RSI and Smoothed RSI Bull Div Strategy [BigBitsIO]This strategy focuses on finding a low RSI value, then targeting a low Smoothed RSI value while the price is below the low RSI in the lookback period to trigger a buy signal.
Features Take Profit, Stop Loss, and Plot Target inputs. As well as many inputs to manage how the RSI and Smoothed RSI are configured within the strategy.
Explanation of all the inputs
Take Profit %: % change in price from position entry where strategy takes profit
Stop Loss %: % change in price from position entry where strategy stops losses
RSI Lookback Period: # of candles used to calculate RSI
Buy Below Lowest Low In RSI Divergence Lookback Target %: % change in price from lowest RSI candle in divergence lookback if set
Source of Buy Below Target Price: Source of price (close, open, high, low, etc..) used to calculated buy below %
Smoothed RSI Lookback Period: # of candles used to calculate RSI
RSI Currently Below: Value the current RSI must be below to trigger a buy
RSI Divergence Lookback Period: # of candles used to lookback for lowest RSI in the divergence lookback period
RSI Lowest In Divergence Lookback Currently Below: Require the lowest RSI in the divergence lookback to be below this value
RSI Sell Above: If take profit or stop loss is not hit, the position will sell when RSI rises above this value
Minimum SRSI Downtrend Length: Require that the downtrend length of the SRSI be this value or higher to trigger a buy
Smoothed RSI Currently Below: Value the current SRSI must be below to trigger a buy
Cari dalam skrip untuk "Divergence"
Killzones SMT + IFVG detectorKillzones SMT + IFVG Detector
Summary
This strategy implements a specific intraday workflow inspired by ICT-style concepts.
It combines:
Killzone session levels (recording untouched highs/lows)
SMT divergence between NQ and ES (exclusive sweep logic)
IFVG confirmation (3-bar imbalance + width filter + inversion guard)
and an optional smart exit engine
The components are not simply mashed together: they interact in sequence.
A setup only confirms if all conditions line up (time window → untouched level sweep → divergence → valid IFVG → confirmation candle → risk filter).
Workflow
Killzones & session levels
Tracks highs/lows inside default killzones (19:00–23:00, 01:00–04:00, 08:30–10:00, 11:00–12:00, 12:30–15:00, chart timezone).
Stores untouched levels forward; sweeps trigger candidate signals.
SMT divergence (exclusive sweep)
Bullish SMT : one index sweeps its low while the other remains above its session low.
Bearish SMT : one index sweeps its high while the other remains below its session high.
Detection supports “Sweep (Cross)” or “Exact Tick.”
Session IDs are tracked so once a side has fired, later re-touches can’t re-trigger .
IFVG confirmation
Locks the first valid 3-bar IFVG after SMT.
Confirmation requires a candle close beyond the IFVG boundary in the direction of the close.
IFVGs must meet a minimum width filter (default 1.0 point).
Inversion guard: ignores IFVGs already inverted before SMT.
Optional “re-lock” keeps tracking the latest IFVG until confirmation/expiry.
Smart exit engine
Initial stop from opposite wick (+ buffer).
Fixed TP (default 40 points).
Dynamic stop escalation at progress thresholds (BE → 50% → 80% of target).
Safety gates
Weekend lockout (Fri 16:40 → Sun 18:00).
Same-bar sweep of high & low cancels setups.
Max initial stop filter skips oversized setups.
Optional cooldown bars.
Alerts
SMT Bullish/Bearish : divergence detected this bar.
Confirm Long/Short : IFVG confirmation triggered.
Default Strategy Properties (used in screenshots/backtests)
Initial capital: $25,000
Order size: 1 contract
Commission: $1.25 per contract per side
Slippage: 2 ticks
Backtest window: Jun 16, 2025 – Sep 14, 2025
These settings are intentionally conservative. If you change them, your results will differ.
How to use
Apply on an NQ or ES futures chart (1–5 min).
Choose your killzones and detection mode.
Select confirmation symbol (NQ, ES, or “Sweeper”).
Enable/disable IFVG re-lock.
Review signals and use alerts for automation if desired.
Limitations
Strict filters reduce trade count; extend backtest window for more samples.
Works best on NQ/ES; not validated elsewhere.
Past performance is not indicative of future results.
This is an educational tool ; not financial advice.
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.
TENKAN BOLTTENKAN BOLT
7 major point in this indicator are as follows :-
•Tenkan-sen
•Ichimoku Cloud
•Exponential Moving Average
•Change of Volume Analysis (calculated in background)
•Modified Keltner Channel (calculated in background)
•RSI Divergence (calculated in background)
•Entry and Exit Point
www.tradingview.com
There will be 2 types of Long entry alert and 2 types of Short entry alert.
•The first one is marked as "Long" or "Short" only which indicates the signal calculated by Keltner Channel, Tenkan-sen and change of volume in sudden time.
•The second one is marked as "Long Divergence" and "Short Divergence" which indicates signal by RSI Divergence in my own way (not aggressive).
The idea of this script is only trade the highest probability setup and I shall call it the "High Probability, Probability Trading". This is definitely not a buy or sell call as the idea of the script is to give a good direction for trader and to learn the high probability trading setup which includes the volatility of the market.
This script specifically created for Futures Crude Palm OIL (FCPO) market and may works differently in different market. It works great in 1 minute time-frame and 3 minute time-frame
(with slight adjustment).
Kindly contact me for usage. Thanks!
Scalper Helper System===========================================================================
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Description
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Scalper Helper System combines a series of trade strategies which have been learned and honed in the Jim of All Trades channel.
Paixy has contributed candlestick combination rules, Jonas has shared his deep understanding of Stochastic.
Jim himself has taught clearly on the merits of RSI.
This system attempts to formulate all the notes and rules I have made over the past months.
The system searches for 10 - 15 rules which are divided into bullets and bombs. Bombs relate to momentum, so these signals may not be pinpoint accurate, but they are more often leading to bigger moves.
This initial version is released mainly only to the JOAT community to help continue the development of the idea and to help find
continued improvements.
Special thanks to FiendishFeather for his strategy work, (check out his work to learn how to apply any trading strategy to his back testing harness), and the date filtering snippet and the tip to show this option at the top.
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The strategy decisions are based on the following general rules:
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BULLETs are hint to the idea of firing a small sized position into the market, BOMBs are hints to go all in - however this does not mean proper risk management should be forgotten.
Without risk management this and any strategy will lead to failure.
Without risk management this and any strategy will lead to failure.
Without risk management this and any strategy will lead to failure.
Without risk management this and any strategy will lead to failure.
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Bullet1 uses the value of the stochastic and checks for buy/sell cross over on 5m, 8m and 13m chart.
These values should be calculated on a ratio basis ideally.
Bullet2 measures divergence between the printed Stochastic signals.
Bullet3 has been decommissioned.
Bullet4 is an RSI divergence and value indicator.
Bullet5 has been decommissioned.
Bullet6 uses the history of the stochastic buy and sell signals
Bullet7 uses the Scalper Helper Trends for entries by attempting to see how the overall trend is changing. More refinement is needed here.
Bullet8 uses the Scalper Helper Trends on multiple timeframes for entries.
Bullet9 strict buy/sell signals from Stochastic RSI
Bomb1 relies on the Fast, Medium and Slow MA's being correctly lined up as well as the Stochastic, this hints at a more imminent move and so the strategy suggests a quicker entry.
Bomb2 relies on the Fast, Medium and Slow MA's NOT being correctly lined up as well as the Stochastic, and therefore has the luxury of suggesting Limit orders near the local high/low.
Bomb3 looks for two or more Stochastics signals in the same direction and then performs a divergence calculation.
Bomb4 looks a change in the Stochastics signals direction and then performs a divergence calculation.
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Configuration settings:
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Users can chose to show mainly buy and/or sell signals and can select a level of strictness. Enabling strict rules will force a multi timeframe comparison of Stochastic analysis.
Users can try different levels for long and short targets for profit and stop loss. This is important because the market does not behave the same going up as it does going down.
The RSI conditional check makes the strategy more selective. This discernment can be applied to bullets or bombs in order to validate entry and exits.
During the bull run and perhaps even in ranging markets, the RSI overbought levels is usually 70-80, but in the bear market we are seeing in Crypto now, a value of 60 is more useful. Try for yourself to see what works for you and feedback in the comments.
An additional indicator, Scalper Helper Trends is recommended to get a quick view on the trend condition (rally, base, down) by viewing the MACD from multiple time frames. Further research is required to know which larger timeframes work best here.
For the 15min chart, 15m, 30m, 45m, 60m, 120m, 240m, 360m, 960m would work well. Note it is not possible to go higher than 1000 at this time.
Whether you use the Scalper Helper trends or not for your own visual confirmation, it is possible to allow this indicator to attempt to read it for you. More research is required to best model the reading of this. For now, it will simply measure the gradient of the number of up versus down colors.
The system can also find entries off the Scalper Helper Trends - but really this, by design is not the best use of Scalper Helper Trends. Although you may prove me wrong so the option is given for you to find buy/sells with your own testing.
Users can chose to use some engulfing candle arrangements to trigger exits and define the length of the 200MA and decide if this should play a part in the filtering of the signals. Similarly, a check can be made to ensure that the first two candles after a signal are behaving as we would expect with the "Wait for 2 closing in the direction of the signal" option. This has a lot of value on the 1min chart.
When Revenge trade is set to true you may re-enter a trade in the same direction as the last one when the last one was stopped out, otherwise you would only be looking for trades in the other direction. We all should not revenge trade, and indeed I have only seen a few cases when it has increased the profitability, however this option remains for now.
The flip opens a new trade in the reverse direction when a signal is given to close a trade, but does not apply to scenarios where stop losses or take profit closed the trade.
[strategy] XBT Stable Max Profit Swing StrategyTrend following strategy indicators through trend analysis.
Minimized loss trading when the price is going sideway, which is a disadvantage of the trend following strategy.
Optimized for XBTUSD 4H.
This indicator is never repainted like other fake indicators.
For replaying to check this indicator repaints or not,
2-day trial period is provided.
* description about the setting factors
- A factors (trend detecting lengths)
A-Factor1: short term checking period
A-Factor2: mid term checking period
A-Factor3: long term checking period
- B factors (factors of detecting trend changing)
B-Factor1: determine detection of trend changing periods
B-Factors2: strength on short trend changing
B-Factors3: strength on long trend changing
- C factors (detecting divergence factors)
C-Factor1: total long divergence value for detecting long signal
C-Factor2: numeric value of each long divergence
C-Factor3:total short divergence value for detecting short signal
C-Factor4:numeric value of each short divergence
* The default setting is recommended, but it is also possible to optimize by setting the details of the three category settings.
(Trade points of settings A, B, and C factors are displayed in the transaction history to help tuning)
* For detailed backtesting, a backtesting period can be set.
* Note: Backtesting results do not guarantee future results.
* This indicator is an invite only indicator.
* If you want to use this indicator, contact with my information below.
Ghost Robo [Bit2Billions]Ghost Robo — Automated Gap-Based Trading System
*An intelligent, fully automated trading strategy designed to identify high-probability opportunities using fair-value gaps, volume, and price action—without adding clutter to your chart.*
Ghost Robo combines gap detection, volume analysis, and smart entry logic into a single, streamlined system. It executes trades cleanly while offering backtesting, position sizing, alerts, and risk management—all internally. The strategy is engineered to maximize precision and reduce noise, giving traders an actionable, automated trading workflow.
Key Features
1. Automatic Gap Analysis
* Detects bullish and bearish fair-value gaps internally for trade logic.
* Evaluates gap “fill” percentages against configurable thresholds for high-probability entries.
2. Volume-Based Decision Making
* Integrates buying and selling activity to assess the strength of each gap.
* Filters trades based on real-time volume analysis for reliable execution.
3. Smart Entry Rules
* Trades are triggered automatically based on gap characteristics, candle confirmation, and user-defined thresholds.
* Queue management and deduplication avoid repeated trades on the same opportunity.
4. Flexible Filters
* Conditions include volume, bull/bear balance, gap age, and candle patterns.
* Allows traders to tune the strategy for their preferred market conditions.
5. Built-in Risk Management
* Stop-loss enforcement, optional trailing stops, and single-position restrictions.
* Ensures disciplined execution and controlled risk exposure.
6. Clean, No-Visual Execution
* All gap detection and calculations occur internally; charts remain uncluttered.
* Ideal for traders who prefer automated logic without additional chart overlays.
What Ghost Robo Solves
* Automates gap-based trading strategies with precision.
* Ensures disciplined entries using multiple filters and predictive gap logic.
* Reduces repeated trades and focuses on high-quality opportunities.
* Provides a complete system for backtesting, alerts, and position management.
Recommended Timeframes & Markets
* Timeframes: 15m and higher (15m, 1H, 4H, Daily). Works on intraday but benefits from higher timeframe structure.
* Markets: Liquid FX pairs, major crypto, indices, and liquid equities.
* Notes: For illiquid instruments, tighten volume filters or use higher timeframes for cleaner signals.
Inputs & Settings
* Default settings pre-configured
* Simple Show/Hide toggles for modules
* Minimal exposed fields for ease of use
Recommended Timeframes & Markets
* Works best on 15M, 1H, 4H, Daily, and higher
* Suitable across forex, crypto, indices, and liquid equities
* Pivot-based modules may show noise on illiquid assets
Performance & Limitations
* May draw many objects → disable unused modules for speed
* Refresh the chart if historical buffer issues occur
* TradingView platform limitations handled internally
License & Legal
* Proprietary © 2025
* Redistribution, resale, or disclosure prohibited
* Independently developed with proprietary extensions
* Any resemblance to other tools may result from public-domain concepts
Respect & Transparency
* Built on widely recognized public trading concepts.
* Developed with respect for the TradingView community.
* Any overlaps or similarities can be addressed constructively.
Disclaimer
* Educational purposes only
* Not financial advice
* Trading carries risk — always use paper testing and proper risk management
FAQs
* Source code is not public
* Works best on 15m, 1H, 4H, Daily, Weekly charts
* Modules can be hidden/shown with toggles
* Alerts can be set up manually by users
* Supports multiple markets: forex, crypto, indices, and equities
About Ghost Trading Suite
Author: BIT2BILLIONS
Project: Ghost Trading Suite © 2025
Indicators: Ghost Matrix, Ghost Protocol, Ghost Cipher, Ghost Shadow
Strategies: Ghost Robo, Ghost Robo Plus
Pine Version: V6
The Ghost Trading Suite is designed to simplify and automate many aspects of chart analysis. It helps traders identify market structure, divergences, support and resistance levels, and momentum efficiently, reducing manual charting time.
The suite includes several integrated tools — such as Ghost Matrix, Ghost Protocol, Ghost Cipher, Ghost Shadow, Ghost Robo, and Ghost Robo Plus — each combining analytical modules for enhanced clarity in trend direction, volatility, pivot detection, and momentum tracking.
Together, these tools form a cohesive framework that assists in visualizing market behavior, measuring momentum, detecting pivots, and analyzing price structure effectively.
This project focuses on providing adaptable and professional-grade tools that turn complex market data into clear, actionable insights for technical analysis.
Crafted with 💖 by BIT2BILLIONS for Traders. That's All Folks!
Changelog
v1.0 – Core Release
* Introduced fully automated gap-based strategy using fair-value gaps (FVGs) for trade logic.
* Added internal volume analysis to evaluate bullish/bearish strength for each gap.
* Implemented smart entry triggers based on gap “fill” percentages.
* Added configurable filters for volume, bull/bear balance, age of gap, candle confirmation, and cooldown between trades.
