility to calculate adaptive upper and decrease obstacles, creating a dynamic channel.
Filter Integration: SMA and MACD filters work in tandem with the fashion calculation to ensure that handiest excessive-probability signals are accomplished.
Signal Execution: Signals are generated whilst the charge breaches those dynamic tiers and aligns with the fashion and filters, ensuring sturdy change access situations.
How to Use
Setup: Apply the approach to SPX or other well suited indices.
Adjust person inputs, together with ATR length, EMA smoothing, and sensitivity, to align together with your buying and selling possibilities.
Enable or disable the SMA and MACD filters to test unique setups.
Alerts: Configure signals for computerized notifications or direct buying and selling execution through third-celebration systems.
Use the supplied JSON payload to integrate with broking APIs or automation tools.
Optimization:
Experiment with leverage, filter out settings, and sensitivity to find most effective configurations to your hazard tolerance and marketplace situations.
Considerations and Best Practices
Risk Management: Always backtest the method with realistic parameters, together with conservative leverage and commissions.
Market Suitability: While designed for SPX, this method can adapt to other gadgets by means of adjusting key parameters.
Limitations: The method is trend-following and can underperform in enormously risky or ranging markets. Regularly evaluate and modify parameters primarily based on recent market conduct.
If you have any questions please let me know - I'm here to help!
BullBear with Volume-Percentile TP - Strategy [presentTrading] Happy New Year, everyone! I hope we have a fantastic year ahead.
It's been a while since I published an open script, but it's time to return.
This strategy introduces an indicator called Bull Bear Power, combined with an advanced take-profit system, which is the main innovative and educational aspect of this script. I hope all of you find some useful insights here. Welcome to engage in meaningful exchanges. This is a versatile tool suitable for both novice and experienced traders.
█ Introduction and How it is Different
Unlike traditional strategies that rely solely on price or volume indicators, this approach combines Bull Bear Power (BBP) with volume percentile analysis to identify optimal entry and exit points. It features a dynamic take-profit mechanism based on ATR (Average True Range) multipliers adjusted by volume and percentile factors, ensuring adaptability to diverse market conditions. This multifaceted strategy not only improves signal accuracy but also optimizes risk management, distinguishing it from conventional trading methods.
BTCUSD 6hr performance
Disable the visualization of Bull Bear Power (BBP) to clearly view the Z-Score.
█ Strategy, How it Works: Detailed Explanation
The BBP Strategy with Volume-Percentile TP utilizes several interconnected components to analyze market data and generate trading signals. Here's an overview with essential equations:
🔶 Core Indicators and Calculations
1. Exponential Moving Average (EMA):
- **Purpose:** Smoothens price data to identify trends.
- **Formula:**
EMA_t = (Close_t * (2 / (lengthInput + 1))) + (EMA_(t-1) * (1 - (2 / (lengthInput + 1))))
- Usage: Baseline for Bull and Bear Power.
2. Bull and Bear Power:
- Bull Power: `BullPower = High_t - EMA_t`
- Bear Power: `BearPower = Low_t - EMA_t`
- BBP:** `BBP = BullPower + BearPower`
- Interpretation: Positive BBP indicates bullish strength, negative indicates bearish.
3. Z-Score Calculation:
- Purpose: Normalizes BBP to assess deviation from the mean.
- Formula:
Z-Score = (BBP_t - bbp_mean) / bbp_std
- Components:
- `bbp_mean` = SMA of BBP over `zLength` periods.
- `bbp_std` = Standard deviation of BBP over `zLength` periods.
- Usage: Identifies overbought or oversold conditions based on thresholds.
