Follow Line Strategy Version 2.5 (React HTF)Follow Line Strategy v2.5 (React HTF) - TradingView Script Usage
This strategy utilizes a "Follow Line" concept based on Bollinger Bands and ATR to identify potential trading opportunities. It includes advanced features like optional working hours filtering, higher timeframe (HTF) trend confirmation, and improved trend-following entry/exit logic. Version 2.5 introduces reactivity to HTF trend changes for more adaptive trading.
Key Features:
Follow Line: The core of the strategy. It dynamically adjusts based on price breakouts beyond Bollinger Bands, using either the low/high or ATR-adjusted levels.
Bollinger Bands: Uses a standard Bollinger Bands setup to identify overbought/oversold conditions.
ATR Filter: Optionally uses the Average True Range (ATR) to adjust the Follow Line offset, providing a more dynamic and volatility-adjusted entry point.
Optional Trading Session Filter: Allows you to restrict trading to specific hours of the day.
Higher Timeframe (HTF) Confirmation: A significant feature that allows you to confirm trade signals with the trend on a higher timeframe. This can help to filter out false signals and improve the overall win rate.
HTF Selection Method: Choose between Auto and Manual HTF selection:
Auto: The script automatically determines the appropriate HTF based on the current chart timeframe (e.g., 1min -> 15min, 5min -> 4h, 1h -> 1D, Daily -> Monthly).
Manual: Allows you to select a specific HTF using the Manual Higher Timeframe input.
Trend-Following Entries/Exits: The strategy aims to enter trades in the direction of the established trend, using the Follow Line to define the trend.
Reactive HTF Trend Changes: v2.5 exits positions not only based on the trade timeframe (TTF) trend changing, but also when the higher timeframe trend reverses against the position. This makes the strategy more responsive to larger market movements.
Alerts: Provides buy and sell alerts for convenient trading signal notifications.
Visualizations: Plots the Follow Line for both the trade timeframe and the higher timeframe (optional), making it easy to understand the strategy's logic.
How to Use:
Add to Chart: Add the "Follow Line Strategy Version 2.5 (React HTF)" script to your TradingView chart.
Configure Settings: Customize the strategy's settings to match your trading style and preferences. Here's a breakdown of the key settings:
Indicator Settings:
ATR Period: The period used to calculate the ATR. A smaller period is more sensitive to recent price changes.
Bollinger Bands Period: The period used for the Bollinger Bands calculation. A longer period results in smoother bands.
Bollinger Bands Deviation: The number of standard deviations from the moving average that the Bollinger Bands are plotted. Higher deviations create wider bands.
Use ATR for Follow Line Offset?: Enable to use ATR to calculate the Follow Line offset. Disable to use the simple high/low.
Show Trade Signals on Chart?: Enable to show BUY/SELL labels on the chart.
Time Filter:
Use Trading Session Filter?: Enable to restrict trading to specific hours of the day.
Trading Session: The trading session to use (e.g., 0930-1600 for regular US stock market hours). Use 0000-2400 for all hours.
Higher Timeframe Confirmation:
Enable HTF Confirmation?: Enable to use the HTF trend to filter trade signals. If enabled, only trades in the direction of the HTF trend will be taken.
HTF Selection Method: Choose between "Auto" and "Manual" HTF selection.
Manual Higher Timeframe: If "Manual" is selected, choose the specific HTF (e.g., 240 for 4 hours, D for daily).
Show HTF Follow Line?: Enable to plot the HTF Follow Line on the chart.
Understanding the Signals:
Buy Signal: The price breaks above the upper Bollinger Band, and the HTF (if enabled) confirms the uptrend.
Sell Signal: The price breaks below the lower Bollinger Band, and the HTF (if enabled) confirms the downtrend.
Exit Long: The trade timeframe trend changes to downtrend or the higher timeframe trend changes to downtrend.
Exit Short: The trade timeframe trend changes to uptrend or the higher timeframe trend changes to uptrend.
Alerts:
The script includes alert conditions for buy and sell signals. To set up alerts, click the "Alerts" button in TradingView and select the desired alert condition from the script. The alert message provides the ticker and interval.
Backtesting and Optimization:
Use TradingView's Strategy Tester to backtest the strategy on different assets and timeframes.
Experiment with different settings to optimize the strategy for your specific trading style and risk tolerance. Pay close attention to the ATR Period, Bollinger Bands settings, and the HTF confirmation options.
Tips and Considerations:
HTF Confirmation: The HTF confirmation can significantly improve the strategy's performance by filtering out false signals. However, it can also reduce the number of trades.
Risk Management: Always use proper risk management techniques, such as stop-loss orders and position sizing, when trading any strategy.
Market Conditions: The strategy may perform differently in different market conditions. It's important to backtest and optimize the strategy for the specific markets you are trading.
Customization: Feel free to modify the script to suit your specific needs. For example, you could add additional filters or entry/exit conditions.
Pyramiding: The pyramiding = 0 setting prevents multiple entries in the same direction, ensuring the strategy doesn't compound losses. You can adjust this value if you prefer to pyramid into winning positions, but be cautious.
Lookahead: The lookahead = barmerge.lookahead_off setting ensures that the HTF data is calculated based on the current bar's closed data, preventing potential future peeking bias.
Trend Determination: The logic for determining the HTF trend and reacting to changes is critical. Carefully review the f_calculateHTFData function and the conditions for exiting positions to ensure you understand how the strategy responds to different market scenarios.