* Introduced queue management & deduplication, ensuring only the most relevant gaps are traded and repeated entries are avoided.
* Implemented risk management features, including percentage stop-loss, optional trailing stops, and single-position enforcement.
* Fully non-visual execution, keeping charts clean while all gap detection and trade calculations happen internally.
* Enabled backtesting, position sizing, and alert creation for complete strategy management.
Ghost Robo Plus [Bit2Billions]Ghost Robo Plus — Rule-Based Trade Management System
*An advanced, rule-based trading strategy for structured entries, exits, and complete trade management using Heikin-Ashi logic.*
Ghost Robo Plus simplifies trade execution by automating entry, stop-loss, and multiple take-profit levels, all visualized cleanly on your chart. It supports position sizing, backtesting, alerts, and real-time trade tracking, making it easy for traders to test strategies, validate ideas, and follow trades without chart clutter.
Key Features
1. Heikin-Ashi Entry System
* Generates clear long/short signals based on Heikin-Ashi candle crossovers.
* Structured entry logic ensures precise timing aligned with trend direction.
2. Multiple Exit Modes (Switch Anytime)
* ATR Mode: TP1/TP2/TP3 and SL based on ATR distance calculations.
* Trailing Mode: Dynamic trailing logic for trend-following continuation.
* Options Mode: Original options-style behavior preserved for flexible testing.
3. Multi–Take-Profit Structure
* Three configurable take-profit levels (TP1, TP2, TP3) with adjustable percentage splits.
* Enables partial profit-taking with structured scaling.
4. ATR-Based Calculations
* All TP and SL levels are derived from ATR length, profit factors, and stop factors.
* Volatility-adjusted trade placement ensures adaptive risk/reward.
5. Visual Trade Manager
* Automatically draws Entry, Stop Loss, and TP lines directly on chart.
* Includes on-chart labels for Entry, SL, TP, and mini entry/exit markers.
* Visuals update automatically per trade, removing clutter or leftover objects.
6. Alerts
* Built-in alerts for:
* Long entry
* Short entry
* TP/SL exits
* Any trade event (unified alert option)
7. Position Sizing & Commission Support
* Percent-of-equity sizing (10% default, fully adjustable).
* Supports TradingView strategy commission settings for realistic backtesting.
What Ghost Robo Plus Solves
* Automates TP/SL drawings and scaling for faster analysis.
* Lets traders test multiple exit styles without rewriting logic.
* Ensures clear, consistent on-chart visualization for every trade.
* Provides a structured workflow for backtesting and strategy validation.
* Eliminates chart clutter with synchronized, auto-updating visual elements.
Inputs & High-Level Settings
* TPS Mode: ATR / Trailing / Options
* Risk Settings: ATR length, profit factor, stop factor
* TP Splits: Adjustable TP1/TP2/TP3 percentages
* Position Sizing: Percent of equity (default 10%)
* Visual Controls: Auto-managed lines & labels
* Alerts: Entry/exit event triggers
Recommended Timeframes & Markets
* Recommended starting timeframes: 15m and higher (15m, 1H, 4H, Daily). Works on intraday but benefits from cleaner HTF structure.
* Suitable for liquid FX pairs, major crypto, indices and liquid equities.
* On illiquid or low-volume instruments, the volume-split and total-volume filters should be tightened, or higher timeframes should be used.
What Ghost Suite Solves
* Helps reduce manual charting work
* Speeds up analysis with automated visual tools
* Cuts through chart noise for improved clarity
* Provides consistent, rule-based visualization for workflows
Inputs & Settings
* Default settings pre-configured
* Simple Show/Hide toggles for modules
* Minimal exposed fields for ease of use
Recommended Timeframes & Markets
* Works best on 15M, 1H, 4H, Daily, and higher
* Suitable across forex, crypto, indices, and liquid equities
* Pivot-based modules may show noise on illiquid assets
Performance & Limitations
* May draw many objects → disable unused modules for speed
* Refresh the chart if historical buffer issues occur
* TradingView platform limitations handled internally
License & Legal
* Proprietary © 2025
* Redistribution, resale, or disclosure prohibited
* Independently developed with proprietary extensions
* Any resemblance to other tools may result from public-domain concepts
Respect & Transparency
* Built on widely recognized public trading concepts.
* Developed with respect for the TradingView community.
* Any overlaps or similarities can be addressed constructively.
Disclaimer
* Educational purposes only
* Not financial advice
* Trading carries risk — always use paper testing and proper risk management
FAQs
* Source code is not public
* Works best on 15m, 1H, 4H, Daily, Weekly charts
* Modules can be hidden/shown with toggles
* Alerts can be set up manually by users
* Supports multiple markets: forex, crypto, indices, and equities
About Ghost Trading Suite
Author: BIT2BILLIONS
Project: Ghost Trading Suite © 2025
Indicators: Ghost Matrix, Ghost Protocol, Ghost Cipher, Ghost Shadow
Strategies: Ghost Robo, Ghost Robo Plus
Pine Version: V6
The Ghost Trading Suite is designed to simplify and automate many aspects of chart analysis. It helps traders identify market structure, divergences, support and resistance levels, and momentum efficiently, reducing manual charting time.
The suite includes several integrated tools — such as Ghost Matrix, Ghost Protocol, Ghost Cipher, Ghost Shadow, Ghost Robo, and Ghost Robo Plus — each combining analytical modules for enhanced clarity in trend direction, volatility, pivot detection, and momentum tracking.
Together, these tools form a cohesive framework that assists in visualizing market behavior, measuring momentum, detecting pivots, and analyzing price structure effectively.
This project focuses on providing adaptable and professional-grade tools that turn complex market data into clear, actionable insights for technical analysis.
Crafted with 💖 by BIT2BILLIONS for Traders. That's All Folks!
Changelog
v1.0 — Initial Release
* Added Heikin-Ashi–based long/short entry system.
* Introduced three exit modes: ATR, Trailing, and Options.
* Added full multi-TP support with configurable TP1/TP2/TP3 quantities.
* Implemented ATR-based TP/SL calculations for ATR mode.
* Added on-chart visuals for Entry, SL, and TP levels with dynamic cleanup.
* Introduced queue-safe line/label manager to avoid object clutter.
* Added alerts for entries, exits, and general signals.
* Enabled position sizing, backtesting, and commission settings.
* Polished internal logic with a clean, auditable structure for reliability.
nOI + Funding + CVD • strategynOI + Funding + CVD Strategy
Overview
This strategy is designed for cryptocurrency trading on platforms like TradingView, focusing on perpetual futures markets. It combines three key indicators—Normalized Open Interest (nOI), Funding Rate, and Cumulative Volume Delta (CVD)—to generate buy and sell signals for long and short positions. The strategy aims to capitalize on market imbalances, such as overextended open interest, funding rate extremes, and volume deltas, which often signal potential reversals or continuations in trending markets.
The script supports pyramiding (up to 10 positions), uses percentage-based position sizing (default 10% of equity per trade), and allows customization of trade directions (longs and shorts can be enabled/disabled independently). It includes multiple signal systems for entries, various exit mechanisms (including stop-loss, take-profit, time-based exits, and conditional closes based on indicators), a Martingale add-on system for averaging positions during drawdowns, and handling of opposite signals (ignore, close, or reverse).
This strategy is not financial advice; backtest thoroughly and use at your own risk. It requires data sources for Open Interest (OI) and Funding Rates, which are fetched via TradingView's security functions (e.g., from Binance for funding premiums).
Key Indicators
1. Normalized Open Interest (nOI)
Group: Open Interest
Purpose: Measures the relative level of open interest over a lookback window to identify overbought (high OI) or oversold (low OI) conditions, which can indicate potential exhaustion in trends.
Calculation:
Fetches OI data (close) from the symbol's standard ticker (e.g., "{symbol}_OI").
Normalizes OI within a user-defined window (default: 500 bars) using min-max scaling: (OI - min_OI) / (max_OI - min_OI) * 100.
Upper threshold (default: 70%): Signals potential short opportunities when crossed from above.
Lower threshold (default: 30%): Signals potential long opportunities when crossed from below.
Visualization: Plotted as a line (teal above upper, red below lower, gray in between). Horizontal lines at upper, mid (50%), lower, and a separator at 102%.
Notes: Handles non-crypto symbols by adjusting timeframe to daily if intraday. Errors if no OI data available.
2. Funding Rate
Group: Funding Rate
Purpose: Tracks the average funding rate (premium index) to detect market sentiment extremes. Positive funding suggests bull bias (longs pay shorts), negative suggests bear bias.
Calculation:
Fetches premium index data from Binance (e.g., "binance:{base}usdt_premium").
Supports lower timeframe aggregation (default: enabled, using 1-min TF) for smoother data.
Averages open and close premiums, clamps values, and scales/shifts for plotting (base: 150, scale: 1000x).
Upper threshold (default: 1.0%): Overheat for shorts.
Lower threshold (default: 1.0%): Overcool for longs.
Ultra level (default: 1.8%): Extreme for additional short signals.
Smoothing: Uses inverse weighted moving average (IWMA) or lower-TF aggregation to reduce noise.
Visualization: Shifted plot (green positive, red negative) with filled areas. Horizontal lines for overheat, overcool, base (0%), and ultra.
Notes: Custom ticker option for non-standard symbols.
3. Cumulative Volume Delta (CVD)
Group: CVD (Cumulative Volume Delta)
Purpose: Measures net buying/selling pressure via volume delta, normalized to identify divergences or confirmations with price.
Calculation:
Delta: +volume if close > open, -volume if close < open.
Cumulative: Rolling cumsum over a window (default: 500 bars), smoothed with EMA (default: 20).
Normalized: Scaled by absolute max in window (-1 to 1 range).
Scaled/shifted for plotting (base: 300 or 0 if anchored, scale: 120x).
Upper threshold (default: 1.0%): Over for shorts.
Lower threshold (default: 1.0%): Under for longs.
Visualization: Shifted plot (aqua positive, purple negative) with filled areas. Horizontal lines for over, under, and separator (default: 252).
Filter Options (for Signal A):
Enable filter (default: false).
Require sign match (Long ≥0, Short ≤0).
Require extreme zones.
Require momentum (rising/falling over N bars, default: 3).
Signal Logics for Entries
Entries are triggered by buy/sell signals from multiple systems (A, B, C, D), filtered by direction toggles and entry conditions.
Signal System A: OI + Funding (with optional CVD filter)
Enabled: Default true.
Sell (Short): nOI > upper threshold, falling over N bars (default: 3), delta ≥ threshold (default: 3%), funding > overheat, and CVD filter OK.
Buy (Long): nOI < lower threshold, rising over N bars (default: 3), delta ≥ threshold (default: 3%), funding < overcool, and CVD filter OK.
Signal System B: Short - Funding Crossunder + Filters
Enabled: Default true.
Sell (Short): Funding crosses under overheat level, optional: CVD > over, nOI < upper.
Signal System C: Short - Ultra Funding
Enabled: Default false.
Sell (Short): Funding crosses ultra level (up or down, both default true).
Signal System D: Long - Funding Crossover + Filters
Enabled: Default true.
Buy (Long): Funding crosses over overcool level, optional: CVD < under, nOI > lower.
Combined: Sell if A/B/C active; Buy if A/D active.
Entry Filters
Cooldown: Optional pause between entries (default: false, 3 bars).
Max Entries: Limit pyramiding (default: true, 6 max).
Entries only if both filters pass and direction allowed.
Opposite Signal Handling
Mode: Ignore (default), Reverse (close and enter opposite), or Close (exit only).
Processed before regular entries.
Position Management
Martingale (3 Steps):
Enabled per step (default: all true).
Triggers add-ons at loss levels (defaults: 5%, 8%, 11%) by adding % to position (default: 100% each).
Resets on position close.
Break Even:
Enabled (default: true).
Activates at profit threshold (default: 5%), sets SL better by offset (default: 0.1%).
Exit Systems
Multiple exits checked in sequence.
Exit 1: SL/TP
Enabled: Separate for long/short (default: true).
SL: % from avg price (defaults: 1% long/short).
TP: % from avg price (defaults: 2% long/short).
Exit 2: Funding
Enabled: Separate for long (up) / short (down) (default: true).
Long Exit: Funding > upper exit threshold (default: 0.8%).
Short Exit: Funding < lower exit threshold (default: 0.8%).
Exit 3: nOI
Enabled: Separate for long (up) / short (down) (default: true).
Long Exit: nOI > upper exit (default: 85%).
Short Exit: nOI < lower exit (default: 15%).
Exit 4: Global SL
Enabled: Default true.
Exit: If position loss ≥ % (default: 7%).
Exit 5: Break Even (integrated in position block)
Exit 6: Time Limit
Enabled: Separate for long/short (default: true).
Exit: After N bars in trade (defaults: 30 each).
Timer updates on add-ons if enabled (default: true).
Visual Elements
Buy/Sell Labels: Small labels ("BUY"/"SELL") on bars with signals, limited to last 30.
All indicators plotted on a separate pane (overlay=false).
Usage Notes
Backtesting: Adjust parameters based on asset/timeframe. Test on historical data.
Data Requirements: Works best on crypto perps with OI and funding data.
Risk Management: Incorporates SL/TP and global SL; monitor drawdowns with Martingale.
Customization: All thresholds, enables, and scales are inputs for fine-tuning.
Version: Pine Script v6.
For questions or improvements, contact the author. Happy trading!
Yuri Garcia Smart Money Strategy FULL (COMPLIANT)Yuri Garcia Smart Money Strategy FULL (Slope Divergence)
This script is not a mashup of random indicators. It is an original, coherent strategy that blends multiple institutional-grade tools to form a unified Smart Money trading system. Each component contributes to precise trade filtering, context, and confirmation — no element is decorative or redundant.
🔍 Strategy Logic: How It Works
This strategy integrates the following tools, each with a clearly defined role:
1. Volume Cluster Zones (Orange bands)
Identifies strong buy/sell areas using the highest volume nodes over a rolling window. These act as dynamic points of control where Smart Money is likely active.
2. HTF Zones (4H) (Purple band)
Defines institutional zones by using the 20-bar high/low on the 4-hour chart. These set the outer bounds for valid entries, ensuring alignment with larger market structure.
3. Wick Pullback Filter (Orange circle 🔶)
Detects exhaustion or absorption near zones. Used to confirm genuine rejection after liquidity sweeps or traps.
4. Cumulative Delta Confirmation (Red square 🟥)
Analyzes whether buyers or sellers are dominant using delta volume. Trades only trigger when volume confirms the intended direction.
5. Slope-Based Delta Divergence (Optional)
Detects hidden reversals between price and delta. This prevents late entries and provides early insight into potential trap reversals.
6. Liquidity Grab Detection (Blue diamond 🔷)
Marks smart money stop hunts — temporary price breaks beyond highs/lows, followed by reversal. Used as a confluence tool.
7. ATR-Based Dynamic Risk Control
The strategy uses ATR to calculate SL/TP dynamically. This allows position sizing to adjust to volatility, reducing overexposure in high-momentum conditions.
🎯 Entry Criteria
All the following conditions must be met:
✅ Price is inside a Volume Cluster Zone
✅ Price is within the HTF Institutional Zone
✅ Wick Pullback confirms reaction
✅ Delta confirms strength of buyers/sellers
✅ (Optional) Slope-based divergence signals hidden shift
✅ (Optional) Liquidity grab occurs
Only then will the strategy trigger an entry.
