Momentum Pull Back Stratergy"Master Pull Back Strategy" is a highly detailed momentum and volume-based trading system designed for Trading View. It visually annotates the chart, detects buy/sell signals, tracks market phases, and evaluates retracements and confirmations. Below is a full breakdown of its logic and components:
🔷 1. Volume Profile Highlights (Arrow Emojis)
Purpose: Show volume strength vs. average using color-coded arrows.
Calculates average volume over a user-defined period (length = 10).
Divides current volume by average volume to get volRatio.
Based on volRatio, plots small arrows (acting like diamonds) in various colors:
Low volume (black, navy, blue...) to high volume (yellow, red, purple).
Visual Purpose: Give a quick sense of how "loud" or "quiet" a candle's volume is.
📈 2. Highs of Day Tracking
Purpose: Track the high price reached during different trading sessions.
Defines pre-market, regular, and post-market sessions.
Tracks the highest price (high) in each session.
Plots colored lines:
Orange: Pre-market high
Red: Regular market high
Blue: Post-market high
🟩 3. Green Candle Pattern Detection
Purpose: Detect bullish patterns formed by consecutive green candles.
Key Conditions:
Count green candles (greenCount) until a red candle appears or 10 candles max.
Require at least 1 silver-or-above volume candle (volRatio >= 1.0).
Must have ≥3% price gain during the green sequence.
Must accumulate >20,000 volume during the green run.
If Valid:
Locks the pattern.
Records important values:
patternStartPrice, patternEndPrice, totalPatternVolume, patternHigh, patternBars
Marks the bar after which red starts (redStartBar)
⬇️ 4. Retracement Monitoring
Purpose: Track retracement from the pattern high after it locks.
Defines retracement percentage:
(greenPatternHigh - low) / (greenPatternHigh - greenPatternLow)
If retracement exceeds 80%, it invalidates the pattern.
Buy signal is disabled if pattern retraces too far.
✅ 5. Buy Signal Logic
Purpose: Fire a buy signal after pattern lock if price breaks above local high.
Conditions:
Pattern is locked (patternLocked).
Price breaks above a short-term high (triggerBreak).
It's not the first red candle.
Price is within 8.5% above EMA9.
Buy signal fires and:
Sets buyActive = true
Tracks highest price after buy
Stores buyPrice = close
❌ 6. Sell Signal Logic
Purpose: Exit signal after retracement from post-buy high.
While buy is active:
If price retraces ≥3% from the post-buy high → sellSignal = true
Resets buyActive, trackedHigh, and buyPrice
Plots a red "SELL" label above the bar.
🎨 7. Buy Signal Visual Color Coding
Purpose: Color buy signal based on how deep the retracement is.
Uses retracement percentage:
≥65% → Red (high risk)
45–65% + MACD bullish → Yellow (moderate)
<45% + MACD bullish → Green (ideal)
Plots BUY label below bar in the respective color.
🔻 8. Retracement Triangle Visuals
Purpose: Shows retracement progression while pattern is locked.
If pattern is locked and not ready for buy:
Plots triangle below bar in the buyColor for visual tracking.
⭐ 9. Star Markers Above Lock Candle
Purpose: Confirmations when pattern locks.
First Star:
Plotted above the first red candle after green pattern lock.
Second Star (⭐⭐):
Additional confirmations:
Volume OK (less than previous)
MACD bullish
Price > VWAP
VolAtLock > 100K
Price up >6% from first green candle
Price below 75% of daily EMA200 or above EMA200
Third Star (⭐⭐⭐):
Even stricter confirmations:
Volume < 60% of previous
High <= previous high
VolAtLock > 500K
Price > $3
Gain >9% from first green
Price < 50% of daily EMA200 or above EMA200
📊 10. Bar Coloring
Purpose: Visually highlight bars based on pattern phase and MACD.
Gray: MACD Bearish
Light Green: Part of active green pattern
Blue: In locked phase but no buy triggered
🔄 11. Reset Logic
Purpose: Clears all tracking variables once a buy signal fires or pattern is invalidated.
Also resets if:
Retracement is too deep
10 candles pass post-lock without a trigger
⛰️ 12. Double Top Detection
Purpose: Basic visual marker when current high == previous high.
Plots a gray triangle if current and previous bar highs match.
📌 Summary: What This Strategy Shows
Buy Opportunities: Based on high-volume green runs and confirmed breakouts.
Sell Triggers: Once a retracement from peak exceeds 3%.
Visuals for Confirmation:
Diamonds for volume
Stars for lock confidence
Colors for retracement strength
Risk Management:
Retracement filtering
Time limits on locked phases
Volume filters
Market Context: Tracks pre/regular/post market highs and daily EMA 200.
스크립트에서 "momentum"에 대해 찾기
Z-Score RSI StrategyOverview
The Z-Score RSI Indicator is an experimental take on momentum analysis. By applying the Relative Strength Index (RSI) to a Z-score of price data, it measures how far prices deviate from their mean, scaled by standard deviation. This isn’t your traditional use of RSI, which is typically based on price data alone. Nevertheless, this unconventional approach can yield unique insights into market trends and potential reversals.
Theory and Interpretation
The RSI calculates the balance between average gains and losses over a set period, outputting values from 0 to 100. Typically, people look at the overbought or oversold levels to identify momentum extremes that might be likely to lead to a reversal. However, I’ve often found that RSI can be effective for trend-following when observing the crossover of its moving average with the midline or the crossover of the RSI with its own moving average. These crossovers can provide useful trend signals in various market conditions.
By combining RSI with a Z-score of price, this indicator estimates the relative strength of the price’s distance from its mean. Positive Z-score trends may signal a potential for higher-than-average prices in the near future (scaled by the standard deviation), while negative trends suggest the opposite. Essentially, when the Z-Score RSI indicates a trend, it reflects that the Z-score (the distance between the average and current price) is likely to continue moving in the trend’s direction. Generally, this signals a potential price movement, though it’s important to note that this could also occur if there’s a shift in the mean or standard deviation, rather than a meaningful change in price itself.
While the Z-Score RSI could be an insightful addition to a comprehensive trading system, it should be interpreted carefully. Mean shifts may validate the indicator’s predictions without necessarily indicating any notable price change, meaning it’s best used in tandem with other indicators or strategies.
Recommendations
Before putting this indicator to use, conduct thorough backtesting and avoid overfitting. The added parameters allow fine-tuning to fit various assets, but be careful not to optimize purely for the highest historical returns. Doing so may create an overly tailored strategy that performs well in backtests but fails in live markets. Keep it balanced and look for robust performance across multiple scenarios, as overfitting is likely to lead to disappointing real-world results.