🔶 Volume Analysis
1. Volume Moving Average (`vol_sma`):
vol_sma = (Volume_1 + Volume_2 + ... + Volume_vol_period) / vol_period
2. Volume Multiplier (`vol_mult`):
vol_mult = Current Volume / vol_sma
- Thresholds:
- High Volume: `vol_mult > 2.0`
- Medium Volume: `1.5 < vol_mult ≤ 2.0`
- Low Volume: `1.0 < vol_mult ≤ 1.5`
🔶 Percentile Analysis
1. Percentile Calculation (`calcPercentile`):
Percentile = (Number of values ≤ Current Value / perc_period) * 100
2. Thresholds:
- High Percentile: >90%
- Medium Percentile: >80%
- Low Percentile: >70%
🔶 Dynamic Take-Profit Mechanism
1. ATR-Based Targets:
TP1 Price = Entry Price ± (ATR * atrMult1 * TP_Factor)
TP2 Price = Entry Price ± (ATR * atrMult2 * TP_Factor)
TP3 Price = Entry Price ± (ATR * atrMult3 * TP_Factor)
- ATR Calculation:
ATR_t = (True Range_1 + True Range_2 + ... + True Range_baseAtrLength) / baseAtrLength
2. Adjustment Factors:
TP_Factor = (vol_score + price_score) / 2
- **vol_score** and **price_score** are based on current volume and price percentiles.
Local performance
🔶 Entry and Exit Logic
1. Long Entry: If Z-Score crosses above 1.618, then Enter Long.
2. Short Entry: If Z-Score crosses below -1.618, then Enter Short.
3. Exiting Positions:
If Long and Z-Score crosses below 0:
Exit Long
If Short and Z-Score crosses above 0:
Exit Short
4. Take-Profit Execution:
- Set multiple exit orders at dynamically calculated TP levels based on ATR and adjusted by `TP_Factor`.
█ Trade Direction
The strategy determines trade direction using the Z-Score from the BBP indicator:
- Long Positions:
- Condition: Z-Score crosses above 1.618.
- Short Positions:
- Condition: Z-Score crosses below -1.618.
- Exiting Trades:
- Long Exit: Z-Score drops below 0.
- Short Exit: Z-Score rises above 0.
This approach aligns trades with prevailing market trends, increasing the likelihood of successful outcomes.
█ Usage
Implementing the BBP Strategy with Volume-Percentile TP in TradingView involves:
1. Adding the Strategy:
- Copy the Pine Script code.
- Paste it into TradingView's Pine Editor.
- Save and apply the strategy to your chart.
2. Configuring Settings:
- Adjust parameters like EMA length, Z-Score thresholds, ATR multipliers, volume periods, and percentile settings to match your trading preferences and asset behavior.
3. Backtesting:
- Use TradingView’s backtesting tools to evaluate historical performance.
- Analyze metrics such as profit factor, drawdown, and win rate.
4. Optimization:
- Fine-tune parameters based on backtesting results.
- Test across different assets and timeframes to enhance adaptability.
5. Deployment:
- Apply the strategy in a live trading environment.
- Continuously monitor and adjust settings as market conditions change.
█ Default Settings
The BBP Strategy with Volume-Percentile TP includes default parameters designed for balanced performance across various markets. Understanding these settings and their impact is essential for optimizing strategy performance:
Bull Bear Power Settings:
- EMA Length (`lengthInput`): 21
- **Effect:** Balances sensitivity and trend identification; shorter lengths respond quicker but may generate false signals.
- Z-Score Length (`zLength`): 252
- **Effect:** Long period for stable mean and standard deviation, reducing false signals but less responsive to recent changes.
- Z-Score Threshold (`zThreshold`): 1.618
- **Effect:** Higher threshold filters out weaker signals, focusing on significant market moves.
Take Profit Settings:
- Use Take Profit (`useTP`): Enabled (`true`)
- **Effect:** Activates dynamic profit-taking, enhancing profitability and risk management.
- ATR Period (`baseAtrLength`): 20
- **Effect:** Shorter period for sensitive volatility measurement, allowing tighter profit targets.
- ATR Multipliers:
- **Effect:** Define conservative to aggressive profit targets based on volatility.
- Position Sizes:
- **Effect:** Diversifies profit-taking across multiple levels, balancing risk and reward.
Volume Analysis Settings:
- Volume MA Period (`vol_period`): 100
- **Effect:** Longer period for stable volume average, reducing the impact of short-term spikes.
- Volume Multipliers:
- **Effect:** Determines volume conditions affecting take-profit adjustments.
- Volume Factors:
- **Effect:** Adjusts ATR multipliers based on volume strength.
Percentile Analysis Settings:
- Percentile Period (`perc_period`): 100
- **Effect:** Balances historical context with responsiveness to recent data.