📈 Visual Legend (Symbols on Chart)
Symbol Description
🟣 Purple Zone HTF Support/Resistance zone (4H context)
🟠 Orange Zone Volume cluster from top 3 volume nodes
🔶 Orange Circle Wick Pullback confirmation
🟥 Red Square Delta Confirmation
🔷 Blue Diamond Liquidity Grab indicator
🔵 Blue X Price is inside HTF Zone
🔻 Red Triangle SHORT entry signal
🔺 Green Triangle LONG entry signal
These visuals make it easier to read the chart intuitively while understanding each condition’s role.
⚙️ Strategy Settings Justification
Default Qty: 2% of equity (sustainable risk)
RRR: 2.0 (adaptive to volatility)
ATR Multiplier: 2.0 for SL/TP
Commission: 0.1% used
Slippage: 2 points for realism
Minimum Trades for Testing: Designed to generate over 100 trades under normal backtest conditions
Dataset: Supports BTC, GOLD, Forex, Indices with realistic volatility and volume
These settings reflect a realistic use case for average retail traders and avoid overfitting or unrealistic returns.
📌 How to Use
Apply on 15-minute or 1-hour timeframe.
Wait for full alignment of all entry conditions.
Confirm visually or use included alerts for manual or bot execution.
SL and TP are automatically handled.
🚫 Important Notes
This script is original, not a remix or mashup of unrelated indicators.
Each component was designed to work in harmony, enhancing trade quality and confidence.
No external scripts are required to function.
Alert messages are pre-formatted for both manual and webhook use.
Bober XM v2.0# ₿ober XM v2.0 Trading Bot Documentation
**Developer's Note**: While our previous Bot 1.3.1 was removed due to guideline violations, this setback only fueled our determination to create something even better. Rising from this challenge, Bober XM 2.0 emerges not just as an update, but as a complete reimagining with multi-timeframe analysis, enhanced filters, and superior adaptability. This adversity pushed us to innovate further and deliver a strategy that's smarter, more agile, and more powerful than ever before. Challenges create opportunity - welcome to Cryptobeat's finest work yet.
## !!!!You need to tune it for your own pair and timeframe and retune it periodicaly!!!!!
## Overview
The ₿ober XM v2.0 is an advanced dual-channel trading bot with multi-timeframe analysis capabilities. It integrates multiple technical indicators, customizable risk management, and advanced order execution via webhook for automated trading. The bot's distinctive feature is its separate channel systems for long and short positions, allowing for asymmetric trade strategies that adapt to different market conditions across multiple timeframes.
### Key Features
- **Multi-Timeframe Analysis**: Analyze price data across multiple timeframes simultaneously
- **Dual Channel System**: Separate parameter sets for long and short positions
- **Advanced Entry Filters**: RSI, Volatility, Volume, Bollinger Bands, and KEMAD filters
- **Machine Learning Moving Average**: Adaptive prediction-based channels
- **Multiple Entry Strategies**: Breakout, Pullback, and Mean Reversion modes
- **Risk Management**: Customizable stop-loss, take-profit, and trailing stop settings
- **Webhook Integration**: Compatible with external trading bots and platforms
### Strategy Components
| Component | Description |
|---------|-------------|
| **Dual Channel Trading** | Uses either Keltner Channels or Machine Learning Moving Average (MLMA) with separate settings for long and short positions |
| **MLMA Implementation** | Machine learning algorithm that predicts future price movements and creates adaptive bands |
| **Pivot Point SuperTrend** | Trend identification and confirmation system based on pivot points |
| **Three Entry Strategies** | Choose between Breakout, Pullback, or Mean Reversion approaches |
| **Advanced Filter System** | Multiple customizable filters with multi-timeframe support to avoid false signals |
| **Custom Exit Logic** | Exits based on OBV crossover of its moving average combined with pivot trend changes |
### Note for Novice Users
This is a fully featured real trading bot and can be tweaked for any ticker — SOL is just an example. It follows this structure:
1. **Indicator** – gives the initial signal
2. **Entry strategy** – decides when to open a trade
3. **Exit strategy** – defines when to close it
4. **Trend confirmation** – ensures the trade follows the market direction
5. **Filters** – cuts out noise and avoids weak setups
6. **Risk management** – controls losses and protects your capital
To tune it for a different pair, you'll need to start from scratch:
1. Select the timeframe (candle size)
2. Turn off all filters and trend entry/exit confirmations
3. Choose a channel type, channel source and entry strategy
4. Adjust risk parameters
5. Tune long and short settings for the channel
6. Fine-tune the Pivot Point Supertrend and Main Exit condition OBV
This will generate a lot of signals and activity on the chart. Your next task is to find the right combination of filters and settings to reduce noise and tune it for profitability.
### Default Strategy values
Default values are tuned for: Symbol BITGET:SOLUSDT.P 5min candle
Filters are off by default: Try to play with it to understand how it works
## Configuration Guide
### General Settings
| Setting | Description | Default Value |
|---------|-------------|---------------|
| **Long Positions** | Enable or disable long trades | Enabled |
| **Short Positions** | Enable or disable short trades | Enabled |
| **Risk/Reward Area** | Visual display of stop-loss and take-profit zones | Enabled |
| **Long Entry Source** | Price data used for long entry signals | hl2 (High+Low/2) |
| **Short Entry Source** | Price data used for short entry signals | hl2 (High+Low/2) |
The bot allows you to trade long positions, short positions, or both simultaneously. Each direction has its own set of parameters, allowing for fine-tuned strategies that recognize the asymmetric nature of market movements.
### Multi-Timeframe Settings
1. **Enable Multi-Timeframe Analysis**: Toggle 'Enable Multi-Timeframe Analysis' in the Multi-Timeframe Settings section
2. **Configure Timeframes**: Set appropriate higher timeframes based on your trading style:
- Timeframe 1: Default is now 15 minutes (intraday confirmation)
- Timeframe 2: Default is 4 hours (trend direction)
3. **Select Sources per Indicator**: For each indicator (RSI, KEMAD, Volume, etc.), choose:
- The desired timeframe (current, mtf1, or mtf2)
- The appropriate price type (open, high, low, close, hl2, hlc3, ohlc4)
### Entry Strategies
- **Breakout**: Enter when price breaks above/below the channel
- **Pullback**: Enter when price pulls back to the channel
- **Mean Reversion**: Enter when price is extended from the channel
You can enable different strategies for long and short positions.
### Core Components
### Risk Management
- **Position Size**: Control risk with percentage-based position sizing
- **Stop Loss Options**:
- Fixed: Set a specific price or percentage from entry
- ATR-based: Dynamic stop-loss based on market volatility
- Swing: Uses recent swing high/low points
- **Take Profit**: Multiple targets with percentage allocation
- **Trailing Stop**: Dynamic stop that follows price movement
## Advanced Usage Strategies
### Moving Average Type Selection Guide
- **SMA**: More stable in choppy markets, good for higher timeframes
- **EMA/WMA**: More responsive to recent price changes, better for entry signals
- **VWMA**: Adds volume weighting for stronger trends, use with Volume filter
- **HMA**: Balance between responsiveness and noise reduction, good for volatile markets
### Multi-Timeframe Strategy Approaches
- **Trend Confirmation**: Use higher timeframe RSI (mtf2) for overall trend, current timeframe for entries
- **Entry Precision**: Use KEMAD on current timeframe with volume filter on mtf1
- **False Signal Reduction**: Apply RSI filter on mtf1 with strict KEMAD settings
### Market Condition Optimization
| Market Condition | Recommended Settings |
|------------------|----------------------|
| **Trending** | Use Breakout strategy with KEMAD filter on higher timeframe |
| **Ranging** | Use Mean Reversion with strict RSI filter (mtf1) |
| **Volatile** | Increase ATR multipliers, use HMA for moving averages |
| **Low Volatility** | Decrease noise parameters, use pullback strategy |
## Webhook Integration
The strategy features a professional webhook system that allows direct connectivity to your exchange or trading platform of choice through third-party services like 3commas, Alertatron, or Autoview.
The webhook payload includes all necessary parameters for automated execution:
- Entry price and direction
- Stop loss and take profit levels
- Position size
- Custom identifier for webhook routing
## Performance Optimization Tips
1. **Start with Defaults**: Begin with the default settings for your timeframe before customizing
2. **Adjust One Component at a Time**: Make incremental changes and test the impact
3. **Match MA Types to Market Conditions**: Use appropriate moving average types based on the Market Condition Optimization table
4. **Timeframe Synergy**: Create logical relationships between timeframes (e.g., 5min chart with 15min and 4h higher timeframes)
5. **Periodic Retuning**: Markets evolve - regularly review and adjust parameters
## Common Setups
### Crypto Trend-Following
- MLMA with EMA or HMA
- Higher RSI thresholds (75/25)
- KEMAD filter on mtf1
- Breakout entry strategy
### Stock Swing Trading
- MLMA with SMA for stability
- Volume filter with higher threshold
- KEMAD with increased filter order
- Pullback entry strategy
### Forex Scalping
- MLMA with WMA and lower noise parameter
- RSI filter on current timeframe
- Use highest timeframe for trend direction only
- Mean Reversion strategy
## Webhook Configuration
- **Benefits**:
- Automated trade execution without manual intervention
- Immediate response to market conditions
- Consistent execution of your strategy
- **Implementation Notes**:
- Requires proper webhook configuration on your exchange or platform
- Test thoroughly with small position sizes before full deployment
- Consider latency between signal generation and execution
### Backtesting Period
Define a specific historical period to evaluate the bot's performance:
| Setting | Description | Default Value |
|---------|-------------|---------------|
| **Start Date** | Beginning of backtest period | January 1, 2025 |
| **End Date** | End of backtest period | December 31, 2026 |
- **Best Practice**: Test across different market conditions (bull markets, bear markets, sideways markets)
- **Limitation**: Past performance doesn't guarantee future results
## Entry and Exit Strategies
### Dual-Channel System
A key innovation of the Bober XM is its dual-channel approach:
- **Independent Parameters**: Each trade direction has its own channel settings
- **Asymmetric Trading**: Recognizes that markets often behave differently in uptrends versus downtrends
- **Optimized Performance**: Fine-tune settings for both bullish and bearish conditions
This approach allows the bot to adapt to the natural asymmetry of markets, where uptrends often develop gradually while downtrends can be sharp and sudden.
### Channel Types
#### 1. Keltner Channels
Traditional volatility-based channels using EMA and ATR:
| Setting | Long Default | Short Default |
|---------|--------------|---------------|
| **EMA Length** | 37 | 20 |
| **ATR Length** | 13 | 17 |
| **Multiplier** | 1.4 | 1.9 |
| **Source** | low | high |
- **Strengths**:
- Reliable in trending markets
- Less prone to whipsaws than Bollinger Bands
- Clear visual representation of volatility
- **Weaknesses**:
- Can lag during rapid market changes
- Less effective in choppy, non-trending markets
#### 2. Machine Learning Moving Average (MLMA)
Advanced predictive model using kernel regression (RBF kernel):
| Setting | Description | Options |
|---------|-------------|--------|
| **Source MA** | Price data used for MA calculations | Any price source (low/high/close/etc.) |
| **Moving Average Type** | Type of MA algorithm for calculations | SMA, EMA, WMA, VWMA, RMA, HMA |
| **Trend Source** | Price data used for trend determination | Any price source (close default) |
| **Window Size** | Historical window for MLMA calculations | 5+ (default: 16) |
| **Forecast Length** | Number of bars to forecast ahead | 1+ (default: 3) |
| **Noise Parameter** | Controls smoothness of prediction | 0.01+ (default: ~0.43) |
| **Band Multiplier** | Multiplier for channel width | 0.1+ (default: 0.5-0.6) |
- **Strengths**:
- Predictive rather than reactive
- Adapts quickly to changing market conditions
- Better at identifying trend reversals early
- **Weaknesses**:
- More computationally intensive
- Requires careful parameter tuning
- Can be sensitive to input data quality
### Entry Strategies
| Strategy | Description | Ideal Market Conditions |
|----------|-------------|-------------------------|
| **Breakout** | Enters when price breaks through channel bands, indicating strong momentum | High volatility, emerging trends |
| **Pullback** | Enters when price retraces to the middle band after testing extremes | Established trends with regular pullbacks |
| **Mean Reversion** | Enters at channel extremes, betting on a return to the mean | Range-bound or oscillating markets |
#### Breakout Strategy (Default)
- **Implementation**: Enters long when price crosses above the upper band, short when price crosses below the lower band
- **Strengths**: Captures strong momentum moves, performs well in trending markets
- **Weaknesses**: Can lead to late entries, higher risk of false breakouts
- **Optimization Tips**:
- Increase channel multiplier for fewer but more reliable signals
- Combine with volume confirmation for better accuracy
#### Pullback Strategy
- **Implementation**: Enters long when price pulls back to middle band during uptrend, short during downtrend pullbacks
- **Strengths**: Better entry prices, lower risk, higher probability setups
- **Weaknesses**: Misses some strong moves, requires clear trend identification
- **Optimization Tips**:
- Use with trend filters to confirm overall direction
- Adjust middle band calculation for market volatility
#### Mean Reversion Strategy
- **Implementation**: Enters long at lower band, short at upper band, expecting price to revert to the mean
- **Strengths**: Excellent entry prices, works well in ranging markets
- **Weaknesses**: Dangerous in strong trends, can lead to fighting the trend
- **Optimization Tips**:
- Implement strong trend filters to avoid counter-trend trades
- Use smaller position sizes due to higher risk nature
### Confirmation Indicators
#### Pivot Point SuperTrend
Combines pivot points with ATR-based SuperTrend for trend confirmation:
| Setting | Default Value |
|---------|---------------|
| **Pivot Period** | 25 |
| **ATR Factor** | 2.2 |
| **ATR Period** | 41 |
- **Function**: Identifies significant market turning points and confirms trend direction
- **Implementation**: Requires price to respect the SuperTrend line for trade confirmation
#### Weighted Moving Average (WMA)
Provides additional confirmation layer for entries:
| Setting | Default Value |
|---------|---------------|
| **Period** | 15 |
| **Source** | ohlc4 (average of Open, High, Low, Close) |
- **Function**: Confirms trend direction and filters out low-quality signals
- **Implementation**: Price must be above WMA for longs, below for shorts
### Exit Strategies
#### On-Balance Volume (OBV) Based Exits
Uses volume flow to identify potential reversals:
| Setting | Default Value |
|---------|---------------|
| **Source** | ohlc4 |
| **MA Type** | HMA (Options: SMA, EMA, WMA, RMA, VWMA, HMA) |
| **Period** | 22 |
- **Function**: Identifies divergences between price and volume to exit before reversals
- **Implementation**: Exits when OBV crosses its moving average in the opposite direction
- **Customizable MA Type**: Different MA types provide varying sensitivity to OBV changes:
- **SMA**: Traditional simple average, equal weight to all periods
- **EMA**: More weight to recent data, responds faster to price changes
- **WMA**: Weighted by recency, smoother than EMA
- **RMA**: Similar to EMA but smoother, reduces noise
- **VWMA**: Factors in volume, helpful for OBV confirmation
- **HMA**: Reduces lag while maintaining smoothness (default)
#### ADX Exit Confirmation
Uses Average Directional Index to confirm trend exhaustion:
| Setting | Default Value |
|---------|---------------|
| **ADX Threshold** | 35 |
| **ADX Smoothing** | 60 |
| **DI Length** | 60 |
- **Function**: Confirms trend weakness before exiting positions
- **Implementation**: Requires ADX to drop below threshold or DI lines to cross
## Filter System
### RSI Filter
- **Function**: Controls entries based on momentum conditions
- **Parameters**:
- Period: 15 (default)
- Overbought level: 71
- Oversold level: 23
- Multi-timeframe support: Current, MTF1 (15min), or MTF2 (4h)
- Customizable price source (open, high, low, close, hl2, hlc3, ohlc4)
- **Implementation**: Blocks long entries when RSI > overbought, short entries when RSI < oversold
### Volatility Filter
- **Function**: Prevents trading during excessive market volatility
- **Parameters**:
- Measure: ATR (Average True Range)
- Period: Customizable (default varies by timeframe)
- Threshold: Adjustable multiplier
- Multi-timeframe support
- Customizable price source
- **Implementation**: Blocks trades when current volatility exceeds threshold × average volatility
### Volume Filter
- **Function**: Ensures adequate market liquidity for trades
- **Parameters**:
- Threshold: 0.4× average (default)
- Measurement period: 5 (default)