T&M/E Wave V2Trend and Momentum With Exception Wave Indicator and Strategy:
This strategy is hand made and I have spent days and many hours making it. The strategy is meant to determine the power between buyers and sellers, match the current power with a historic trend (through a moving average statistical equation), and finally volatility (measured with a mix between standard deviation from Bollinger Bands and HPV). Below will be a list of how to determine the inputs for the indicator
**For reference, all numbers, and settings displayed on the input screen are only what I HAVE FOUND to be profitable for my own strategy, Yours will differ. This is not financial advice and I am not a financial advisor. Please do your due diligence and own research before considering taking entries based on this strategy and indicator. I am not advertising investing, trading, or skills untaught, this is simply to help incorporate into your own strategy and improve your trading journey!**
INPUTS:
EV: This is an integer value set to default at 55. This value is equated to the lead value, volatility measurement, and standard deviation between averages
EV 2: This integer is used as the base value and is meant to always be GREATER THEN EV, the default is set at 163. There should be at least a 90+ integer difference between EVs for data accuracy.
EV TYPE & EV TYPE 2: This option only affects the output for the moving average histograms. (and data inserted for strategy)
Volatility Smoothing: This is the smoothness of the custom-made volatility oscillator. I have this default at 1 to show time-worthy-term (3.9%+) moves or significant trends to correspond with the standard deviation declination between EVMA and EVMA2.
Directional Length: This is the amount of data observed per candle in the bull versus bear indicator.
Take Profit: Pre-set takes profit level that is set to 4 but can be adjusted for user experience.
Style:
Base Length: Columns equated using a custom-made statistical equation derived from EV TYPE 2+EV2 to determine a range of differential in historic averages to a micro-scale.
Lead Length: Columns equated using a custom-made statistical equation derived from EV TYPE+EV to determine a range of differential in historic averages to a micro-scale.
Weighted EMA Differential: Equation expressing the differences between exponential and simple averages derived from EV+EV Type 2. Default is displaying none, but optional for use if found helpful.
Volatility: Represents volatility from multiple data sets spanning from Bollinger bands to HPV and translated through smoothing.
Bull Strength: The strength of Bulls in the current trend is derived from a DMI+RSI+MACD equation to represent where the trend lies.
Bear Strength: The strength of Bears in the current trend is derived from a DMI+RSI+MACD equation to represent where the trend lies.
CHEAT CODE'S NOTES:
Do not use this indicator on high leverage. I have personally used this indicator for a week and faced a max of 8% drawdown, albeit painful I was on low leverage and still closed on my take profit level.
85% is not 100% do not overtrade using this indicator's entry conditions if you have made 4 consecutive profitable trades.
Mess around with the input values and let me know if you find an even BETTER hit rate, 30+ entries and a good drawdown!!
V2 UPGRADES:
*Increased Opacity on Bull Bear Columns
*Removed the Stop Loss Input option
*Decreased EV2 to a default of 143 for accuracy
*Added additional disclaimers in the description
* Removed Bull/Bear offset values for accuracy
-Cheat Code
BYBIT:BTCUSDT
NRTH_ Smart SignalsA Custom Unique indicator by NRTH_
Comes included with the Premium Package.
NRTH_ Smart Signals is made up of over 5+ indicators and custom calculation methods. Get access to a full set of trading tools & relevant data all within one indicator to give you the levels of confluence you need.
Smart Signals works in any market & allows users to:
Detect the direction of trends in the price using two different algorithms designed for both trend following and contrarian traders.
Get automatic pivot point levels in real-time.
Filter out noise with the MA Trend Filter
Built-In Alerts
Visual Risk Management
Customizable Entry Rules
2 Calculation Methods
Get Confirmation
Use our MA Trend filter to detect the direction of trends for any asset & on any timeframe allowing traders to increase their confidence in positions and follow trends. The larger the cloud, the larger the trend.
Choose between the two calculation methods:
Leading
More sensitive
Designed to predict moves based on market data
Lagging
Less sensitive
Waits for confirmation signals
Both calculation methods have the possibility to adjust the sensitivity of these signals to market price variations, as well as the option to make them less sensitive to ranging markets so that you can trade only the variations you want.
The algo uses both momentum and trend calculation to find an entry, highly recommended use with the built-in MA Filter for best results.
Trade 24/7 without pressing a button
Smart Signals has integrated alerts which give you the ability to automate your signals with 3rd party applications. Simply adjust the sensitivities for your market and trade on autopilot.
You can also use Heikin Ashi Charts with the algo IF you only place limit orders on the exact price line that the trade outputs to ensure accurate real-time results
(Heikin Ashi trading is NOT recommended for automated trading, manual limit orders must be placed in order to match real-time results with backtested data)
Backtesting Results Info
Period 7/7/2021-15/11/2021
Entry value at $1000 with 10x leverage
Binance standard taker fee rate (0.04%)
ATR Exits : 1:2 RR
-------------------------------------------
Disclaimer
Copyright NRTH_ Indicators 2021.
NRTH_ and all affiliated parties are not registered as financial advisors. The products & services NRTH_ offers are for educational purposes only and should not be construed as financial advice. You must be aware of the risks and be willing to bear any level of risk to invest in financial markets. Past performance is not necessarily indicative of future results. NRTH_ and all individuals associated assume no responsibility for your trading results or investments.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, or individual’s trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
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Crypto Squeeze StrategyThis strategy was inspired by two famous Trading View contributors. Shout out to Lazy Bear and Crypto Face!
The strategy includes a similar replication of the blue wave, and MFI indicator. The point of the strategy is to buy when the blue wave crosses up the zero value, and the MFI is greater than zero value. This indicates that there is strong bullish momentum and money flowing into the market.
Momentum Trading By Mahfuz AzimA following indicator is Momentum Trading that uses fast QQE crosses with Moving Averages
Use for trend direction filtering. QQE or Qualitative Quantitative Estimation is based
Relative strength index (RSI), but uses a smoothing technique as an additional transformation. Three crosses can be selected (all selected by default)
Momentum StrategyThis strategy uses momentum to determine when to enter and exit positions. The default settings are set to look for a new 63 day high (~1 trading quarter) and a new 40 day relative high. If the stock is trending above the 50 day moving average it is a candidate to be bought. Stops are triggered when price closes below the 20 day or 50 day EMAs depending on how well the stock is trending. A stop could also be triggered even if price continues to move up, but is breaking down on a relative basis to a benchmark either SPX or BTCUSD . The goal is to hold on to our winners for as long as possible and cut the losers as soon as possible. This will alow us to capture the majority of major trends while avoiding many large drawdown and relative losers.
Denario momentum strategy Momentum strategy based on early trend detection indicator. It oscillates in the range . Negative values correspond to downtrend, positive to uptrend.
Values closer to 0 correspond to noise. You can set threshold values for long/short entry and exit.
But like any other momentum indicator use it along with extra filters to confirm entry and exit.