- Percentile Thresholds:
- **Effect:** Defines price and volume percentile levels influencing take-profit adjustments.
- Percentile Factors:
- **Effect:** Modulates ATR multipliers based on price percentile strength.
Impact on Performance:
- EMA Length: Shorter EMAs increase sensitivity but may cause more false signals; longer EMAs provide stability but react slower to market changes.
- Z-Score Parameters:*Longer Z-Score periods create more stable signals, while higher thresholds reduce trade frequency but increase signal reliability.
- ATR Multipliers and Position Sizes: Higher multipliers allow for larger profit targets with increased risk, while diversified position sizes help in securing profits at multiple levels.
- Volume and Percentile Settings: These adjustments ensure that take-profit targets adapt to current market conditions, enhancing flexibility and performance across different volatility environments.
- Commission and Slippage: Accurate settings prevent overestimation of profitability and ensure the strategy remains viable after accounting for trading costs.
Conclusion
The BBP Strategy with Volume-Percentile TP offers a robust framework by combining BBP indicators with volume and percentile analyses. Its dynamic take-profit mechanism, tailored through ATR adjustments, ensures that traders can effectively capture profits while managing risks in varying market conditions.
DAILY Supertrend + EMA Crossover with RSI FilterThis strategy is a technical trading approach that combines multiple indicators—Supertrend, Exponential Moving Averages (EMAs), and the Relative Strength Index (RSI)—to identify and manage trades.
Core Components:
1. Exponential Moving Averages (EMAs):
Two EMAs, one with a shorter period (fast) and one with a longer period (slow), are calculated. The idea is to spot when the faster EMA crosses above or below the slower EMA. A fast EMA crossing above the slow EMA often suggests upward momentum, while crossing below suggests downward momentum.
2. Supertrend Indicator:
The Supertrend uses Average True Range (ATR) to establish dynamic support and resistance lines. These lines shift above or below price depending on the prevailing trend. When price is above the Supertrend line, the trend is considered bullish; when below, it’s considered bearish. This helps ensure that the strategy trades only in the direction of the overall trend rather than against it.
3. RSI Filter:
The RSI measures momentum. It helps avoid buying into markets that are already overbought or selling into markets that are oversold. For example, when going long (buying), the strategy only proceeds if the RSI is not too high, and when going short (selling), it only proceeds if the RSI is not too low. This filter is meant to improve the quality of the trades by reducing the chance of entering right before a reversal.
4. Time Filters:
The strategy only triggers entries during user-specified date and time ranges. This is useful if one wants to limit trading activity to certain trading sessions or periods with higher market liquidity.
5. Risk Management via ATR-based Stops and Targets:
Both stop loss and take profit levels are set as multiples of the ATR. ATR measures volatility, so when volatility is higher, both stops and profit targets adjust to give the trade more breathing room. Conversely, when volatility is low, stops and targets tighten. This dynamic approach helps maintain consistent risk management regardless of market conditions.
Overall Logic Flow:
- First, the market conditions are analyzed through EMAs, Supertrend, and RSI.
- When a buy (long) condition is met—meaning the fast EMA crosses above the slow EMA, the trend is bullish according to Supertrend, and RSI is below the specified “overbought” threshold—the strategy initiates or adds to a long position.
- Similarly, when a sell (short) condition is met—meaning the fast EMA crosses below the slow EMA, the trend is bearish, and RSI is above the specified “oversold” threshold—it initiates or adds to a short position.
- Each position is protected by an automatically calculated stop loss and a take profit level based on ATR multiples.
Intended Result:
By blending trend detection, momentum filtering, and volatility-adjusted risk management, the strategy aims to capture moves in the primary trend direction while avoiding entries at excessively stretched prices. Allowing multiple entries can potentially amplify gains in strong trends but also increases exposure, which traders should consider in their risk management approach.
In essence, this strategy tries to ride established trends as indicated by the Supertrend and EMAs, filter out poor-quality entries using RSI, and dynamically manage trade risk through ATR-based stops and targets.
DemaRSI StrategyThis is a repost to a old script that cant be updated anymore, the request was made on Feb, 27, 2016.