- Moving average type: Customizable (HMA default)
- Multi-timeframe support
- Customizable price source
- **Implementation**: Requires current volume to exceed threshold × average volume
### Bollinger Bands Filter
- **Function**: Controls entries based on price relative to statistical boundaries
- **Parameters**:
- Period: Customizable
- Standard deviation multiplier: Adjustable
- Moving average type: Customizable
- Multi-timeframe support
- Customizable price source
- **Implementation**: Can require price to be within bands or breaking out of bands depending on strategy
### KEMAD Filter (Kalman EMA Distance)
- **Function**: Advanced trend confirmation using Kalman filter algorithm
- **Parameters**:
- Process Noise: 0.35 (controls smoothness)
- Measurement Noise: 24 (controls reactivity)
- Filter Order: 6 (higher = more smoothing)
- ATR Length: 8 (for bandwidth calculation)
- Upper Multiplier: 2.0 (for long signals)
- Lower Multiplier: 2.7 (for short signals)
- Multi-timeframe support
- Customizable visual indicators
- **Implementation**: Generates signals based on price position relative to Kalman-filtered EMA bands
## Risk Management System
### Position Sizing
Automatically calculates position size based on account equity and risk parameters:
| Setting | Default Value |
|---------|---------------|
| **Risk % of Equity** | 50% |
- **Implementation**:
- Position size = (Account equity × Risk %) ÷ (Entry price × Stop loss distance)
- Adjusts automatically based on volatility and stop placement
- **Best Practices**:
- Start with lower risk percentages (1-2%) until strategy is proven
- Consider reducing risk during high volatility periods
### Stop-Loss Methods
Multiple stop-loss calculation methods with separate configurations for long and short positions:
| Method | Description | Configuration |
|--------|-------------|---------------|
| **ATR-Based** | Dynamic stops based on volatility | ATR Period: 14, Multiplier: 2.0 |
| **Percentage** | Fixed percentage from entry | Long: 1.5%, Short: 1.5% |
| **PIP-Based** | Fixed currency unit distance | 10.0 pips |
- **Implementation Notes**:
- ATR-based stops adapt to changing market volatility
- Percentage stops maintain consistent risk exposure
- PIP-based stops provide precise control in stable markets
### Trailing Stops
Locks in profits by adjusting stop-loss levels as price moves favorably:
| Setting | Default Value |
|---------|---------------|
| **Stop-Loss %** | 1.5% |
| **Activation Threshold** | 2.1% |
| **Trailing Distance** | 1.4% |
- **Implementation**:
- Initial stop remains fixed until profit reaches activation threshold
- Once activated, stop follows price at specified distance
- Locks in profit while allowing room for normal price fluctuations
### Risk-Reward Parameters
Defines the relationship between risk and potential reward:
| Setting | Default Value |
|---------|---------------|
| **Risk-Reward Ratio** | 1.4 |
| **Take Profit %** | 2.4% |
| **Stop-Loss %** | 1.5% |
- **Implementation**:
- Take profit distance = Stop loss distance × Risk-reward ratio
- Higher ratios require fewer winning trades for profitability
- Lower ratios increase win rate but reduce average profit
### Filter Combinations
The strategy allows for simultaneous application of multiple filters:
- **Recommended Combinations**:
- Trending markets: RSI + KEMAD filters
- Ranging markets: Bollinger Bands + Volatility filters
- All markets: Volume filter as minimum requirement
- **Performance Impact**:
- Each additional filter reduces the number of trades
- Quality of remaining trades typically improves
- Optimal combination depends on market conditions and timeframe
### Multi-Timeframe Filter Applications
| Filter Type | Current Timeframe | MTF1 (15min) | MTF2 (4h) |
|-------------|-------------------|-------------|------------|
| RSI | Quick entries/exits | Intraday trend | Overall trend |
| Volume | Immediate liquidity | Sustained support | Market participation |
| Volatility | Entry timing | Short-term risk | Regime changes |
| KEMAD | Precise signals | Trend confirmation | Major reversals |
## Visual Indicators and Chart Analysis
The bot provides comprehensive visual feedback on the chart:
- **Channel Bands**: Keltner or MLMA bands showing potential support/resistance
- **Pivot SuperTrend**: Colored line showing trend direction and potential reversal points
- **Entry/Exit Markers**: Annotations showing actual trade entries and exits
- **Risk/Reward Zones**: Visual representation of stop-loss and take-profit levels
These visual elements allow for:
- Real-time strategy assessment
- Post-trade analysis and optimization
- Educational understanding of the strategy logic
## Implementation Guide
### TradingView Setup
1. Load the script in TradingView Pine Editor
2. Apply to your preferred chart and timeframe
3. Adjust parameters based on your trading preferences
4. Enable alerts for webhook integration
### Webhook Integration
1. Configure webhook URL in TradingView alerts
2. Set up receiving endpoint on your trading platform
3. Define message format matching the bot's output
4. Test with small position sizes before full deployment
### Optimization Process
1. Backtest across different market conditions
2. Identify parameter sensitivity through multiple tests
3. Focus on risk management parameters first
4. Fine-tune entry/exit conditions based on performance metrics
5. Validate with out-of-sample testing
## Performance Considerations
### Strengths
- Adaptability to different market conditions through dual channels
- Multiple layers of confirmation reducing false signals
- Comprehensive risk management protecting capital
- Machine learning integration for predictive edge
### Limitations
- Complex parameter set requiring careful optimization
- Potential over-optimization risk with so many variables
- Computational intensity of MLMA calculations
- Dependency on proper webhook configuration for execution
### Best Practices
- Start with conservative risk settings (1-2% of equity)
- Test thoroughly in demo environment before live trading
- Monitor performance regularly and adjust parameters
- Consider market regime changes when evaluating results
## Conclusion
The ₿ober XM v2.0 represents a significant evolution in trading strategy design, combining traditional technical analysis with machine learning elements and multi-timeframe analysis. The core strength of this system lies in its adaptability and recognition of market asymmetry.
### Market Asymmetry and Adaptive Approach
The strategy acknowledges a fundamental truth about markets: bullish and bearish phases behave differently and should be treated as distinct environments. The dual-channel system with separate parameters for long and short positions directly addresses this asymmetry, allowing for optimized performance regardless of market direction.
### Targeted Backtesting Philosophy
It's counterproductive to run backtests over excessively long periods. Markets evolve continuously, and strategies that worked in previous market regimes may be ineffective in current conditions. Instead:
- Test specific market phases separately (bull markets, bear markets, range-bound periods)
- Regularly re-optimize parameters as market conditions change
- Focus on recent performance with higher weight than historical results
- Test across multiple timeframes to ensure robustness
### Multi-Timeframe Analysis as a Game-Changer
The integration of multi-timeframe analysis fundamentally transforms the strategy's effectiveness:
- **Increased Safety**: Higher timeframe confirmations reduce false signals and improve trade quality
- **Context Awareness**: Decisions made with awareness of larger trends reduce adverse entries
- **Adaptable Precision**: Apply strict filters on lower timeframes while maintaining awareness of broader conditions
- **Reduced Noise**: Higher timeframe data naturally filters market noise that can trigger poor entries
The ₿ober XM v2.0 provides traders with a framework that acknowledges market complexity while offering practical tools to navigate it. With proper setup, realistic expectations, and attention to changing market conditions, it delivers a sophisticated approach to systematic trading that can be continuously refined and optimized.
- Trading Bot – TopBot Anomaly Robot Strategy -- Introduction -
This strategy is based on a search for abnormal market price movements relative to a time-shifted main moving average. Different variations of the main moving average are created and shifted proportionally rather than linearly, giving the strategy greater reactivity and serving as position entry points. What's more ? This strategy stands out with a major innovation, allowing position exits to be set on variations in the moving average (and not on the moving average itself, like all strategies that close positions on return to the moving average), which greatly improves actual results.
- Detailed operation of the strategy -
It defines a function that calculates various moving averages (depending on the type of moving average defined by the user) and the chosen length. The function takes into account different types of moving averages: SMA, PCMA, EMA, WMA, DEMA, ZLEMA and HMA, and is offset in time so that it can be an entry or exit condition in real time (otherwise you'd have to wait for the next candle for the moving average to be calculated).
It calculates shifted variants (semi-parallel) as a percentage of this main moving average, high and low, to define position entry points (depending on user settings, up to 10 shifted levels for ten position entries for each direction). By calculating shifts as percentages rather than fixed values, the resulting deviations are not parallel to the main moving average, but can be used to detect sudden price contractions. By adjusting these deviations proportionally, we can observe variations relative to the main moving average more clearly, enabling us to detect dynamic support and resistance zones that adapt to market fluctuations. The fact that they are not strictly parallel avoids too rigid an interpretation and gives a more nuanced reading of trends, capturing small divergences that could indicate more subtle changes in market dynamics.
The most distinctive feature of this strategy concerns position exits: the script calculates two new moving averages shifted in proportion to the main moving average (adjustable) to define position exit price levels.
The strategy enters position when one of the deviations from the position entry moving average is crossed, and exits position when the deviation from the position exit moving average is crossed.
Position entry can be single or up to ten entry levels per direction to smooth trades. Differentiated settings are available for Longs and Shorts.
In this type of strategy, the return to the moving average is generally used as the position exit point, but this strategy incorporates a unique feature: the position exit can be made on a deviation from the moving average, adjustable and differentiated for Long and Short positions.
This is a major change compared to other strategies using a moving-average position exit, since the result is thatchanging the position exit point considerably improves the strategy's results .
Backtest with a classic exit back to the moving average :
Backtest with an exit back on an (adjustable) derivative of the moving average :
- “Ready to use” and user-adjustable parameters -
The strategy interface has been optimized for easy creation of trading robots, with all settings underlying the calculations and numerous options for optimization. Here are the contents of the strategy parameters interface:
In addition, important information about strategy settings and results is displayed directly on the chart. The percentage profit displayed may differ slightly from that of the backtest, as it includes potential profits from open trades (strategy.openprofit) in its calculation.
- Conditions, options and settings for graph and backtest presentation -
Here are the conditions and settings for the graph presented on the screen:
The strategy is set for 10 possible LONG and SHORT entries
10% of capital in x2 leverage is invested at each position entry (i.e. 20% of capital under backtest conditions)
The backtest runs for 14 months: from 08/17/2023 to 08/19/2024
It is carried out on PENDLEUSDT.P on BitGet Swap in 4H
LONGS strategy settings: 0.18 - 0.19 - 0.2 - 0.21 - 0.22 - 0.23 - 0.24 - 0.25 - 0.26 - 0.275 - LONGS output deviation: 0.03 (3%)
Strategy settings for SHORTS: 0.21 - 0.22 - 0.23 - 0.24 - 0.25 - 0.26 - 0.27 - 0.28 - 0.29 - 0.3 - LONGS output deviation: 0.032 (3.2%)
All other settings are strategy defaults - Broker fees + spread are set at 0.13% per trade
We can see several interesting points:
The strategy has very high winrate if set to this objective
The settings here have not been “over-optimized”, i.e. all 10 entries are unused, leaving room for larger-than-expected market movements in the future. In this particular case, it is set to favor safety over profitability optimization, but other approaches are possible to maximize profitability.
The result is 277.75% , thanks to the strategy's adjustment of position exit levels. With a conventional exit at the moving average, results are only 204.47%, a significant difference.
- How to adjust and apply the strategy? -
Generally speaking, the strategy works well on a large proportion of cryptocurrencies, especially for LONG positions. The recommended timeframes are: 30M-45M-1H-2H-3H-4H and the most appropriate timeframe will vary according to the cryptocurrency. It is also possible, with certain assets, to run the strategy on shorter timeframes such as 5M or 15M with success.
The strategy can be used with a single position entry level, maximizing capital utilization on each trade and/or having several strategies active on a single account at the same time
It can also be used in a “safe” way, using up to ten successive entries to smooth out unforeseen market movements and minimize risk as much as possible. In this case, enter positions with 1/10 of the capital each time, for a setting of ten entries, and give preference to a single active bot per account so that all positions can be covered (a fixed dollar amount, not a percentage, is then recommended)
The recommended leverage is x1 or x2 for controlled long-term trading, especially with ten entry levels, although sometimes higher leverage could be considered with controlled risk.
Here's how to set up the strategy:
Start by finding a cryptocurrency displaying a nice curve with the default settings
Then try out the default settings on all timeframes, and select the timeframe with the best curve or the best result
Deactivate shorts
Set the first long triggerlevel to the value that gives the best result
(optional): Change the moving average type, period and data source to find the most optimized setting before proceeding to the next step
Set the 10thlong inputlevel to the last value modifying the result
Set the 8 intermediate input levels, distributing them as evenly as possible
Then adjust the output level of the longs, which can greatly improve the results
Temporarily deactivate the longs, activate the shorts and follow the same process
Reactivate longs and shorts
- How to program robots for automated trading using this strategy -
If you want to use this strategy for automated trading, it's very simple. All you need is an account with a cryptocurrency broker that allows APIs, and an intermediary between TradinView and your broker who will manage your orders.
Here's how it works:
On your intermediary, create a bot that will manage the details of your orders (amount, single or multiple entries, exit conditions). This bot is linked to the broker via an API and will be able to place real orders. Each bot has four different signals that enable it to be activated via a webhook. When one of the signals is received, it executes the orders for you.
On TradingView, set the strategy to a suitable asset and timeframe. Once set, enter in the strategy parameters the signals specific to the bot you've created. Confirm and close the parameters.
Still on TradingView, create an alarm based on your set strategy (on the strategy tester). Give the alarm the name of your choice and in “Message” enter only{{strategy.order.comment}}.
In alarm notifications, activate the webhook and enter the webhook of your trading intermediary. Confirm the alarm.
As long as the alarm is activated in TradingView, the strategy will monitor the market and send an order to enter or exit a position as soon as the conditions are met. Your bot will receive the instruction and place orders with your broker. Subsequent changes to the strategy settings do not change those stored in the alarm. If you wish to change the settings for one of your bots, simply delete the old alarm and create a new one.
Note: In your bot settings, on your intermediary, make sure to allow: - Multiple inputs - A single output signal to close all positions - Stoploss disabled (if necessary, use the strategy one)
MACD Trend Trading with Dynamic Position Sizing // AlgoFyreThe MACD Trend Trading with Dynamic Position Sizing strategy combines MACD and trend indicators for trend trading. It uses MACD crossovers to identify entry points and a trend source for directional bias. The strategy incorporates risk management through dynamic position sizing based on a fixed risk amount. It allows for both long and short positions with customizable stop-loss and take-profit levels. The script includes visualization options for entry, stop-loss, and take-profit levels, enhancing trade analysis.