Momentum Strategy (BTC/USDT; 30m) - STOCH RSI (with source code)Here's a strategy for low time frames (30min suggested) for BTC , based on momentum Analysis using Stochastic RSI
By default the strategy will use the 50% of the specified capital for each trade; if "Gamble Sizing" is enabled, it will add the specified amount of capital (25% by default, until reaching the 100% limit or lower) for the next trade after having detected a loss in the previous trade; if the next trade is successful, the size for the next trade comes back to 50%
• Trend Filter LONG: If the fast exponential moving average is UNDER the slow exponential moving average , it won't open LONG positions
• Trend Filter SHORT: If the fast exponential moving average is ABOVE the slow exponential moving average , it won't open SHORT positions
• Bars delay: the strategy will wait the specified amount of bars before closing the current position; the counter is triggered as soon as the closing trade condition is verified
BY MAKING USE OF THIS STRATEGY, YOU ACKNOWLEDGE AND AGREE THAT: (1) YOU ARE AWARE OF THE RISKS ASSOCIATED WITH TRANSACTIONS OF DIGITAL CURRENCIES AND THEIR DERIVATIVES; (2) YOU SHALL ASSUME ALL RISKS RELATED TO THE USE OF THIS STRATEGY AND TRANSACTIONS OF DIGITAL CURRENCIES AND THEIR DERIVATIVES; AND (3) I SHALL NOT BE LIABLE FOR ANY SUCH RISKS OR ADVERSE OUTCOMES.
SOURCE CODE BELOW
Momentum Strategy for cryptos (V7.B.4)Here's a strategy for low time frames (30min suggested) for BTC, based on momentum Analysis using Stochastic RSI
By default the strategy will use the 50% of the specified capital for each trade; if "Gamble Sizing" is enabled, it will add the specified amount of capital (25% by default, until reaching the 100% limit or lower) for the next trade after having detected a loss in the previous trade; if the next trade is successful, the size for the next trade comes back to 50%
• Trend Filter LONG: If the fast exponential moving average is UNDER the slow exponential moving average, it won't open LONG positions
• Trend Filter SHORT: If the fast exponential moving average is ABOVE the slow exponential moving average, it won't open SHORT positions
• Bars delay: the strategy will wait the specified amount of bars before closing the current position; the counter is triggered as soon as the closing trade condition is verified
BY MAKING USE OF THIS STRATEGY, YOU ACKNOWLEDGE AND AGREE THAT: (1) YOU ARE AWARE OF THE RISKS ASSOCIATED WITH TRANSACTIONS OF DIGITAL CURRENCIES AND THEIR DERIVATIVES; (2) YOU SHALL ASSUME ALL RISKS RELATED TO THE USE OF THIS STRATEGY AND TRANSACTIONS OF DIGITAL CURRENCIES AND THEIR DERIVATIVES; AND (3) I SHALL NOT BE LIABLE FOR ANY SUCH RISKS OR ADVERSE OUTCOMES.
Momentum fader 1.0The strategy is based on a momentum gauge designed for lower timeframes. In the current iteration, trades are very conservative and closed quickly.
In a future version, I've planned to implement dynamic take profit and stoploss levels for ultimate accuracy and maximized profit:drawdown ratio.
The strategy is specifically made for ETH and works best on the 3-minute timeframe.
Enjoy!
MOMENTUM INDICATOR / INVERS FISHER / RSI / MTF / STRAT// Strategy based on Momentum indicator and Inverse Fisher transform with Multi Time Frame function on Relative Strength Index (RSI)
// Greatest effect on 15M+ time frame
// Created and based on Binance chart
// Working with comission
// No repaints
Momentum Indicator Strategy 15m// Strategy based on Momentum Indicator
// Greatest effect on 15M time frame
// Created and based on Binance chart
// Working with comission
// No repaints
Momentum Strategy, rev.2This is a revised version of the Momentum strategy listed in the built-ins.
For more information check out this resource:
www.forexstrategiesresources.com
Runner 1.0This script uses moving average crosses together with momentum to try to optimalise entry and exit, based on the market info at that time.
It works best on the 5 minute chart, and pyramiding will increase profit - but lower the profit factor. Based on testing, it works with the most major currency pairs as well as commodities.
OmenImproved momentum-based trading algorithm based on my previous Merlin V6 script. Adjusted trade filtering rules to improve net return and profit factor on both long and short positions.
Works best with mid time-frame Heikin-Ashi data.
SuperATR 7-Step Profit - Strategy [presentTrading] Long time no see!
█ Introduction and How It Is Different
The SuperATR 7-Step Profit Strategy is a multi-layered trading approach that integrates adaptive Average True Range (ATR) calculations with momentum-based trend detection. What sets this strategy apart is its sophisticated 7-step take-profit mechanism, which combines four ATR-based exit levels and three fixed percentage levels. This hybrid approach allows traders to dynamically adjust to market volatility while systematically capturing profits in both long and short market positions.
Traditional trading strategies often rely on static indicators or single-layered exit strategies, which may not adapt well to changing market conditions. The SuperATR 7-Step Profit Strategy addresses this limitation by:
- Using Adaptive ATR: Enhances the standard ATR by making it responsive to current market momentum.
- Incorporating Momentum-Based Trend Detection: Identifies stronger trends with higher probability of continuation.
- Employing a Multi-Step Take-Profit System: Allows for gradual profit-taking at predetermined levels, optimizing returns while minimizing risk.
BTCUSD 6hr Performance
█ Strategy, How It Works: Detailed Explanation
The strategy revolves around detecting strong market trends and capitalizing on them using an adaptive ATR and momentum indicators. Below is a detailed breakdown of each component of the strategy.
🔶 1. True Range Calculation with Enhanced Volatility Detection
The True Range (TR) measures market volatility by considering the most significant price movements. The enhanced TR is calculated as:
TR = Max
Where:
High and Low are the current bar's high and low prices.
Previous Close is the closing price of the previous bar.
Abs denotes the absolute value.
Max selects the maximum value among the three calculations.
🔶 2. Momentum Factor Calculation
To make the ATR adaptive, the strategy incorporates a Momentum Factor (MF), which adjusts the ATR based on recent price movements.
Momentum = Close - Close
Stdev_Close = Standard Deviation of Close over n periods
Normalized_Momentum = Momentum / Stdev_Close (if Stdev_Close ≠ 0)
Momentum_Factor = Abs(Normalized_Momentum)
Where:
Close is the current closing price.
n is the momentum_period, a user-defined input (default is 7).
Standard Deviation measures the dispersion of closing prices over n periods.
Abs ensures the momentum factor is always positive.
🔶 3. Adaptive ATR Calculation
The Adaptive ATR (AATR) adjusts the traditional ATR based on the Momentum Factor, making it more responsive during volatile periods and smoother during consolidation.
Short_ATR = SMA(True Range, short_period)
Long_ATR = SMA(True Range, long_period)
Adaptive_ATR = /
Where:
SMA is the Simple Moving Average.
short_period and long_period are user-defined inputs (defaults are 3 and 7, respectively).
🔶 4. Trend Strength Calculation
The strategy quantifies the strength of the trend to filter out weak signals.