Here's a engaging description for the tradingview script:
**DemaRSI Strategy: A Proven Trading System**
Join thousands of traders who have already experienced the power of this highly effective strategy. The DemaRSI system combines two powerful indicators - DEMA (Double Exponential Moving Average) and RSI (Relative Strength Index) - to generate profitable trades with minimal risk.
**Key Features:**
* **Trend-Following**: Our algorithm identifies strong trends using a combination of DEMA and RSI, allowing you to ride the waves of market momentum.
* **Risk Management**: The system includes built-in stop-loss and take-profit levels, ensuring that your gains are protected and losses are minimized.
* **Session-Based Trading**: Trade during specific sessions only (e.g., London or New York) for even more targeted results.
* **Customizable Settings**: Adjust the length of moving averages, RSI periods, and other parameters to suit your trading style.
**What You'll Get:**
* A comprehensive strategy that can be used with any broker or platform
* Easy-to-use interface with customizable settings
* Real-time performance metrics and backtesting capabilities
**Start Trading Like a Pro Today!**
This script is designed for intermediate to advanced traders who want to take their trading game to the next level. With its robust risk management features, this strategy can help you achieve consistent profits in various market conditions.
**Disclaimer:** This script is not intended as investment advice and should be used at your own discretion. Trading carries inherent risks, and losses are possible.
~Llama3
MicuRobert EMA Cross StrategyThis is a repost of a old strategy that cant be updated anymore, it was a request for a user made in Oct, 6, 2015
Here's a possible engaging description for the tradingview script:
**MicuRobert EMA Cross V2: A Powerful Trading Strategy**
Join the ranks of successful traders with this advanced strategy, designed to help you profit from market trends. The MicuRobert EMA Cross V2 combines two essential indicators - Exponential Moving Average (EMA) and Divergence EMA (DEMA) - to generate buy and sell signals.
**Key Features:**
* **Trading Session Filter**: Only trade during your preferred session, ensuring you're in sync with market conditions.
* **Trailing Stop**: Automatically adjust stop-loss levels to lock in profits or limit losses.
* **Customizable Trade Size**: Set the size of each trade based on your risk tolerance and trading goals.
**How it Works:**
The script uses two EMAs (5-period and 34-period) to identify trends. When the shorter EMA crosses above the longer one, a buy signal is generated. Conversely, when the shorter EMA falls below the longer one, a sell signal is triggered. The strategy also incorporates divergence analysis between price action and the EMAs.
**Visual Aids:**
* **EMA Plots**: Visualize the two EMAs on your chart to gauge market momentum.
* **Buy/Sell Signals**: See when buy or sell signals are generated, along with their corresponding entry prices.
* **Trailing Stop Lines**: Monitor stop-loss levels as they adjust based on price action.
**Get Started:**
Download this script and start trading like a pro! With its robust features and customizable settings, the MicuRobert EMA Cross V2 is an excellent addition to any trader's arsenal.
~Llama3
Gold Friday Anomaly StrategyThis script implements the " Gold Friday Anomaly Strategy ," a well-known historical trading strategy that leverages the gold market's behavior from Thursday evening to Friday close. It is a backtesting-focused strategy designed to assess the historical performance of this pattern. Traders use this anomaly as it captures a recurring market tendency observed over the years.
What It Does:
Entry Condition: The strategy enters a long position at the beginning of the Friday trading session (Thursday evening close) within the defined backtesting period.
Exit Condition: Friday evening close.
Backtesting Controls: Allows users to set custom backtesting periods to evaluate strategy performance over specific date ranges.
Key Features:
Custom Backtest Periods: Easily configurable inputs to set the start and end date of the backtesting range.
Fixed Slippage and Commission Settings: Ensures realistic simulation of trading conditions.
Process Orders on Close: Backtesting is optimized by processing orders at the bar's close.
Important Notes:
Backtesting Only: This script is intended purely for backtesting purposes. Past performance is not indicative of future results.
Live Trading Recommendations: For live trading, it is highly recommended to use limit orders instead of market orders, especially during evening sessions, as market order slippage can be significant.
Default Settings:
Entry size: 10% of equity per trade.
Slippage: 1 tick.
Commission: 0.05% per trade.