TABLE OF CONTENTS
🔶 ORIGINALITY
🔸Dynamic Position Sizing
🔸Trend-MACD Combination
🔸Customizable Risk Management
🔶 FUNCTIONALITY
🔸Indicators
🞘 Trend Indicator
🞘 Moving Average Convergence Divergence (MACD)
🔸Conditions
🞘 Long Entry
🞘 Short Entry
🔶 INSTRUCTIONS
🔸Step-by-Step Guidelines
🞘 Setting Up the Strategy
🞘 Alerts
🔸Customize settings
🔶 CONCLUSION
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🔶 ORIGINALITY The MACD Trend Trading with Dynamic Position Sizing strategy uniquely combines MACD indicators with trend analysis to optimize entry and exit points. Unlike static trading strategies, it employs dynamic position sizing based on a fixed risk amount, ensuring consistent risk management. This approach allows traders to adapt to varying market conditions by adjusting position sizes according to predefined risk parameters, enhancing both flexibility and control in trading decisions. The strategy's integration of customizable stop-loss and take-profit levels further refines its risk management capabilities, making it a robust tool for both trending and volatile markets.
🔸Dynamic Position Sizing This strategy calculates position sizes dynamically, based on a fixed risk amount, allowing traders to maintain consistent risk exposure across trades.
🔸Trend-MACD Combination By combining trend direction with MACD crossovers, the strategy enhances the accuracy of entry signals, aligning trades with prevailing market trends.
🔸Customizable Risk Management Traders can set flexible risk-reward ratios and adjust stop-loss and take-profit levels, tailoring the strategy to their risk tolerance and market conditions.
🔶 FUNCTIONALITY The MACD Trend Trading with Dynamic Position Sizing strategy leverages a combination of trend indicators and the MACD to identify optimal trading opportunities. This strategy is designed to capitalize on short-term price movements by dynamically adjusting position sizes based on predefined risk parameters. It allows traders to manage risk effectively while taking advantage of both long and short positions.
🔸Indicators 🞘 Trend Indicator: Utilizes the trend source to determine market direction, ensuring trades align with prevailing trends.
Recommendation: We recommend using the Adaptive MAs (Hurst, CVaR, Fractal) indicator with the following settings for trend detection. However, you can use any trend indicator that suits your trading style.
🞘 Moving Average Convergence Divergence (MACD): Employs MACD crossovers to generate entry signals, enhancing the accuracy of trade execution. Use the "Moving Average Convergence Divergence" Indicator with the following settings:
🔸Conditions 🞘 Long Entry: Initiates a long position when the price is above the trend source, and a MACD crossover occurs with both MACD and signal lines below zero.
🞘 Short Entry: Initiates a short position when the price is below the trend source, and a MACD crossunder occurs with both MACD and signal lines above zero.
🔶 INSTRUCTIONS
The MACD Trend Trading with Dynamic Position Sizing strategy can be set up by adding it to your TradingView chart and configuring parameters such as the MACD source, trend source, and risk management settings. This strategy is designed to capitalize on short-term price movements by dynamically adjusting position sizes based on predefined risk parameters. Enhance the accuracy of signals by combining this strategy with additional indicators like trend-following or momentum-based tools. Adjust settings to better manage risk and optimize entry and exit points.
🔸Step-by-Step Guidelines
🞘 Setting Up the Strategy
Adding the Strategy to the Chart:
Go to your TradingView chart.
Click on the "Indicators" button at the top.
Search for "MACD Trend Trading with Dynamic Position Sizing" in the indicators list.
Click on the strategy to add it to your chart.
Configuring the Strategy:
Open the strategy settings by clicking on the gear icon next to its name on the chart.
MACD: Select the MACD from the MACD Indicator.
MACD Signal: Select the MACD Signal from the MACD Indicator.
Trend Source: Choose the trend source to determine market direction. If you use the Adaptive MAs (Hurst, CVaR, Fractal) with our settings shown above, choose the MA1 Smoothing Line.
Stop Loss Percentage: Set the stop loss distance from the trend source as a percentage.
Risk/Reward Ratio: Define the desired risk/reward ratio for trades.
Backtesting and Practice:
Backtest the strategy on historical data to understand how it performs in various market environments.
Practice using the strategy on a demo account before implementing it in live trading.
Market Awareness:
Keep an eye on market news and events that might cause extreme price movements. The strategy reacts to price data and might not account for news-driven events that can cause large deviations.
🔶 CONCLUSION
The MACD Trend Trading with Dynamic Position Sizing strategy provides a robust framework for capitalizing on short-term market trends by combining the MACD indicator with dynamic position sizing. This strategy leverages MACD crossovers to identify entry points and utilizes a trend source for directional bias, ensuring trades align with prevailing market conditions. By incorporating dynamic position sizing based on a fixed risk amount, traders can effectively manage risk and adapt to varying market conditions. The strategy's customizable stop-loss and take-profit levels further enhance its risk management capabilities, making it a versatile tool for both trending and volatile markets. With its strategic blend of technical indicators and risk management, the MACD Trend Trading strategy offers traders a comprehensive approach to optimizing trade execution and maximizing potential returns.
Self Optimizing RSI and Self Adaptive TP/SL [Starbots]Self Optimizing RSI and Self Adaptive TP/SL Strategy. (non-repainting)
This script continuously backtests 20 different combinations of RSI Buy conditions across 5 different Take Profit/Stop Loss combinations. In total, it tests 100 variants on every bar close and records the Net Profit gained for each combination. The strategy then selects and uses the best-performing combination of settings currently available for you to trade.
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The Relative Strength Index (RSI), developed by J. Welles Wilder, is a momentum oscillator that measures the speed and change of price movements. The RSI oscillates between zero and 100. Traditionally the RSI is considered overbought when above 70 and oversold when below 30. Signals can be generated by looking for divergences and failure swings. RSI can also be used to identify the general trend.
To improve our results we are calculating Multiple Length RSI - Average RSI based on the multiple periods. You can use just 1 Length or Multiple.
Set Inputs to Min=14, Max=14 if you want to use just 1 period.
= RSI(14)
3 RSI Lengths example (12,13 and 14):
Min=12, Max=14
(12+13+14) / 3 = avg. RSI
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Backtester - Optimizer Explained:
The backtester runs numerous backtests in the background to optimize trading strategies. Here’s how it works:
Default Inputs (Combinations of TP/SL)
TP 1%, SL4%
TP 2%, SL4%
TP 3%, SL4%
TP 2%, SL5%
TP 4.5%, SL10%
Default Inputs (RSI Crossover Buys) :
18 ,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,45,55, 69
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Backtest RSI Crossover 18:
TP1%, SL4% => Save net profit
TP2%, SL4% => Save net profit
TP3%, SL4% => Save net profit
TP2%, SL5% => Save net profit
TP4.5%, SL10% => Save net profit
,...
,...
Backtest RSI Crossover 69:
TP1%, SL4% => Save net profit
TP2%, SL4% => Save net profit
TP3%, SL4% => Save net profit
TP2%, SL5% => Save net profit
TP4.5%, SL10% => Save net profit
Self Optimizing Buy Condition and Self Optimizing Take Profit - Stop Los
This process involves testing various combinations of RSI crossover values with different Take Profit (TP) and Stop Loss (SL) percentages. The net profit for each combination is saved, allowing the optimizer to select the best-performing settings for trading.
It recalculates on every bar close. If one combination starts performing better than others—achieving a higher net profit gain (essentially like running 100 backtests with different settings in the background)—the strategy switches to that combination of TP/SL and Buy condition. It continues trading with the new settings until another parameter starts performing better and the strategy switches to that setting.
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If you wish to use it as INDICATOR - turn on 'Recalculate - On every tick' in Properties tab to have this script updating constantly and use it as a normal Indicator tool for manual trading.
Other functions:
Set the %fee for optimizing engine. If you set this % higher, you also punish small average trades and make the strategy prefer larger avg. trades, giving you better chances to make your strategy profitable.
Trade with trend and optimize the strategy only when the market is uptrending with EMA/HMA
Use Moving Average of avg.RSI and smooth the values for indicator even more. (Yes strategy is self optimizing RSI or avg.RSI or RSI-MA, you can select all sorts of this indicator for optimizing)
All trading alerts are working and functional, if you want to automate the strategy
This script is simple to use for any trader as it saves a lot of time for searching good parameters on your own. It's self-optimizing and adjusting to the markets on the go.
TradeBuilderOverview
TradeBuilder is an ever-growing toolbox that lets you combine and compound any number of bundled indicators and algorithms to create a compound strategy. At launch, we're including two Moving Averages (SMA, EMA), RSI, and Stochastic Oscillator, with many more to come. You can use any combination of indicators, be it just one, two, or all.
Key Concepts
Indicator Integration: Tradebuilder allows the use of Moving Averages, RSI, and Stochastic Oscillators, with customizable parameters for each. More indicators to come.
Mode Selection : Choose between Confirm Trend Mode (using indicators to confirm trends) and Momentum Mode (using indicators to spot reversals).
Trade Flexibility : Offers options for both long and short trades, enabling diverse trading strategies.
Customizable Inputs : Easily toggle indicators on or off and adjust specific settings like periods and thresholds.
Signal Generation : Combines multiple conditions to generate entry and exit signals.
Input Parameters:
Moving Average (MA):
use_ma : Enable this to include the Moving Average in your strategy.
ma_cross_type : Choose between "Close/MA" (price crossing the MA) or "MA/MA" (one MA crossing another).
ma_length : Set the period for the primary MA.
ma_type : Choose between "SMA" (Simple Moving Average) or "EMA" (Exponential Moving Average).
ma_length2 : Set the period for the secondary MA if using the "MA/MA" cross type.
ma_type2 : Set the type for the secondary MA.
Relative Strength Index (RSI):
use_rsi : Enable this to include RSI in your strategy.
rsi_length : Set the period for RSI calculation.
rsi_overbought : Define the overbought level.
rsi_oversold : Define the oversold level.
Stochastic Oscillator:
use_stoch : Enable this to include the Stochastic Oscillator in your strategy.
stoch_k : Set the %K period.
stoch_d : Set the %D period.
stoch_smooth : Define the smoothing factor.
stoch_overbought : Set the overbought level.
stoch_oversold : Set the oversold level.
Confirmation or Momentum Mode:
confirm_trend : Set this to true to use RSI and Stochastic Oscillator to confirm trends (long when above overbought, short when below oversold). Set to false to trade on momentum (short when above overbought, long when below oversold).
Tip: When set to false and used with just momentum oscillators like Stochastic or RSI, it's geared toward scalping as it essentially becomes momentum trading.
Trade Directions:
trade_long : Enable to allow long trades.
trade_short : Enable to allow short trades.
Example Strategy on E-mini S&P 500 Index Futures ( CME_MINI:ES1! ), 1-minute Chart
Let’s say you want to create a strategy to go long when:
A 5-period SMA crosses above a 100-period EMA.
RSI is above 20.
The Stochastic Oscillator is above 95.
Trend Confirmation Mode is on.
For short:
A 5-period SMA crosses below a 100-period EMA.
RSI is below 45.
The Stochastic Oscillator is below 5.
Trend Confirmation Mode is on.
Here’s how you would set it up in Tradebuilder:
use_ma = true
ma_cross_type = "MA/MA"
ma_length = 5
ma_type = "SMA"
ma_length2 = 100
ma_type2 = "EMA"
use_rsi = true
rsi_length = 14
rsi_overbought = 20
rsi_oversold = 45
use_stoch = true
stoch_k = 8
stoch_d = 1
stoch_smooth = 1
stoch_overbought = 95
stoch_oversold = 5
confirm_trend = true
trade_long = true
trade_short = false
Alerts
Here is how to set TradeBuilder alerts: open a TradingView chart, attach TradeBuilder, right-click on chart -> Add Alert. Condition: Symbol (e.g. NQ) >> TradeBuilder >> Open-Ended Alert >> Once Per Bar Close.
Development Roadmap
We plan to add many more compoundable indicators to TradeBuilder over the coming months from all walks of technical analysis, including Volume, Volatility, Trend Detection/Validation, Momentum, Divergences, Chart Patterns, Support/Resistance Analysis. etc.
Multi Timeframe RSI Buy Sell Strategy [TradeDots]The "Multi Timeframe RSI Buy/Sell Strategy" is a trading strategy that utilizes Relative Strength Index (RSI) indicators from multiple timeframes to provide buy and sell signals.
This strategy allows for extensive customization, supporting up to three distinct RSIs, each configurable with its own timeframe, length, and data source.
HOW DOES IT WORK
This strategy integrates up to three RSIs, each selectable from different timeframes and customizable in terms of length and source. Users have the flexibility to define the number of active RSIs. These selections visualize as plotted lines on the chart, enhancing interpretability.
Users can also manage the moving average of the selected RSI lines. When multiple RSIs are active, the moving average is calculated based on these active lines' average value.
The color intensity of the moving average line changes as it approaches predefined buying or selling thresholds, alerting users to potential signal generation.
A buy or sell signal is generated when all active RSI lines simultaneously cross their respective threshold lines. Concurrently, a label will appear on the chart to signify the order placement.
For those preferring not to display order information or activate the strategy, an "Enable backtest" option is provided in the settings for toggling activation.
APPLICATION
The strategy leverages multiple RSIs to detect extreme market conditions across various timeframes without the need for manual timeframe switching.
This feature is invaluable for identifying divergences across timeframes, such as detecting potential short-term reversals within broader trends, thereby aiding traders in making better trading decisions and potentially avoiding losses.
DEFAULT SETUP
Commission: 0.01%
Initial Capital: $10,000
Equity per Trade: 60%
RISK DISCLAIMER
Trading entails substantial risk, and most day traders incur losses. All content, tools, scripts, articles, and education provided by TradeDots serve purely informational and educational purposes. Past performances are not definitive predictors of future results.
TradeDots Stochastic Z-Score
OBVious MA Strategy [1000X Trader]Exploring OBV: The OBVious MA Strategy
Are you using On Balance Volume (OBV) effectively? OBV is a gift to traders. OBV often provides a leading signal at the outset of a trend, when compression in the markets produces a surge in OBV prior to increased volatility.
This strategy demonstrates one method of utilizing OBV to your advantage. I call it the "OBVious MA Strategy ” only because it is so simple in its mechanics. This is meant to be a demonstration, not a strategy to utilize in live trading, as the primary utility of the OBVious MA indicator is as a volume confirmation filter that complements other components of a strategy. That said, I felt useful to present this indicator in isolation in this strategy to demonstrate the power it holds.
Strategy Features:
• OBV is the core signal: this strategy revolves around the On Balance Volume indicator. OBV is a straightforward indicator: it registers a value by adding total volume traded on up candles, and subtracts total volume on down candles, generating a line by connecting those values. OBV was described in 1963 by Joe Granville in his book "Granville's New Key to Stock Market Profits” in which the author argues that OBV is the most vital key to success as a trader, as volume changes are a major predictor of price changes.
• Dual Moving Averages: here we use separate moving averages for entries and exits. This allows for more granular trade management; for example, one can either extend the length of the exit MA to hold positions longer, or shorten the MA for swifter exits, independently of the entry signals.
Execution: long trades are taken when the OBV line crosses above the Long Entry Moving Average of the OBV. Long exits occur when the OBV line crosses under the Long Exit MA of the OBV. Shorts enter on a cross below the Short Entry MA, and exit on a cross above the Short Exit MA.
• Directional Trading: a direction filter can be set to "long" or "short," but not “both”, given that there is no trend filter in this strategy. When used in a bi-directional strategy with a trend filter, we add “both” to the script as a third option.