Price_Change = Close - Close
ATR_Multiple = Price_Change / Adaptive_ATR (if Adaptive_ATR ≠ 0)
Trend_Strength = SMA(ATR_Multiple, n)
🔶 5. Trend Signal Determination
If (Short_MA > Long_MA) AND (Trend_Strength > Trend_Strength_Threshold):
Trend_Signal = 1 (Strong Uptrend)
Elif (Short_MA < Long_MA) AND (Trend_Strength < -Trend_Strength_Threshold):
Trend_Signal = -1 (Strong Downtrend)
Else:
Trend_Signal = 0 (No Clear Trend)
🔶 6. Trend Confirmation with Price Action
Adaptive_ATR_SMA = SMA(Adaptive_ATR, atr_sma_period)
If (Trend_Signal == 1) AND (Close > Short_MA) AND (Adaptive_ATR > Adaptive_ATR_SMA):
Trend_Confirmed = True
Elif (Trend_Signal == -1) AND (Close < Short_MA) AND (Adaptive_ATR > Adaptive_ATR_SMA):
Trend_Confirmed = True
Else:
Trend_Confirmed = False
Local Performance
🔶 7. Multi-Step Take-Profit Mechanism
The strategy employs a 7-step take-profit system
█ Trade Direction
The SuperATR 7-Step Profit Strategy is designed to work in both long and short market conditions. By identifying strong uptrends and downtrends, it allows traders to capitalize on price movements in either direction.
Long Trades: Initiated when the market shows strong upward momentum and the trend is confirmed.
Short Trades: Initiated when the market exhibits strong downward momentum and the trend is confirmed.
█ Usage
To implement the SuperATR 7-Step Profit Strategy:
1. Configure the Strategy Parameters:
- Adjust the short_period, long_period, and momentum_period to match the desired sensitivity.
- Set the trend_strength_threshold to control how strong a trend must be before acting.
2. Set Up the Multi-Step Take-Profit Levels:
- Define ATR multipliers and fixed percentage levels according to risk tolerance and profit goals.
- Specify the percentage of the position to close at each level.
3. Apply the Strategy to a Chart:
- Use the strategy on instruments and timeframes where it has been tested and optimized.
- Monitor the positions and adjust parameters as needed based on performance.
4. Backtest and Optimize:
- Utilize TradingView's backtesting features to evaluate historical performance.
- Adjust the default settings to optimize for different market conditions.
█ Default Settings
Understanding default settings is crucial for optimal performance.
Short Period (3): Affects the responsiveness of the short-term MA.
Effect: Lower values increase sensitivity but may produce more false signals.
Long Period (7): Determines the trend baseline.
Effect: Higher values reduce noise but may delay signals.
Momentum Period (7): Influences adaptive ATR and trend strength.
Effect: Shorter periods react quicker to price changes.
Trend Strength Threshold (0.5): Filters out weaker trends.
Effect: Higher thresholds yield fewer but stronger signals.
ATR Multipliers: Set distances for ATR-based exits.
Effect: Larger multipliers aim for bigger moves but may reduce hit rate.
Fixed TP Levels (%): Control profit-taking on smaller moves.
Effect: Adjusting these levels affects how quickly profits are realized.
Exit Percentages: Determine how much of the position is closed at each TP level.
Effect: Higher percentages reduce exposure faster, affecting risk and reward.
Adjusting these variables allows you to tailor the strategy to different market conditions and personal risk preferences.
By integrating adaptive indicators and a multi-tiered exit strategy, the SuperATR 7-Step Profit Strategy offers a versatile tool for traders seeking to navigate varying market conditions effectively. Understanding and adjusting the key parameters enables traders to harness the full potential of this strategy.
Gabriel's Witcher Strategy [65 Minute Trading Bot]Strategy Description: Gabriel's Witcher Strategy
Author: Gabriel
Platform: TradingView Pine Script (Version 5)
Backtested Asset: Avalanche (Coinbase Brokage for Volume adjustment)
Timeframe: 65 Minutes
Strategy Type: Comprehensive Trend-Following and Momentum Strategy with Scalping and Risk Management Features
Overview
Gabriel's Witcher Strategy is an advanced trading bot designed for the Avalanche pair on a 65-minute timeframe. This strategy integrates a multitude of technical indicators to identify and execute high-probability trading opportunities. By combining trend-following, momentum, volume analysis, and range filtering, the strategy aims to capitalize on both long and short market movements. Additionally, it incorporates scalping mechanisms and robust risk management features, including take-profit (TP) levels and commission considerations, to optimize trade performance and profitability.
====Key Components====
Source Selection:
Custom Source Flexibility: Allows traders to select from a wide range of price and volume sources (e.g., Close, Open, High, Low, HL2, HLC3, OHLC4, VWAP, On-Balance Volume, etc.) for indicator calculations, enhancing adaptability to various trading styles.
Various curves of Volume Analysis are employed:
Tick Volume Calculation: Utilizes tick volume as a fallback when actual volume data is unavailable, ensuring consistency across different data feeds.
Volume Indicators: Incorporates multiple volume-based indicators such as On-Balance Volume (OBV), Accumulation/Distribution (AccDist), Negative Volume Index (NVI), Positive Volume Index (PVI), and Price Volume Trend (PVT) for comprehensive market analysis.
Trend Indicators:
ADX (Average Directional Index): Measures trend strength using either the Classic or Masanakamura method, with customizable length and threshold settings. It's used to open positions when the mesured trend is strong, or exit when its weak.
Jurik Moving Average (JMA): A smooth moving average that reduces lag, configurable with various parameters including source, resolution, and repainting options.
Parabolic SAR: Identifies potential reversals in market trends with adjustable start, increment, and maximum settings.
Custom Trend Indicator: Utilizes highest and lowest price points over a specified timeframe to determine current and previous trend bases, visually represented with color-filled areas.
Momentum Indicators:
Relative Strength Index (RSI): Evaluates the speed and change of price movements, smoothed with a custom length and source. It's used to not enter the market for shorts in oversold or longs for overbought conditions, and to enter for long in oversold or shorts for overboughts.
Momentum-Based Calculations: Employs both Double Exponential Moving Averages (DEMA) on a MACD-based RSI to enhance momentum signal accuracy which is then further accelerated by a Hull MA. This is the technical analysis tool that determines bearish or bullish momentum.
OBV-Based Momentum Conditions: Uses two exponential moving averages of OBV to determine bullish or bearish momentum shifts, anomalities, breakouts where banks flow their funds in or Smart Money Concepts trade.
Moving Averages (MA):
Multiple MA Types: Includes Simple Moving Average (SMA), Exponential Moving Average (EMA), Weighted Moving Average (WMA), Hull Moving Average (HMA), and Volume-Weighted Moving Average (VWMA), selectable via input parameters.
MA Speed Calculation: Measures the percentage change in MA values to determine the direction and speed of the trend.