Application:
While this strategy outlines entry and exit conditions based on OBV crossovers with designated moving averages, is is, as stated, best used in conjunction with a supporting cast of confirmatory indicators (feel free to drop me a note and tell me how you've used it). It can be used to confirm entries, or you might try using it as a sole exit indicator in a strategy.
Visualization:
The strategy includes conditional plotting of the OBV MAs, which plot based on the selected trading direction. This visualization aids in understanding how OBV interacts with the set moving averages.
Further Discussion:
We all know the importance of volume; this strategy demonstrates one simple yet effective method of incorporating the OBV for volume analysis. The OBV indicator can be used in many ways - for example, we can monitor OBV trend line breaks, look for divergences, or as we do here, watch for breaks of the moving average.
Despite its simplicity, I'm unaware of any previously published cases of this method. The concept of applying MAs or EMAs to volume-based indicators like OBV is not uncommon in technical analysis, so I expect that work like this has been done before. If you know of other similar indicators or strategies, please mention in the comments.
One comparable strategy that uses EMAs of the OBV is QuantNomad’s "On Balance Volume Oscillator Strategy ", which uses a pair of EMAs on a normalized-range OBV-based oscillator. In that strategy, however, entries and exits occur on one EMA crossing the other, which places trades at distinctly different times than crossings of the OBV itself. Both are valid approaches with strength in simplicity.
Self Optimizing ROC [Starbots]Self Optimizing Rate of Change (ROC) Strategy. (non-repainting)
Script constantly tests 15 different ROC parameter combinations for maximum profitability and trades based on the best performing combination.
You will notice that signal lines switch after a bar close sometimes, this is when the strategy optimizes to the better combination and change plots, strategy is dynamic.
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The Rate-of-Change (ROC) indicator, which is also referred to as Momentum, is a pure momentum oscillator that measures the percent change in price from one period to the next. The ROC calculation compares the current price with the price “n” periods ago. The plot forms an oscillator that fluctuates above and below the zero line as the rate of change moves from positive to negative. As a momentum oscillator, ROC signals include centerline crossovers, divergences, and overbought-oversold readings.
ROC = (Close - Close n periods ago) / (Close n periods ago) * 100
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The logic of self - optimizing:
This script is always backtesting 15 different combinations of ROC settings in the background and saves the net. profit gained for every single one of them, then strategy selects and use the best performing combination of settings currently available for you to trade.
It's recalculating on every bar close - if one of the parameters starts performing better than others - have a higher net profit gain (it's literally like running 15 backtests with different settings in the background) strategy switches to that parameter and continues trading like that until one of the other indicator parameters starts performing better again and switches to that settings.
We are optimizing our strategy based on 15 different 'lengths' or also called 'periods' of ROC.
Inputs (ROC period) : (you don't need to change them, you have a nice wide variety of periods)
🔴Roc (default=9) = 5
🟢Roc2 = 6
🔵Roc3 = 7
🟡Roc4 = 8
🟣Roc5 = 9
🟠Roc6 = 10
🔴Roc7 = 11
🟢Roc8 = 12
🔵Roc9 = 13
🟡Roc10 = 14
🟣Roc11 = 15
🟠Roc12 = 16
🟡Roc13 = 17
🟣Roc14 = 18
🟠Roc15 = 20
Backtester in the background works like this:
backtest ROC1 => save net. profit
backtest ROC2 => save net. profit ;
backtest ROC3 => save net. profit ;
..........
..........
backtest ROC15 => save net. profit ;
=>
It will backtest 15 different ROC parameters and save their profits.
Your strategy then trades based on the best performing (highest net.profit) ROC Setting currently available. It will check the calculations and backtest them on every new bar close - it's like running 15 strategies at time, and manually selecting the best performing one.
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If you wish to use it as INDICATOR - turn on 'Recalculate after every tick' in Properties tab to have this script updating constantly and use it as a normal Indicator tool for manual trading.
-- Noise Filter - This will punish the tiny trades made by certain parameters and give more advantage to big average trades. It's basically normal fee calculation, it will deduct 0.xx % fee from every trade when optimizing. You usually want it to have the same number as your fees on exchange. Large number will choose big long swing trades, small number will prioritize small scalping trades.
-- Turn on ROC Combination Profits and spot the worst/best performing combination. You can change periods to get the best performance after checking this table stats.
-- Backtesting Range - backtest within your desired time window. Example: 'from 01 / 01 /2020 to 01 / 01 /2023'.
-- Optimizing range - you can decrease the amount of bars/data for optimizing script. This way you can keep it up to date to more recent market by selecting optimizing range to optimize it just from the recent 3-6months of data for example. Strategy before this selected range will normally trade (backtest) based on the first ROC period ( 'Roc(default=9)' Input) parameter in your menu if you have Optimizing Range turned on.
**** I recommend 'Optimizing Range' to be turned off, use max amount of available bars in your history for optimization script.
-- Strategy is trading on the bar close without repaint. You can trade Long-Sell or Long- Short. Alerts available, insert webhook messages.
-- Turn on Profit Calendar for better overview of how your strategy performs monthly/annualy
-- Recommended ROC periods: from 5 to 24.
-- Recommended Sources : close, hlc3, hlcc4
-- Recommended Chart Timeframe : 4h +
-- Notes window : add your custom comments here or save your webhook messages inside here
-- Trading Session: in a session, you have to specify the time range for every day. It will trade only within this window and close trades when it's out. Session from 9am to 5pm will look like that: 0900-1700 or 7am to 4:30pm 0700-1630. After the colon, you can specify days of the week for your trading session. 1234567 trading all days, 23456 – Monday to Friday ('1 is Sunday here'). 0000-0000:1234567 by default will trade every day nonstop. 00.00am to 00.00pm and 1234567 every day of the week for example - Cryptocurrencies.
This script is simple to use for any trader as it saves a lot of time for searching good parameters on your own. It's self-optimizing and adjusting to the markets on the go.
Supertrend Advance Pullback StrategyHandbook for the Supertrend Advance Strategy
1. Introduction
Purpose of the Handbook:
The main purpose of this handbook is to serve as a comprehensive guide for traders and investors who are looking to explore and harness the potential of the Supertrend Advance Strategy. In the rapidly changing financial market, having the right tools and strategies at one's disposal is crucial. Whether you're a beginner hoping to dive into the world of trading or a seasoned investor aiming to optimize and diversify your portfolio, this handbook offers the insights and methodologies you need. By the end of this guide, readers should have a clear understanding of how the Supertrend Advance Strategy works, its benefits, potential pitfalls, and practical application in various trading scenarios.
Overview of the Supertrend Advance Pullback Strategy:
At its core, the Supertrend Advance Strategy is an evolution of the popular Supertrend Indicator. Designed to generate buy and sell signals in trending markets, the Supertrend Indicator has been a favorite tool for many traders around the world. The Advance Strategy, however, builds upon this foundation by introducing enhanced mechanisms, filters, and methodologies to increase precision and reduce false signals.
1. Basic Concept:
The Supertrend Advance Strategy relies on a combination of price action and volatility to determine the potential trend direction. By assessing the average true range (ATR) in conjunction with specific price points, this strategy aims to highlight the potential starting and ending points of market trends.
2. Methodology:
Unlike the traditional Supertrend Indicator, which primarily focuses on closing prices and ATR, the Advance Strategy integrates other critical market variables, such as volume, momentum oscillators, and perhaps even fundamental data, to validate its signals. This multidimensional approach ensures that the generated signals are more reliable and are less prone to market noise.
3. Benefits:
One of the main benefits of the Supertrend Advance Strategy is its ability to filter out false breakouts and minor price fluctuations, which can often lead to premature exits or entries in the market. By waiting for a confluence of factors to align, traders using this advanced strategy can increase their chances of entering or exiting trades at optimal points.
4. Practical Applications:
The Supertrend Advance Strategy can be applied across various timeframes, from intraday trading to swing trading and even long-term investment scenarios. Furthermore, its flexible nature allows it to be tailored to different asset classes, be it stocks, commodities, forex, or cryptocurrencies.
In the subsequent sections of this handbook, we will delve deeper into the intricacies of this strategy, offering step-by-step guidelines on its application, case studies, and tips for maximizing its efficacy in the volatile world of trading.
As you journey through this handbook, we encourage you to approach the Supertrend Advance Strategy with an open mind, testing and tweaking it as per your personal trading style and risk appetite. The ultimate goal is not just to provide you with a new tool but to empower you with a holistic strategy that can enhance your trading endeavors.
2. Getting Started
Navigating the financial markets can be a daunting task without the right tools. This section is dedicated to helping you set up the Supertrend Advance Strategy on one of the most popular charting platforms, TradingView. By following the steps below, you'll be able to integrate this strategy into your charts and start leveraging its insights in no time.
Setting up on TradingView:
TradingView is a web-based platform that offers a wide range of charting tools, social networking, and market data. Before you can apply the Supertrend Advance Strategy, you'll first need a TradingView account. If you haven't set one up yet, here's how:
1. Account Creation:
• Visit TradingView's official website.
• Click on the "Join for free" or "Sign up" button.
• Follow the registration process, providing the necessary details and setting up your login credentials.
2. Navigating the Dashboard:
• Once logged in, you'll be taken to your dashboard. Here, you'll see a variety of tools, including watchlists, alerts, and the main charting window.
• To begin charting, type in the name or ticker of the asset you're interested in the search bar at the top.
3. Configuring Chart Settings:
• Before integrating the Supertrend Advance Strategy, familiarize yourself with the chart settings. This can be accessed by clicking the 'gear' icon on the top right of the chart window.
• Adjust the chart type, time intervals, and other display settings to your preference.
Integrating the Strategy into a Chart:
Now that you're set up on TradingView, it's time to integrate the Supertrend Advance Strategy.
1. Accessing the Pine Script Editor:
• Located at the top-center of your screen, you'll find the "Pine Editor" tab. Click on it.
• This is where custom strategies and indicators are scripted or imported.
2. Loading the Supertrend Advance Strategy Script:
• Depending on whether you have the script or need to find it, there are two paths:
• If you have the script: Copy the Supertrend Advance Strategy script, and then paste it into the Pine Editor.
• If searching for the script: Click on the “Indicators” icon (looks like a flame) at the top of your screen, and then type “Supertrend Advance Strategy” in the search bar. If available, it will show up in the list. Simply click to add it to your chart.
3. Applying the Strategy:
• After pasting or selecting the Supertrend Advance Strategy in the Pine Editor, click on the “Add to Chart” button located at the top of the editor. This will overlay the strategy onto your main chart window.
4. Configuring Strategy Settings:
• Once the strategy is on your chart, you'll notice a small settings ('gear') icon next to its name in the top-left of the chart window. Click on this to access settings.
• Here, you can adjust various parameters of the Supertrend Advance Strategy to better fit your trading style or the specific asset you're analyzing.
5. Interpreting Signals:
• With the strategy applied, you'll now see buy/sell signals represented on your chart. Take time to familiarize yourself with how these look and behave over various timeframes and market conditions.
3. Strategy Overview
What is the Supertrend Advance Strategy?
The Supertrend Advance Strategy is a refined version of the classic Supertrend Indicator, which was developed to aid traders in spotting market trends. The strategy utilizes a combination of data points, including average true range (ATR) and price momentum, to generate buy and sell signals.
In essence, the Supertrend Advance Strategy can be visualized as a line that moves with the price. When the price is above the Supertrend line, it indicates an uptrend and suggests a potential buy position. Conversely, when the price is below the Supertrend line, it hints at a downtrend, suggesting a potential selling point.
Strategy Goals and Objectives:
1. Trend Identification: At the core of the Supertrend Advance Strategy is the goal to efficiently and consistently identify prevailing market trends. By recognizing these trends, traders can position themselves to capitalize on price movements in their favor.
2. Reducing Noise: Financial markets are often inundated with 'noise' - short-term price fluctuations that can mislead traders. The Supertrend Advance Strategy aims to filter out this noise, allowing for clearer decision-making.
3. Enhancing Risk Management: With clear buy and sell signals, traders can set more precise stop-loss and take-profit points. This leads to better risk management and potentially improved profitability.
4. Versatility: While primarily used for trend identification, the strategy can be integrated with other technical tools and indicators to create a comprehensive trading system.
Type of Assets/Markets to Apply the Strategy:
1. Equities: The Supertrend Advance Strategy is highly popular among stock traders. Its ability to capture long-term trends makes it particularly useful for those trading individual stocks or equity indices.
2. Forex: Given the 24-hour nature of the Forex market and its propensity for trends, the Supertrend Advance Strategy is a valuable tool for currency traders.
3. Commodities: Whether it's gold, oil, or agricultural products, commodities often move in extended trends. The strategy can help in identifying and capitalizing on these movements.
4. Cryptocurrencies: The volatile nature of cryptocurrencies means they can have pronounced trends. The Supertrend Advance Strategy can aid crypto traders in navigating these often tumultuous waters.
5. Futures & Options: Traders and investors in derivative markets can utilize the strategy to make more informed decisions about contract entries and exits.
It's important to note that while the Supertrend Advance Strategy can be applied across various assets and markets, its effectiveness might vary based on market conditions, timeframe, and the specific characteristics of the asset in question. As always, it's recommended to use the strategy in conjunction with other analytical tools and to backtest its effectiveness in specific scenarios before committing to trades.
4. Input Settings
Understanding and correctly configuring input settings is crucial for optimizing the Supertrend Advance Strategy for any specific market or asset. These settings, when tweaked correctly, can drastically impact the strategy's performance.
Grouping Inputs:
Before diving into individual input settings, it's important to group similar inputs. Grouping can simplify the user interface, making it easier to adjust settings related to a specific function or indicator.
Strategy Choice:
This input allows traders to select from various strategies that incorporate the Supertrend indicator. Options might include "Supertrend with RSI," "Supertrend with MACD," etc. By choosing a strategy, the associated input settings for that strategy become available.
Supertrend Settings:
1. Multiplier: Typically, a default value of 3 is used. This multiplier is used in the ATR calculation. Increasing it makes the Supertrend line further from prices, while decreasing it brings the line closer.
2. Period: The number of bars used in the ATR calculation. A common default is 7.
EMA Settings (Exponential Moving Average):
1. Period: Defines the number of previous bars used to calculate the EMA. Common periods are 9, 21, 50, and 200.
2. Source: Allows traders to choose which price (Open, Close, High, Low) to use in the EMA calculation.
RSI Settings (Relative Strength Index):
1. Length: Determines how many periods are used for RSI calculation. The standard setting is 14.
2. Overbought Level: The threshold at which the asset is considered overbought, typically set at 70.
3. Oversold Level: The threshold at which the asset is considered oversold, often at 30.
MACD Settings (Moving Average Convergence Divergence):
1. Short Period: The shorter EMA, usually set to 12.
2. Long Period: The longer EMA, commonly set to 26.
3. Signal Period: Defines the EMA of the MACD line, typically set at 9.
CCI Settings (Commodity Channel Index):
1. Period: The number of bars used in the CCI calculation, often set to 20.
2. Overbought Level: Typically set at +100, denoting overbought conditions.
3. Oversold Level: Usually set at -100, indicating oversold conditions.
SL/TP Settings (Stop Loss/Take Profit):
1. SL Multiplier: Defines the multiplier for the average true range (ATR) to set the stop loss.
2. TP Multiplier: Defines the multiplier for the average true range (ATR) to set the take profit.
Filtering Conditions:
This section allows traders to set conditions to filter out certain signals. For example, one might only want to take buy signals when the RSI is below 30, ensuring they buy during oversold conditions.
Trade Direction and Backtest Period:
1. Trade Direction: Allows traders to specify whether they want to take long trades, short trades, or both.
2. Backtest Period: Specifies the time range for backtesting the strategy. Traders can choose from options like 'Last 6 months,' 'Last 1 year,' etc.