Range Filtering:
Variance-Based Filter: Utilizes variance and moving averages to filter out trades during low-volatility periods, enhancing trade quality.
Color-Coded Range Indicators: Visualizes range filtering with color changes on the chart for quick assessment.
Scalping Mechanism:
Heikin-Ashi Candles: Optionally uses Heikin-Ashi candles for smoother price action analysis.
EMA-Based Trend Detection: Employs fast, medium, and slow EMAs to determine trend direction and potential entry points.
Fractal-Based Filtering: Detects regular or BW (Black & White) fractals to confirm trade signals.
Take Profit (TP) Management:
Dynamic TP Levels: Calculates TP levels based on the number of consecutive long or short entries, adjusting targets to maximize profits.
TP Signals and Re-Entry: Plots TP signals on the chart and allows for automatic re-entry upon TP hit, maintaining continuous trade flow.
Risk Management:
Commission Integration: Accounts for trading commissions to ensure net profitability.
Position Sizing: Configured to use a percentage of equity for each trade, adjustable via input parameters.
Pyramiding: Allows up to one additional position per direction to enhance gains during strong trends.
Alerts and Visual Indicators:
Buy/Sell Signals: Plots visual indicators (triangles and flags) on the chart to signify entry and TP points.
Bar Coloring: Changes bar colors based on ADX and trend conditions for immediate visual cues.
Price Levels: Marks significant price levels related to TP and position entries with cross styles.
Input Parameters
Source Settings:
Custom Sources (srcinput): Choose from various price and volume sources to tailor indicator calculations.
ADX Settings:
ADX Type (ADX_options): Select between 'CLASSIC' and 'MASANAKAMURA' methods.
ADX Length (ADX_len): Defines the period for ADX calculation.
ADX Threshold (th): Sets the minimum ADX value to consider a strong trend.
RSI Settings:
RSI Length (len_3): Period for RSI calculation.
RSI Source (src_3): Source data for RSI.
Trend Strength Settings:
Channel Length (n1): Period for trend channel calculation.
Average Length (n2): Period for smoothing trend strength.
Jurik Moving Average (JMA) Settings:
JMA Source (inp): Source data for JMA.
JMA Resolution (reso): Timeframe for JMA calculation.
JMA Repainting (rep): Option to allow JMA to repaint.
JMA Length (lengths): Period for JMA.
Parabolic SAR Settings:
SAR Start (start): Initial acceleration factor.
SAR Increment (increment): Acceleration factor increment.
SAR Maximum (maximum): Maximum acceleration factor.
SAR Point Width (width): Visual width of SAR points.
Trend Indicator Settings:
Trend Timeframe (timeframe): Period for trend indicator calculations.
Momentum Settings:
Source Type (srcType): Select between 'Price' and 'VWAP'.
Momentum Source (srcPrice): Source data for momentum calculations.
RSI Length (rsiLen): Period for momentum RSI.
Smooth Length (sLen): Smoothing period for momentum RSI.
OBV Settings:
OBV Line 1 (e1): EMA period for OBV line 1.
OBV Line 2 (e2): EMA period for OBV line 2.
Moving Average (MA) Settings:
MA Length (length): Period for MA calculations.
MA Type (matype): Select MA type (1: SMA, 2: EMA, 3: HMA, 4: WMA, 5: VWMA).
Range Filter Settings:
Range Filter Length (length0): Period for range filtering.
Range Filter Multiplier (mult): Multiplier for range variance.
Take Profit (TP) Settings:
TP Long (tp_long0): Percentage for long TP.
TP Short (tp_short0): Percentage for short TP.
Scalping Settings:
Scalping Activation (ACT_SCLP): Enable or disable scalping.
Scalping Length (HiLoLen): Period for scalping indicators.
Fast EMA Length (fastEMAlength): Period for fast EMA in scalping.
Medium EMA Length (mediumEMAlength): Period for medium EMA in scalping.
Slow EMA Length (slowEMAlength): Period for slow EMA in scalping.
Filter (filterBW): Enable or disable additional fractal filtering.
Pullback Lookback (Lookback): Number of bars for pullback consideration.
Use Heikin-Ashi Candles (UseHAcandles): Option to use Heikin-Ashi candles for smoother trend analysis.
Strategy Logic
Indicator Calculations:
Volume and Source Selection: Determines the primary data source based on user input, ensuring flexibility and adaptability.
ADX Calculation: Computes ADX using either the Classic or Masanakamura method to assess trend strength.
RSI Calculation: Evaluates market momentum using RSI, further smoothed with custom periods.
Trend Strength Assessment: Utilizes trend channel and average lengths to gauge the robustness of current trends.
Jurik Moving Average (JMA): Smooths price data to reduce lag and enhance trend detection.
Parabolic SAR: Identifies potential trend reversals with adjustable parameters for sensitivity.
Momentum Analysis: Combines RSI with DEMA and OBV-based conditions to confirm bullish or bearish momentum.
Moving Averages: Employs multiple MA types to determine trend direction and speed.
Range Filtering: Filters out low-volatility periods to focus on high-probability trades.
Trade Conditions:
Long Entry Conditions:
ADX Confirmation: ADX must be above the threshold, indicating a strong uptrend.
RSI and Momentum: RSI below 70 and positive momentum signals.
JMA and SAR: JMA indicates an uptrend, and Parabolic SAR is below the price.
Trend Indicator: Confirms the current trend direction.
Range Filter: Ensures market is in an upward range.
Scalping Option: If enabled, additional scalping conditions must be met.
Short Entry Conditions:
ADX Confirmation: ADX must be above the threshold, indicating a strong downtrend.
RSI and Momentum: RSI above 30 and negative momentum signals.
JMA and SAR: JMA indicates a downtrend, and Parabolic SAR is above the price.
Trend Indicator: Confirms the current trend direction.
Range Filter: Ensures market is in a downward range.
Scalping Option: If enabled, additional scalping conditions must be met.
Position Management:
Entry Execution: Places long or short orders based on the identified conditions and user-selected position types (Longs, Shorts, or Both).
Take Profit (TP): Automatically sets TP levels based on predefined percentages, adjusting dynamically with consecutive trades.
Re-Entry Mechanism: Allows for automatic re-entry upon TP hit, maintaining active trading positions.
Exit Conditions: Closes positions when TP levels are reached or when opposing trend signals are detected.
Visual Indicators:
Bar Coloring: Highlights bars in green for bullish conditions, red for bearish, and orange for neutral.
Plotting Price Levels: Marks significant price levels related to TP and trade entries with cross symbols.
Signal Shapes: Displays triangle and flag shapes on the chart to indicate trade entries and TP hits.
Alerts:
Custom Alerts: Configured to notify traders of long entries, short entries, and TP hits, enabling timely trade management and execution.
Usage Instructions
Setup:
Apply the Strategy: Add the script to your TradingView chart set to BTCUSDT with a 65-minute timeframe.