It's essential to remember that while default settings are provided for many of these tools, optimal settings can vary based on the market, timeframe, and trading style. Always backtest new settings on historical data to gauge their potential efficacy.
5. Understanding Strategy Conditions
Developing an understanding of the conditions set within a trading strategy is essential for traders to maximize its potential. Here, we delve deep into the logic behind these conditions, using the Supertrend Advance Strategy as our focal point.
Basic Logic Behind Conditions:
Every strategy is built around a set of conditions that provide buy or sell signals. The conditions are based on mathematical or statistical methods and are rooted in the study of historical price data. The fundamental idea is to recognize patterns or behaviors that have been profitable in the past and might be profitable in the future.
Buy and Sell Conditions:
1. Buy Conditions: Usually formulated around bullish signals or indicators suggesting upward price momentum.
2. Sell Conditions: Centered on bearish signals or indicators indicating downward price momentum.
Simple Strategy:
The simple strategy could involve using just the Supertrend indicator. Here:
• Buy: When price closes above the Supertrend line.
• Sell: When price closes below the Supertrend line.
Pullback Strategy:
This strategy capitalizes on price retracements:
• Buy: When the price retraces to the Supertrend line after a bullish signal and is supported by another bullish indicator.
• Sell: When the price retraces to the Supertrend line after a bearish signal and is confirmed by another bearish indicator.
Indicators Used:
EMA (Exponential Moving Average):
• Logic: EMA gives more weight to recent prices, making it more responsive to current price movements. A shorter-period EMA crossing above a longer-period EMA can be a bullish sign, while the opposite is bearish.
RSI (Relative Strength Index):
• Logic: RSI measures the magnitude of recent price changes to analyze overbought or oversold conditions. Values above 70 are typically considered overbought, and values below 30 are considered oversold.
MACD (Moving Average Convergence Divergence):
• Logic: MACD assesses the relationship between two EMAs of a security’s price. The MACD line crossing above the signal line can be a bullish signal, while crossing below can be bearish.
CCI (Commodity Channel Index):
• Logic: CCI compares a security's average price change with its average price variation. A CCI value above +100 may mean the price is overbought, while below -100 might signify an oversold condition.
And others...
As the strategy expands or contracts, more indicators might be added or removed. The crucial point is to understand the core logic behind each, ensuring they align with the strategy's objectives.
Logic Behind Each Indicator:
1. EMA: Emphasizes recent price movements; provides dynamic support and resistance levels.
2. RSI: Indicates overbought and oversold conditions based on recent price changes.
3. MACD: Showcases momentum and direction of a trend by comparing two EMAs.
4. CCI: Measures the difference between a security's price change and its average price change.
Understanding strategy conditions is not just about knowing when to buy or sell but also about comprehending the underlying market dynamics that those conditions represent. As you familiarize yourself with each condition and indicator, you'll be better prepared to adapt and evolve with the ever-changing financial markets.
6. Trade Execution and Management
Trade execution and management are crucial aspects of any trading strategy. Efficient execution can significantly impact profitability, while effective management can preserve capital during adverse market conditions. In this section, we'll explore the nuances of position entry, exit strategies, and various Stop Loss (SL) and Take Profit (TP) methodologies within the Supertrend Advance Strategy.
Position Entry:
Effective trade entry revolves around:
1. Timing: Enter at a point where the risk-reward ratio is favorable. This often corresponds to confirmatory signals from multiple indicators.
2. Volume Analysis: Ensure there's adequate volume to support the movement. Volume can validate the strength of a signal.
3. Confirmation: Use multiple indicators or chart patterns to confirm the entry point. For instance, a buy signal from the Supertrend indicator can be confirmed with a bullish MACD crossover.
Position Exit Strategies:
A successful exit strategy will lock in profits and minimize losses. Here are some strategies:
1. Fixed Time Exit: Exiting after a predetermined period.
2. Percentage-based Profit Target: Exiting after a certain percentage gain.
3. Indicator-based Exit: Exiting when an indicator gives an opposing signal.
Percentage-based SL/TP:
• Stop Loss (SL): Set a fixed percentage below the entry price to limit potential losses.
• Example: A 2% SL on an entry at $100 would trigger a sell at $98.
• Take Profit (TP): Set a fixed percentage above the entry price to lock in gains.
• Example: A 5% TP on an entry at $100 would trigger a sell at $105.
Supertrend-based SL/TP:
• Stop Loss (SL): Position the SL at the Supertrend line. If the price breaches this line, it could indicate a trend reversal.
• Take Profit (TP): One could set the TP at a point where the Supertrend line flattens or turns, indicating a possible slowdown in momentum.
Swing high/low-based SL/TP:
• Stop Loss (SL): For a long position, set the SL just below the recent swing low. For a short position, set it just above the recent swing high.
• Take Profit (TP): For a long position, set the TP near a recent swing high or resistance. For a short position, near a swing low or support.
And other methods...
1. Trailing Stop Loss: This dynamic SL adjusts with the price movement, locking in profits as the trade moves in your favor.
2. Multiple Take Profits: Divide the position into segments and set multiple TP levels, securing profits in stages.
3. Opposite Signal Exit: Exit when another reliable indicator gives an opposite signal.
Trade execution and management are as much an art as they are a science. They require a blend of analytical skill, discipline, and intuition. Regularly reviewing and refining your strategies, especially in light of changing market conditions, is crucial to maintaining consistent trading performance.
7. Visual Representations
Visual tools are essential for traders, as they simplify complex data into an easily interpretable format. Properly analyzing and understanding the plots on a chart can provide actionable insights and a more intuitive grasp of market conditions. In this section, we’ll delve into various visual representations used in the Supertrend Advance Strategy and their significance.
Understanding Plots on the Chart:
Charts are the primary visual aids for traders. The arrangement of data points, lines, and colors on them tell a story about the market's past, present, and potential future moves.
1. Data Points: These represent individual price actions over a specific timeframe. For instance, a daily chart will have data points showing the opening, closing, high, and low prices for each day.
2. Colors: Used to indicate the nature of price movement. Commonly, green is used for bullish (upward) moves and red for bearish (downward) moves.
Trend Lines:
Trend lines are straight lines drawn on a chart that connect a series of price points. Their significance:
1. Uptrend Line: Drawn along the lows, representing support. A break below might indicate a trend reversal.
2. Downtrend Line: Drawn along the highs, indicating resistance. A break above might suggest the start of a bullish trend.
Filled Areas:
These represent a range between two values on a chart, usually shaded or colored. For instance:
1. Bollinger Bands: The area between the upper and lower band is filled, giving a visual representation of volatility.
2. Volume Profile: Can show a filled area representing the amount of trading activity at different price levels.
Stop Loss and Take Profit Lines:
These are horizontal lines representing pre-determined exit points for trades.
1. Stop Loss Line: Indicates the level at which a trade will be automatically closed to limit losses. Positioned according to the trader's risk tolerance.
2. Take Profit Line: Denotes the target level to lock in profits. Set according to potential resistance (for long trades) or support (for short trades) or other technical factors.
Trailing Stop Lines:
A trailing stop is a dynamic form of stop loss that moves with the price. On a chart:
1. For Long Trades: Starts below the entry price and moves up with the price but remains static if the price falls, ensuring profits are locked in.
2. For Short Trades: Starts above the entry price and moves down with the price but remains static if the price rises.
Visual representations offer traders a clear, organized view of market dynamics. Familiarity with these tools ensures that traders can quickly and accurately interpret chart data, leading to more informed decision-making. Always ensure that the visual aids used resonate with your trading style and strategy for the best results.
8. Backtesting
Backtesting is a fundamental process in strategy development, enabling traders to evaluate the efficacy of their strategy using historical data. It provides a snapshot of how the strategy would have performed in past market conditions, offering insights into its potential strengths and vulnerabilities. In this section, we'll explore the intricacies of setting up and analyzing backtest results and the caveats one must be aware of.
Setting Up Backtest Period:
1. Duration: Determine the timeframe for the backtest. It should be long enough to capture various market conditions (bullish, bearish, sideways). For instance, if you're testing a daily strategy, consider a period of several years.
2. Data Quality: Ensure the data source is reliable, offering high-resolution and clean data. This is vital to get accurate backtest results.
3. Segmentation: Instead of a continuous period, sometimes it's helpful to backtest over distinct market phases, like a particular bear or bull market, to see how the strategy holds up in different environments.
Analyzing Backtest Results:
1. Performance Metrics: Examine metrics like the total return, annualized return, maximum drawdown, Sharpe ratio, and others to gauge the strategy's efficiency.
2. Win Rate: It's the ratio of winning trades to total trades. A high win rate doesn't always signify a good strategy; it should be evaluated in conjunction with other metrics.
3. Risk/Reward: Understand the average profit versus the average loss per trade. A strategy might have a low win rate but still be profitable if the average gain far exceeds the average loss.
4. Drawdown Analysis: Review the periods of losses the strategy could incur and how long it takes, on average, to recover.
9. Tips and Best Practices
Successful trading requires more than just knowing how a strategy works. It necessitates an understanding of when to apply it, how to adjust it to varying market conditions, and the wisdom to recognize and avoid common pitfalls. This section offers insightful tips and best practices to enhance the application of the Supertrend Advance Strategy.
When to Use the Strategy:
1. Market Conditions: Ideally, employ the Supertrend Advance Strategy during trending market conditions. This strategy thrives when there are clear upward or downward trends. It might be less effective during consolidative or sideways markets.
2. News Events: Be cautious around significant news events, as they can cause extreme volatility. It might be wise to avoid trading immediately before and after high-impact news.
3. Liquidity: Ensure you are trading in assets/markets with sufficient liquidity. High liquidity ensures that the price movements are more reflective of genuine market sentiment and not due to thin volume.
Adjusting Settings for Different Markets/Timeframes:
1. Markets: Each market (stocks, forex, commodities) has its own characteristics. It's essential to adjust the strategy's parameters to align with the market's volatility and liquidity.
2. Timeframes: Shorter timeframes (like 1-minute or 5-minute charts) tend to have more noise. You might need to adjust the settings to filter out false signals. Conversely, for longer timeframes (like daily or weekly charts), you might need to be more responsive to genuine trend changes.
3. Customization: Regularly review and tweak the strategy's settings. Periodic adjustments can ensure the strategy remains optimized for the current market conditions.
10. Frequently Asked Questions (FAQs)
Given the complexities and nuances of the Supertrend Advance Strategy, it's only natural for traders, both new and seasoned, to have questions. This section addresses some of the most commonly asked questions regarding the strategy.
1. What exactly is the Supertrend Advance Strategy?
The Supertrend Advance Strategy is an evolved version of the traditional Supertrend indicator. It's designed to provide clearer buy and sell signals by incorporating additional indicators like EMA, RSI, MACD, CCI, etc. The strategy aims to capitalize on market trends while minimizing false signals.
2. Can I use the Supertrend Advance Strategy for all asset types?
Yes, the strategy can be applied to various asset types like stocks, forex, commodities, and cryptocurrencies. However, it's crucial to adjust the settings accordingly to suit the specific characteristics and volatility of each asset type.
3. Is this strategy suitable for day trading?
Absolutely! The Supertrend Advance Strategy can be adjusted to suit various timeframes, making it versatile for both day trading and long-term trading. Remember to fine-tune the settings to align with the timeframe you're trading on.
4. How do I deal with false signals?
No strategy is immune to false signals. However, by combining the Supertrend with other indicators and adhering to strict risk management protocols, you can minimize the impact of false signals. Always use stop-loss orders and consider filtering trades with additional confirmation signals.
5. Do I need any prior trading experience to use this strategy?
While the Supertrend Advance Strategy is designed to be user-friendly, having a foundational understanding of trading and market analysis can greatly enhance your ability to employ the strategy effectively. If you're a beginner, consider pairing the strategy with further education and practice on demo accounts.
6. How often should I review and adjust the strategy settings?
There's no one-size-fits-all answer. Some traders adjust settings weekly, while others might do it monthly. The key is to remain responsive to changing market conditions. Regular backtesting can give insights into potential required adjustments.
7. Can the Supertrend Advance Strategy be automated?
Yes, many traders use algorithmic trading platforms to automate their strategies, including the Supertrend Advance Strategy. However, always monitor automated systems regularly to ensure they're operating as intended.
8. Are there any markets or conditions where the strategy shouldn't be used?
The strategy might generate more false signals in markets that are consolidative or range-bound. During significant news events or times of unexpected high volatility, it's advisable to tread with caution or stay out of the market.
9. How important is backtesting with this strategy?
Backtesting is crucial as it allows traders to understand how the strategy would have performed in the past, offering insights into potential profitability and areas of improvement. Always backtest any new setting or tweak before applying it to live trades.
10. What if the strategy isn't working for me?
No strategy guarantees consistent profits. If it's not working for you, consider reviewing your settings, seeking expert advice, or complementing the Supertrend Advance Strategy with other analysis methods. Remember, continuous learning and adaptation are the keys to trading success.
Other comments
Value of combining several indicators in this script and how they work together
Diversification of Signals: Just as diversifying an investment portfolio can reduce risk, using multiple indicators can offer varied perspectives on potential price movements. Each indicator can capture a different facet of the market, ensuring that traders are not overly reliant on a single data point.
Confirmation & Reduced False Signals: A common challenge with many indicators is the potential for false signals. By requiring confirmation from multiple indicators before acting, the chances of acting on a false signal can be significantly reduced.
Flexibility Across Market Conditions: Different indicators might perform better under different market conditions. For example, while moving averages might excel in trending markets, oscillators like RSI might be more useful during sideways or range-bound conditions. A mashup strategy can potentially adapt better to varying market scenarios.
Comprehensive Analysis: With multiple indicators, traders can gauge trend strength, momentum, volatility, and potential market reversals all at once, providing a holistic view of the market.
How do the different indicators in the Supertrend Advance Strategy work together?
Supertrend: This is primarily a trend-following indicator. It provides traders with buy and sell signals based on the volatility of the price. When combined with other indicators, it can filter out noise and give more weight to strong, confirmed trends.
EMA (Exponential Moving Average): EMA gives more weight to recent price data. It can be used to identify the direction and strength of a trend. When the price is above the EMA, it's generally considered bullish, and vice versa.
RSI (Relative Strength Index): An oscillator that measures the magnitude of recent price changes to evaluate overbought or oversold conditions. By cross-referencing with other indicators like EMA or MACD, traders can spot potential reversals or confirmations of a trend.
MACD (Moving Average Convergence Divergence): This indicator identifies changes in the strength, direction, momentum, and duration of a trend in a stock's price. When the MACD line crosses above the signal line, it can be a bullish sign, and when it crosses below, it can be bearish. Pairing MACD with Supertrend can provide dual confirmation of a trend.
CCI (Commodity Channel Index): Initially developed for commodities, CCI can indicate overbought or oversold conditions. It can be used in conjunction with other indicators to determine entry and exit points.
In essence, the synergy of these indicators provides a balanced, comprehensive approach to trading. Each indicator offers its unique lens into market conditions, and when they align, it can be a powerful indication of a trading opportunity. This combination not only reduces the potential drawbacks of each individual indicator but leverages their strengths, aiming for more consistent and informed trading decisions.
Backtesting and Default Settings
• This indicator has been optimized to be applied for 1 hour-charts. However, the underlying principles of this strategy are supply and demand in the financial markets and the strategy can be applied to all timeframes. Daytraders can use the 1min- or 5min charts, swing-traders can use the daily charts.