Configure Inputs: Adjust the input parameters under their respective groups (e.g., Source Settings, ADX, RSI, Trend Strength, etc.) to match your trading preferences and risk tolerance.
Position Selection:
Choose Position Type: Use the Position input to select Longs, Shorts, or Both based on your market outlook.
Execution: The strategy will automatically execute and manage positions according to the selected type, ensuring targeted trading actions.
Signal Interpretation:
Buy Signals: Blue triangles below the bars indicate potential long entry points.
Sell Signals: Red triangles above the bars indicate potential short entry points.
Take Profit Signals: Flags above or below the bars signify TP hits for long and short positions, respectively.
Bar Colors: Green bars suggest bullish conditions, red bars indicate bearish conditions, and orange bars represent neutral or consolidating markets.
Risk Management:
Default Position Size: Set to 100% of equity. Adjust the default_qty_value as needed for your risk management strategy.
Commission: Accounts for a 0.1% commission per trade. Adjust the commission_value to match your broker's fees.
Pyramiding: Allows up to one additional position per direction to enhance gains during strong trends.
Backtesting and Optimization:
Historical Testing: Utilize TradingView's backtesting features to evaluate the strategy's performance over historical data.
Parameter Tuning: Optimize input parameters to align the strategy with current market dynamics and personal trading objectives.
Alerts Configuration:
Set Up Alerts: Enable and configure alerts based on the predefined alertcondition statements to receive real-time notifications of trade signals and TP hits.
Additional Features
Comprehensive Indicator Integration: Combines multiple technical indicators to provide a holistic view of market conditions, enhancing trade signal accuracy.
Scalping Options: Offers an optional scalping mechanism to capitalize on short-term price movements, increasing trading flexibility.
Dynamic Take Profit Levels: Adjusts TP targets based on the number of consecutive trades, maximizing profit potential during favorable trends.
Advanced Volume Analysis: Utilizes various volume indicators to confirm trend strength and validate trade signals.
Customizable Range Filtering: Filters trades based on market volatility, ensuring trades are taken during optimal conditions.
Heikin-Ashi Candle Support: Optionally uses Heikin-Ashi candles for smoother price action analysis and reduced noise.
====Recommendations====
Thorough Backtesting:
Historical Performance: Before deploying the strategy in a live trading environment, perform comprehensive backtesting to understand its performance under various market conditions. These are the premium settings for Avalanche Coinbase.
Optimization: Regularly review and adjust input parameters to ensure the strategy remains effective amidst changing market volatility and trends. Backtest the strategy for each crypto and make sure you are in the right brokage when using the volume sources as it will affect the overall outcome of the trading strategy.
Risk Management:
Position Sizing: Adjust the default_qty_value to align with your risk tolerance and account size.
Stop-Loss Implementation: Although the strategy includes TP levels, they're also consided to be a stop-loss mechanisms to protect against adverse market movements.
Commission Adjustment: Ensure the commission_value accurately reflects your broker's fees to maintain realistic backtesting results. Generally, 0.1~0.3% are most of the average broker's comission fees.
Slipage: The slip comssion is 1 Tick, since the strategy is adjusted to only enter/exit on bar close where most positions are available.
Continuous Monitoring:
Strategy Performance: Regularly monitor the strategy's performance to ensure it operates as expected and make adjustments as needed. A max-drawndown hit has been added to operate in case the premium Avalanche settings go wrong, but you can turn it off an adjust the equity percentage to 50% if you are confortable with the high volatile max-drown or even 100% if your account allows you to borrow cash.
Customization:
Indicator Parameters: Tailor indicator settings (e.g., ADX length, RSI period, MA types) to better fit your specific trading style and market conditions.
Scalping Options: Enable or disable scalping based on your trading preferences and risk appetite.
Conclusion
Gabriel's Witcher Strategy is a robust and versatile trading solution designed to navigate the complexities of the Crypto market. By integrating a wide array of technical indicators and providing extensive customization options, this strategy empowers traders to execute informed and strategic trades. Its comprehensive approach, combining trend analysis, momentum detection, volume evaluation, and range filtering, ensures that trades are taken during optimal market conditions. Additionally, the inclusion of scalping features and dynamic take-profit management enhances the strategy's adaptability and profitability potential. Unlike any trading strategy, with both diligent testing and continuous monitoring under the strategy tester, it's possible to achieve sustained success by adjusting the settings to the individual Crypto that need it, for example this one is preset for Avalanche Coinbase 65 Miinutes but it can be adjust for BTCUSD or Etherium if you backtest and search for the right settings.
DRM StrategyOne of the ways I go when I develop strategies is by reducing the number of parameters and removing fixed parameters and levels.
In this strategy, I'm trying to create an RSI indicator with a dynamic length.
Length is computed based on the correlation between Price and its momentum.
You can set min and max values for the RSI, and if the correlation is close to 1, we'll be at a min RSI value. When it's -1, we'll be at the max level.
I got this idea from Sofien Kaabar's book.
The strategy is super simple, and there might be much room for improvement.
Performance on the deep backtesting is not excellent, so I think the strategy needs some filters for regimes, etc.
Thanks to @MUQWISHI for helping me code it.
Disclaimer
Please remember that past performance may not indicate future results.
Due to various factors, including changing market conditions, the strategy may no longer perform as well as in historical backtesting.
This post and the script don’t provide any financial advice.
Kernel Regression Envelope with SMI OscillatorThis script combines the predictive capabilities of the **Nadaraya-Watson estimator**, implemented by the esteemed jdehorty (credit to him for his excellent work on the `KernelFunctions` library and the original Nadaraya-Watson Envelope indicator), with the confirmation strength of the **Stochastic Momentum Index (SMI)** to create a dynamic trend reversal strategy. The core idea is to identify potential overbought and oversold conditions using the Nadaraya-Watson Envelope and then confirm these signals with the SMI before entering a trade.
**Understanding the Nadaraya-Watson Envelope:**
The Nadaraya-Watson estimator is a non-parametric regression technique that essentially calculates a weighted average of past price data to estimate the current underlying trend. Unlike simple moving averages that give equal weight to all past data within a defined period, the Nadaraya-Watson estimator uses a **kernel function** (in this case, the Rational Quadratic Kernel) to assign weights. The key parameters influencing this estimation are:
* **Lookback Window (h):** This determines how many historical bars are considered for the estimation. A larger window results in a smoother estimation, while a smaller window makes it more reactive to recent price changes.
* **Relative Weighting (alpha):** This parameter controls the influence of different time frames in the estimation. Lower values emphasize longer-term price action, while higher values make the estimator more sensitive to shorter-term movements.
* **Start Regression at Bar (x\_0):** This allows you to exclude the potentially volatile initial bars of a chart from the calculation, leading to a more stable estimation.
The script calculates the Nadaraya-Watson estimation for the closing price (`yhat_close`), as well as the highs (`yhat_high`) and lows (`yhat_low`). The `yhat_close` is then used as the central trend line.
**Dynamic Envelope Bands with ATR:**
To identify potential entry and exit points around the Nadaraya-Watson estimation, the script uses **Average True Range (ATR)** to create dynamic envelope bands. ATR measures the volatility of the price. By multiplying the ATR by different factors (`nearFactor` and `farFactor`), we create multiple bands:
* **Near Bands:** These are closer to the Nadaraya-Watson estimation and are intended to identify potential immediate overbought or oversold zones.
* **Far Bands:** These are further away and can act as potential take-profit or stop-loss levels, representing more extreme price extensions.
The script calculates both near and far upper and lower bands, as well as an average between the near and far bands. This provides a nuanced view of potential support and resistance levels around the estimated trend.
**Confirming Reversals with the Stochastic Momentum Index (SMI):**
While the Nadaraya-Watson Envelope identifies potential overextended conditions, the **Stochastic Momentum Index (SMI)** is used to confirm a potential trend reversal. The SMI, unlike a traditional stochastic oscillator, oscillates around a zero line. It measures the location of the current closing price relative to the median of the high/low range over a specified period.
The script calculates the SMI on a **higher timeframe** (defined by the "Timeframe" input) to gain a broader perspective on the market momentum. This helps to filter out potential whipsaws and false signals that might occur on the current chart's timeframe. The SMI calculation involves:
* **%K Length:** The lookback period for calculating the highest high and lowest low.
* **%D Length:** The period for smoothing the relative range.
* **EMA Length:** The period for smoothing the SMI itself.
The script uses a double EMA for smoothing within the SMI calculation for added smoothness.
**How the Indicators Work Together in the Strategy:**
The strategy enters a long position when:
1. The closing price crosses below the **near lower band** of the Nadaraya-Watson Envelope, suggesting a potential oversold condition.
2. The SMI crosses above its EMA, indicating positive momentum.
3. The SMI value is below -50, further supporting the oversold idea on the higher timeframe.
Conversely, the strategy enters a short position when:
1. The closing price crosses above the **near upper band** of the Nadaraya-Watson Envelope, suggesting a potential overbought condition.
2. The SMI crosses below its EMA, indicating negative momentum.
3. The SMI value is above 50, further supporting the overbought idea on the higher timeframe.
Trades are closed when the price crosses the **far band** in the opposite direction of the trade. A stop-loss is also implemented based on a fixed value.
**In essence:** The Nadaraya-Watson Envelope identifies areas where the price might be deviating significantly from its estimated trend. The SMI, calculated on a higher timeframe, then acts as a confirmation signal, suggesting that the momentum is shifting in the direction of a potential reversal. The ATR-based bands provide dynamic entry and exit points based on the current volatility.
**How to Use the Script:**
1. **Apply the script to your chart.**
2. **Adjust the "Kernel Settings":**
* **Lookback Window (h):** Experiment with different values to find the smoothness that best suits the asset and timeframe you are trading. Lower values make the envelope more reactive, while higher values make it smoother.
* **Relative Weighting (alpha):** Adjust to control the influence of different timeframes on the Nadaraya-Watson estimation.
* **Start Regression at Bar (x\_0):** Increase this value if you want to exclude the initial, potentially volatile, bars from the calculation.
* **Stoploss:** Set your desired stop-loss value.
3. **Adjust the "SMI" settings:**
* **%K Length, %D Length, EMA Length:** These parameters control the sensitivity and smoothness of the SMI. Experiment to find settings that work well for your trading style.
* **Timeframe:** Select the higher timeframe you want to use for SMI confirmation.
4. **Adjust the "ATR Length" and "Near/Far ATR Factor":** These settings control the width and sensitivity of the envelope bands. Smaller ATR lengths make the bands more reactive to recent volatility.
5. **Customize the "Color Settings"** to your preference.
6. **Observe the plots:**
* The **Nadaraya-Watson Estimation (yhat)** line represents the estimated underlying trend.
* The **near and far upper and lower bands** visualize potential overbought and oversold zones based on the ATR.
* The **fill areas** highlight the regions between the near and far bands.
7. **Look for entry signals:** A long entry is considered when the price touches or crosses below the lower near band and the SMI confirms upward momentum. A short entry is considered when the price touches or crosses above the upper near band and the SMI confirms downward momentum.
8. **Manage your trades:** The script provides exit signals when the price crosses the far band. The fixed stop-loss will also close trades if the price moves against your position.
**Justification for Combining Nadaraya-Watson Envelope and SMI:**
The combination of the Nadaraya-Watson Envelope and the SMI provides a more robust approach to identifying potential trend reversals compared to using either indicator in isolation. The Nadaraya-Watson Envelope excels at identifying potential areas where the price is overextended relative to its recent history. However, relying solely on the envelope can lead to false signals, especially in choppy or volatile markets. By incorporating the SMI as a confirmation tool, we add a momentum filter that helps to validate the potential reversals signaled by the envelope. The higher timeframe SMI further helps to filter out noise and focus on more significant shifts in momentum. The ATR-based bands add a dynamic element to the entry and exit points, adapting to the current market volatility. This mashup aims to leverage the strengths of each indicator to create a more reliable trading strategy.
Intraday Alpha Pro - ORB + Trend/MomentumOverview
This is a pure intraday trading strategy designed for active traders seeking to capitalize on short-term price movements using two complementary modules: Opening Range Breakout (ORB) and Trend/Momentum. The strategy operates strictly within a user-defined trading session, automatically flattening all positions at session end to avoid overnight carry. It employs a points-based exit system with a trailing stop that activates only after the target is reached, ensuring disciplined risk management. Optional Martingale position sizing is included for users who prefer aggressive scaling after losses.Key Features Pure Intraday, No Carry: Trades are confined to a user-defined session (default: 9:15 AM–3:25 PM, Monday–Sunday). All positions are closed at session end.
Non-Repainting: Entries are evaluated only on confirmed bar closes (barstate.isconfirmed), ensuring no lookahead or repainting.
Dual Signal Modules: Opening Range Breakout (ORB): Captures breakouts above/below the high/low of a user-defined opening range (default: 9:15 AM–9:30 AM).
Trend/Momentum: Combines EMA (9/21) crossovers, RSI filters, volume confirmation, and an optional 200-period MA trend filter for robust trend-following signals.
Points-Based Exits: Uses fixed stop-loss (slPoints, default 16 points) and take-profit (tpPoints, default 32 points) distances. Once the take-profit level is reached, a trailing stop (trailDistPts, default 10 points) activates, ratcheting monotonically to lock in gains.
Martingale Sizing (Optional): Allows position size increases after losses (up to maxQtyInput) with a reset option after wins.
Cooldown Period: Prevents immediate re-entries after exits using a configurable cooldown (cooldownBars).
Flexible Inputs: Toggle long/short entries, enable/disable ORB or Trend/Momentum modules, and customize all parameters (e.g., MA lengths, RSI thresholds, volume multiplier).