• This strategy has been designed to identify the most promising, highest probability entries and trades for each stock or other financial security.
• The combination of the qualifiers results in a highly selective strategy which only considers the most promising swing-trading entries. As a result, you will normally only find a low number of trades for each stock or other financial security per year in case you apply this strategy for the daily charts. Shorter timeframes will result in a higher number of trades / year.
• Consequently, traders need to apply this strategy for a full watchlist rather than just one financial security.
• Default properties: RSI on (length 14, RSI buy level 50, sell level 50), EMA, RSI, MACD on, type of strategy pullback, SL/TP type: ATR (length 10, factor 3), trade direction both, quantity 5, take profit swing hl 5.1, highest / lowest lookback 2, enable ATR trail (ATR length 10, SL ATR multiplier 1.4, TP multiplier 2.1, lookback = 4, trade direction = both).
LuxAlgo - Backtester (OSC)The OSC Backtester is an innovative strategy script that allows users to create a wide variety of strategies using various unique oscillators.
By utilizing our 'Step' and 'Match' algorithms, users can create custom and complex strategy entries from each of the supported oscillators and included conditions, as well as any external sources, allowing users to create entries from a sequence of conditions and/or multiple matching conditions.
We included a complete alert system that will send a notification for each action taken by the strategy and we also allow users to set custom messages for each action taken by a strategy.
🔶 Features
🔹 Step & Match Algorithm
More complex entry rules can be created by using multiple conditions together, this is done thanks to the Step dropdown setting on the right of each condition.
The Step setting is directly related to the Step & Match algorithm and works in two ways:
When two or more conditions have the same step number, both conditions are evaluated. Used to test matching conditions.
When two or more conditions have different step numbers, each conditions will be evaluated in order, testing for the first step and switching to the next step once the previous one is true. When the final step is true the strategy will open a market order. Used to create sequence of conditions.
This operation is complementary, as you can create a sequence of conditions with one step consisting of two or more matching conditions as long as they have the same step number.
🔹 Fully Customizable Entries From Various Oscillators And Conditions
We allow the users to set entries using our unique HyperWave, Smart Money Flow, and their derived conditions as entries.
The Hyper Wave is a normalized adaptive oscillator aiming to reflect price trends without returning a high amount of noise.
The Smart Money Flow aims to detect trends based on market activity, by doing a comparative analysis between current volume and historical volume. A Smart Money Flow above 50 suggest market participants are bullish, else bearish. Derived from this oscillator we have Overflow indications, this indicator detects when market is overbought or oversold based on participants activity.
Other entries include proprietary reversal signals, real-time divergence detection, oscillator confluence (indicating how aligned each oscillator is), as well as entries using external sources.
🔹 Complete Alert System
Users can get alerted for any action executed by a strategy, from opening positions to closing them.
The message field in the Alert Messages setting section allows for the strategy to send a custom alert message depending on the action taken by the strategy, if no messages are set the strategy will send default messages.
🔶 Usage
Users can create a wide variety of strategies from this script, whether they are trend-following or contrarian traders.
Let's see a contrarian (revesal-based) strategy example using the following entry conditions:
Long: Hyperwave bullish divergence and oversold Hyperwave (lower than 20).
Short: Hyperwave bearish divergence and overbought Hyperwave (greater than 20).
We can also introduce take-profit and stop-loss exit conditions based on external indicators, allowing more control over exits in our strategy. For example:
Long: Hyperwave crossing over 50 while money flow is bearish.
Short: Hyperwave crossing under 50 while money flow is bullish.
Exit Long on a profit (long exit tp): Hyperwave crossing 80.
Exit Short on a profit (short exit tp): Hyperwave crossing 20.
While this strategy script can be used as a standalone, we recommend using other indicators creatively to assist with entries and exits as well as TP/SLs.
Our Step & Match algorithm can magnify interoperability, allowing for way more complete strategies through complex conditions, let's demonstrate this using the following entries:
Long: Any bullish reversal occurring after the price crosses over the lowest upper reversal zone of the Signals & Overlays™.
Short: Any bearish reversal occurring after the price crosses under the highest lower reversal zone of the Signals & Overlays™.
Long TP/SL: 5 ATR's away from the entry price.
Short TP/SL: 5 ATR's away from the entry price.
🔶 Strategy Properties (Important)
This script backtest is done on daily EURGBP, using the following backtesting properties:
Balance (default): 10 000 (default base currency)
Order Size: 10% of the equity
Comission: 3.4 pips (average spread for EURGBP)
Slippage: 3 tick
Stop Loss: 0.02 points away from entry price
We use these properties to ensure a realistic preview of the backtesting system, do note that default properties can be different for various reasons described below:
Order Size: 1 contract by default, this is to allow the strategy to run properly on most instruments such as futures.
Comission: Comission can vary depending on the market and instrument, there is no default value that might return realistic results.
We strongly recommend all users to ensure they adjust the Properties within the script settings to be in line with their accounts & trading platforms of choice to ensure results from the strategies built are realistic.
🔶 How To Access
You can see the Author's Instructions below to learn how to get access.
Pineconnector Strategy TemplateHello traders
After getting five requests in a raw to convert an indicator into a backtest strategy with statistics + Metatrader MT4/MT5 bot using Pineconnector, I decided to publish this TradingView strategy plug-and-play template automatically generating the Pineconnector alerts for you.
Trial
A 4-day FREE TRIAL is available upon request.
I'll help you with the Expert Advisor configuration on Metatrader if needed.
Features
✅ Easily convert your TradingView Indicators into a Strategy with automatically generated alerts using the Pineconnector syntax.
Non-coders don't know how to send the entry price/SL/TP/etc information from TradingView to Pineconnector.
I made that automatic - the alert messages are automatically generated with the correct syntax based on the selected broker connected to your Metatrader.
For example, the OANDA tickers aren't the same as the EightCap tickers.
The template pre-selects the correct tickers for you, and I'll keep updating that tickers list whenever there is a ticker name update on the broker side.
✅ Select whether you want to create "at-market" or "limit" orders.
The alert messages are updated accordingly.
✅ Custom close condition
Some indicators may have a custom close trade condition
For example, A trader could decide to cut a trade if another indicator gives a signal in the opposite direction
In that case, the template alerts the Expert Advisor to close the opened trade(s).
✅ Includes a Stop-Loss, Take-Profit, Trailing Stop-Loss, Stop-Loss to breakeven features
The Stop-Loss/Take-Profit can be set in percentage or pips value.
The template sends those price values to the MetaTrader Expert Advisor.
✅ For a complicated TradingView script to connect or for more filters, we suggest selecting the "Custom Integration" option
A complex TradingView is any script involving a Zig Zag, divergences, Harmonic patterns, or similar logic.
If you don't know if the indicator(s) you want to connect is/are complex or not, please ask me in DM to have a look first.
Alerts
Important: When creating the alerts, select the option "Order fills and alert() function calls"
Leave the alert message field as is - It has already been pre-filled for you.
Need more information?
For more information, please send me a direct message or email.
Strategy Results from this post
Please note they're not relevant.
I connected a simple SMA cross indicator not to showcase the backtest statistics but the connection feature between a TradingView indicator script with this Pineconnector strategy template.
Dave
CCI+EMA Strategy with Percentage or ATR TP/SL [Alifer]This is a momentum strategy based on the Commodity Channel Index (CCI), with the aim of entering long trades in oversold conditions and short trades in overbought conditions.
Optionally, you can enable an Exponential Moving Average (EMA) to only allow trading in the direction of the larger trend. Please note that the strategy will not plot the EMA. If you want, for visual confirmation, you can add to the chart an Exponential Moving Average as a second indicator, with the same settings used in the strategy’s built-in EMA.
The strategy also allows you to set internal Stop Loss and Take Profit levels, with the option to choose between Percentage-based TP/SL or ATR-based TP/SL.
The strategy can be adapted to multiple assets and timeframes:
Pick an asset and a timeframe
Zoom back as far as possible to identify meaningful positive and negative peaks of the CCI
Set Overbought and Oversold at a rough average of the peaks you identified
Adjust TP/SL according to your risk management strategy
Like the strategy? Give it a boost!
Have any questions? Leave a comment or drop me a message.
CAUTIONARY WARNING
Please note that this is a complex trading strategy that involves several inputs and conditions. Before using it in live trading, it is highly recommended to thoroughly test it on historical data and use risk management techniques to safeguard your capital. After backtesting, it's also highly recommended to perform a first live test with a small amount. Additionally, it's essential to have a good understanding of the strategy's behavior and potential risks. Only risk what you can afford to lose .
USED INDICATORS
1 — COMMODITY CHANNEL INDEX (CCI)
The Commodity Channel Index (CCI) is a technical analysis indicator used to measure the momentum of an asset. It was developed by Donald Lambert and first published in Commodities magazine (now Futures) in 1980. Despite its name, the CCI can be used in any market and is not just for commodities. The CCI compares current price to average price over a specific time period. The indicator fluctuates above or below zero, moving into positive or negative territory. While most values, approximately 75%, fall between -100 and +100, about 25% of the values fall outside this range, indicating a lot of weakness or strength in the price movement.
The CCI was originally developed to spot long-term trend changes but has been adapted by traders for use on all markets or timeframes. Trading with multiple timeframes provides more buy or sell signals for active traders. Traders often use the CCI on the longer-term chart to establish the dominant trend and on the shorter-term chart to isolate pullbacks and generate trade signals.
CCI is calculated with the following formula:
(Typical Price - Simple Moving Average) / (0.015 x Mean Deviation)
Some trading strategies based on CCI can produce multiple false signals or losing trades when conditions turn choppy. Implementing a stop-loss strategy can help cap risk, and testing the CCI strategy for profitability on your market and timeframe is a worthy first step before initiating trades.
2 — AVERAGE TRUE RANGE (ATR)
The Average True Range (ATR) is a technical analysis indicator that measures market volatility by calculating the average range of price movements in a financial asset over a specific period of time. The ATR was developed by J. Welles Wilder Jr. and introduced in his book “New Concepts in Technical Trading Systems” in 1978.
The ATR is calculated by taking the average of the true range over a specified period. The true range is the greatest of the following:
The difference between the current high and the current low.
The difference between the previous close and the current high.
The difference between the previous close and the current low.
The ATR can be used to set stop-loss orders. One way to use ATR for stop-loss orders is to multiply the ATR by a factor (such as 2 or 3) and subtract it from the entry price for long positions or add it to the entry price for short positions. This can help traders set stop-loss orders that are more adaptive to market volatility.
3 — EXPONENTIAL MOVING AVERAGE (EMA)
The Exponential Moving Average (EMA) is a type of moving average (MA) that places a greater weight and significance on the most recent data points.
The EMA is calculated by taking the average of the true range over a specified period. The true range is the greatest of the following:
The difference between the current high and the current low.
The difference between the previous close and the current high.
The difference between the previous close and the current low.
The EMA can be used by traders to produce buy and sell signals based on crossovers and divergences from the historical average. Traders often use several different EMA lengths, such as 10-day, 50-day, and 200-day moving averages.
The formula for calculating EMA is as follows:
Compute the Simple Moving Average (SMA).
Calculate the multiplier for weighting the EMA.
Calculate the current EMA using the following formula:
EMA = Closing price x multiplier + EMA (previous day) x (1-multiplier)
STRATEGY EXPLANATION
1 — INPUTS AND PARAMETERS
The strategy uses the Commodity Channel Index (CCI) with additional options for an Exponential Moving Average (EMA), Take Profit (TP) and Stop Loss (SL).
length : The period length for the CCI calculation.
overbought : The overbought level for the CCI. When CCI crosses above this level, it may signal a potential short entry.
oversold : The oversold level for the CCI. When CCI crosses below this level, it may signal a potential long entry.
useEMA : A boolean input to enable or disable the use of Exponential Moving Average (EMA) as a filter for long and short entries.
emaLength : The period length for the EMA if it is used.
2 — CCI CALCULATION
The CCI indicator is calculated using the following formula:
(src - ma) / (0.015 * ta.dev(src, length))
src is the typical price (average of high, low, and close) and ma is the Simple Moving Average (SMA) of src over the specified length.
3 — EMA CALCULATION
If the useEMA option is enabled, an EMA is calculated with the given emaLength .
4 — TAKE PROFIT AND STOP LOSS METHODS
The strategy offers two methods for TP and SL calculations: percentage-based and ATR-based.
tpSlMethod_percentage : A boolean input to choose the percentage-based method.
tpSlMethod_atr : A boolean input to choose the ATR-based method.
5 — PERCENTAGE-BASED TP AND SL
If tpSlMethod_percentage is chosen, the strategy calculates the TP and SL levels based on a percentage of the average entry price.
tp_percentage : The percentage value for Take Profit.
sl_percentage : The percentage value for Stop Loss.
6 — ATR-BASED TP AND SL
If tpSlMethod_atr is chosen, the strategy calculates the TP and SL levels based on Average True Range (ATR).
atrLength : The period length for the ATR calculation.
atrMultiplier : A multiplier applied to the ATR to set the SL level.
riskRewardRatio : The risk-reward ratio used to calculate the TP level.
7 — ENTRY CONDITIONS
The strategy defines two conditions for entering long and short positions based on CCI and, optionally, EMA.
Long Entry: CCI crosses below the oversold level, and if useEMA is enabled, the closing price should be above the EMA.
Short Entry: CCI crosses above the overbought level, and if useEMA is enabled, the closing price should be below the EMA.
8 — TP AND SL LEVELS
The strategy calculates the TP and SL levels based on the chosen method and updates them dynamically.
For the percentage-based method, the TP and SL levels are calculated as a percentage of the average entry price.
For the ATR-based method, the TP and SL levels are calculated using the ATR value and the specified multipliers.
9 — EXIT CONDITIONS
The strategy defines exit conditions for both long and short positions.
If there is a long position, it will be closed either at TP or SL levels based on the chosen method.
If there is a short position, it will be closed either at TP or SL levels based on the chosen method.
Additionally, positions will be closed if CCI crosses back above oversold in long positions or below overbought in short positions.
10 — PLOTTING
The script plots the CCI line along with overbought and oversold levels as horizontal lines.
The CCI line is colored red when above the overbought level, green when below the oversold level, and white otherwise.
The shaded region between the overbought and oversold levels is plotted as well.
BBWAS StrategyA breakout in trading refers to a situation where the price of a security or asset moves beyond a defined level of support or resistance, which is typically indicated by technical analysis tools like Bollinger Bands . Bollinger Bands consist of three lines: the upper band, the lower band, and the middle band (or basis). The upper and lower bands are set at a specified number of standard deviations away from the middle band, and they help to define the range within which the price of an asset is expected to fluctuate.
When the price of the asset moves beyond the upper or lower band, it is said to have "broken out" of the range. If the price closes below the lower band, it is considered a bearish breakout, and if it closes above the upper band, it is considered a bullish breakout.
Once a breakout occurs, traders may look for a confirmation signal before entering a trade. In this case, crossing the middle line (or basis) after a breakout may signal a potential trend reversal and a good opportunity to enter a long or short trade, depending on the direction of the breakout.
Overall, this script provides a customizable and flexible system for traders to use Bollinger Bands to identify breakout trades, with additional features to incorporate volume and RSI divergence. The dynamic TPSL system also allows traders to manage their risk and reward by automatically setting take-profit and stop-loss levels based on the volatility of the market.
Dear traders, while we strive to provide you with the best trading tools and resources, we want to remind you to exercise caution and diligence in your investing decisions.
It is important to always do your own research and analysis before making any trades. Remember, the responsibility for your investments ultimately lies with you.
Happy trading!