Visuals & Alerts: Plots ORB high/low lines and moving averages (9, 21, 200). Includes alerts for long/short entries and end-of-day flattening.
How It Works Session Management: Trades only within the specified tradeSes (default: 9:15 AM–3:25 PM). The ORB module uses a separate orbSes (default: 9:15 AM–9:30 AM) to calculate breakout levels. Positions are closed automatically at session end.
Entry Conditions: ORB: Long when price closes above the ORB high after the ORB session ends; short when price closes below the ORB low.
Trend/Momentum: Long on fast MA (default EMA 9) crossing above slow MA (default EMA 21), with RSI above rsiBuy (default 55), volume exceeding volMult (default 1.5x prior bar), and price above the 200-period MA (if enabled). Shorts use the inverse.
Exit Logic: Stop-loss is set at entry price ± slPoints.
Take-profit is monitored using a running high/low since entry. Once price moves tpPoints in profit, the stop trails at trailDistPts behind the current price, adjusting only in the favorable direction (never loosening).
Exits use strategy.exit with stop only (no limit orders).
Position Sizing: Default size is baseQtyInput (minimum 1 contract). With useMartingale enabled, size increases by martingaleFactor after a loss, capped at maxQtyInput. If resetOnWin is true, size resets to baseQtyInput after a winning trade.
Cooldown: After an exit, no new trades are allowed for cooldownBars to prevent overtrading.
Futures-Safe Volume: Volume filter accommodates markets with missing or zero volume data (e.g., futures), ensuring signals aren’t blocked unnecessarily.
Inputs Trading Session: tradeSes (e.g., "0915-1525:1234567") and orbSes (e.g., "0915-0930:1234567").
Toggles: enableLong, enableShort, useORB, useTrendMom, useTrendFilter (200-MA).
Trend/Momentum: maType (EMA/SMA), fastLen (9), slowLen (21), trendLen (200), rsiLen (14), rsiBuy (55), rsiSell (45), volMult (1.5).
Exits: slPoints (16), tpPoints (32), trailDistPts (10).
Martingale: useMartingale, baseQtyInput, maxQtyInput, martingaleFactor, resetOnWin.
Cooldown: cooldownBars (1).
Legacy (Ignored): tp1RR, tp2RR, tp3RR, tp1Pct, tp2Pct, tp3Pct, stepTrail for backward compatibility.
Usage Notes Best suited for liquid, intraday markets (e.g., futures like ES, NQ, or forex pairs).
Adjust slPoints, tpPoints, and trailDistPts to match instrument volatility.
Use useMartingale cautiously, as it increases risk after losses.
Ensure tradeSes and orbSes align with your market’s trading hours.
Alerts can be set for long/short entries and EOD flattening.
The strategy avoids lookahead and repainting, ensuring reliability in live trading.
Risk Warning
Trading involves significant risk. Backtest thoroughly and use appropriate risk management. The Martingale option can amplify losses if not carefully monitored. Past performance is not indicative of future results.
Slight Swing Momentum Strategy.Introduction:
The Swing Momentum Strategy is a quantitative trading strategy designed to capture mid-term opportunities in the financial markets by combining swing trading principles with momentum indicators. It utilizes a combination of technical indicators, including moving averages, crossover signals, and volume analysis, to generate buy and sell signals. The strategy aims to identify market trends and capitalize on price momentum for profit generation.
Highlights:
The strategy offers several key highlights that make it unique and potentially attractive to traders:
Swing Trading with Momentum: The strategy combines the principles of swing trading, which aim to capture short-to-medium-term price swings, with momentum indicators that help identify strong price trends and potential breakout opportunities.
Technical Indicator Optimization: The strategy utilizes a selection of optimized technical indicators, including moving averages and crossover signals, to filter out the noise and focus on high-probability trading setups. This optimization enhances the strategy's ability to identify favourable entry and exit points.
Risk Management: The strategy incorporates risk management techniques, such as position sizing based on equity and dynamic stop loss levels, to manage risk exposure and protect capital. This helps to minimize drawdowns and preserve profits.
Buy Condition:
The buy condition in the strategy is determined by a combination of factors, including A1, A2, A3, XG, and weeklySlope. Let's break it down:
A1 Condition: The A1 condition checks for specific price relationships. It verifies that the ratio of the highest price to the closing price is less than 1.03, the ratio of the opening price to the lowest price is less than 1.03, and the ratio of the highest price to the previous day's closing price is greater than 1.06. This condition looks for a specific pattern indicating potential bullish momentum.
A2 Condition: The A2 condition checks for price relationships related to the closing price. It verifies that the ratio of the closing price to the opening price is greater than 1.05 or that the ratio of the closing price to the previous day's closing price is greater than 1.05. This condition looks for signs of upward price movement and momentum.
A3 Condition: The A3 condition focuses on volume. It checks if the current volume crosses above the highest volume over the last 60 periods. This condition aims to identify increased buying interest and potentially confirms the strength of the potential upward price movement.
XG Condition: The XG condition combines the A1 and A2 conditions and checks if they are true for both the current and previous bars. It also verifies that the ratio of the closing price to the 5-period EMA crosses above the 9-period SMA of the same ratio. This condition helps identify potential buy signals when multiple factors align, indicating a strong bullish momentum and potential entry point.
Weekly Trend Factor: The weekly slope condition calculates the slope of the 50-period SMA over a weekly timeframe. It checks if the slope is positive, indicating an overall upward trend on a weekly basis. This condition provides additional confirmation that the stock is in an upward trend.
When all of these conditions align, the buy condition is triggered, indicating a favourable time to enter a long position.
Sell Condition:
The sell condition is relatively straightforward in the strategy:
Sell Signal: The sell condition simply checks if the closing price crosses below the 10-period EMA. When this condition is met, it indicates a potential reversal or weakening of the upward price momentum, and a sell signal is generated.
Backtest Outcome:
The strategy was backtested over the period from January 22nd, 1999 to May 3rd, 2023, using daily candlestick charts for the NASDAQ: NVDA. The strategy used an initial capital of 1,000,000 USD, The order quantity is defined as 10% of the equity. The strategy allows for pyramiding with 1 order, and the transaction fee is set at 0.03% per trade. Here are the key outcomes of the backtest:
Net Profit: 539,595.84 USD, representing a return of 53.96%.
Percent Profitable: 48.82%
Total Closed Trades: 127
Profit Factor: 2.331
Max Drawdown: 68,422.70 USD
Average Trade: 4,248.79 USD
Average Number of Bars in Trades: 11, indicating the average duration of the trades.
Conclusion:
In conclusion, the Swing Momentum Strategy is a quantitative trading approach that combines swing trading principles with momentum indicators to identify and capture mid term trading opportunities. The strategy has demonstrated promising results during backtesting, including a significant net profit and a favourable profit factor.