Disclaimer:
This script is for informational and educational purposes only. It is not financial advice, and you should not trade based solely on the signals generated by this script. Always do your own research and consult with a qualified financial advisor before making any trading decisions. The author is not responsible for any losses incurred as a result of using this script.
Penunjuk dan strategi
EMA Crossover (Short Focus with Trailing Stop)This strategy utilizes a combination of Exponential Moving Averages (EMA) and Simple Moving Averages (SMA) to generate entry and exit signals for both long and short positions. The core of the strategy is based on the 13-period EMA (short EMA) crossing the 33-period EMA (long EMA) for entering long trades, while a 13-period EMA crossing the 25-period EMA (mid EMA) generates short trade signals. The 100-period SMA and 200-period SMA serve as additional trend indicators to provide context for the market conditions. The strategy aims to capitalize on trend reversals and momentum shifts in the market.
The strategy is designed to execute trades swiftly with an emphasis on entering positions when conditions align in real time. For long entries, the strategy initiates a buy when the 13 EMA is greater than the 33 EMA, indicating a bullish trend. For short entries, the 13 EMA crossing below the 33 EMA signals a bearish trend, prompting a short position. Importantly, the code includes built-in exit conditions for both long and short positions. Long positions are exited when the 13 EMA falls below the 33 EMA, while short positions are closed when the 13 EMA crosses above the 25 EMA.
A key feature of the strategy is the use of trailing stops for both long and short positions. This dynamic exit method adjusts the stop level as the market moves in favor of the trade, locking in profits while reducing the risk of losses. The trailing stop for long positions is based on the high price of the current bar, while the trailing stop for short positions is set using the low price, providing more flexibility in managing risk. This trailing stop mechanism helps to capture profits from favorable market moves while ensuring that positions are exited if the market moves against them.
This strategy works best on the 4H timeframe and is optimized for major cryptocurrency pairs. The daily chart allows for the EMAs to provide more reliable signals, as the strategy is designed to capture broader trends rather than short-term market fluctuations. Using it on major crypto pairs increases its effectiveness as these assets tend to have strong and sustained trends, providing better opportunities for the strategy to perform well.
Gold EMA + CHOCH StrategyStrategy Logic:
Higher Timeframe (15 min):
Bullish: HTF_20EMA > HTF_100EMA and forming H.H
Bearish: HTF_20EMA < HTF_100EMA and Forming L.L
Lower Timeframe (1 min):
Entry when 20 EMA crosses 100 EMA:
Buy if 20 EMA crosses above 100 EMA and 1 min CHOCH and HTF trend is bullish
Sell if 20 EMA crosses below 100 EMA and1 minCHOCH and HTF trend is bearish
EMA+SMA+VWAP Trading Strategy This strategy is for COINBASE:ETHUSD 15min. Tweak the INPUTS as per requirement.
Note: The strategy will give different results for different sources(Binance, Bitstamp) and symbols.
For more accurate P&L in "Strategy Tester" modify the settings as below:
Under "Properties" tab
--Change "Order Size" value (default is 1) and type from "% of equity" to "Contract".
--Add "Commission". For me commission was "0.07 %".
Strategy Explanation
Trend Following: The strategy uses EMA crossovers (17 vs. 31) to detect momentum shifts, with VWAP and SMA (69) acting as filters to confirm the broader trend.
Reversal Mechanism: It allows switching directly from long to short (or vice versa) by closing the existing position before entering the new one.
Exit Strategy: Faster EMAs (8 and 9) are used for exits, making the strategy sensitive to short-term reversals while avoiding premature exits during strong trends.
Risk Management: The use of multiple filters (VWAP, SMA) reduces false signals, though it may delay entries in fast-moving markets.
How It Works:
Bullish Scenario: If the 17-period EMA crosses above the 31-period EMA, and the price is above both VWAP and the 69-period SMA, a long position is opened. It exits when the 8-period EMA crosses below the 9-period EMA.
Bearish Scenario: If the 17-period EMA crosses below the 31-period EMA, and the price is below both VWAP and the 69-period SMA, a short position is opened. It exits when the 8-period EMA crosses above the 9-period EMA.
Reversal: If a short position is active and a long signal triggers, the short is closed before entering the long (and vice versa).
Potential Strengths
Combines momentum (EMA crossovers) with trend confirmation (VWAP, SMA).
Reversal logic allows flexibility in choppy markets.
Visual indicators make it easy to monitor signals.
Potential Weaknesses
Multiple conditions may reduce trade frequency, missing some opportunities.
Sensitivity to EMA periods; defaults (17, 31, 8, 9, 69) may not suit all assets or timeframes.
No explicit stop-loss or take-profit logic, relying solely on EMA exits.
EMA Crossover (New Trailing Stop)This strategy utilizes a combination of Exponential Moving Averages (EMA) to generate entry and exit signals for both long and short positions. The core of the strategy is based on the 13-period EMA (short EMA) crossing the 33-period EMA (long EMA) for entering long trades, while a 13-period EMA crossing the 25-period EMA (mid EMA) generates short trade signals. The strategy aims to capitalize on trend reversals and momentum shifts in the market.
A key enhancement in this strategy is the inclusion of slippage, set at 5 ticks, to simulate more realistic trading conditions. Slippage accounts for the difference between the expected price of a trade and the actual price, providing a more accurate representation of real-world trading scenarios.
Stack Overflow
To address the issue of overlapping exit orders, the strategy incorporates a flag (isExiting) to track whether an exit has been processed. This ensures that only one exit order is generated per bar, preventing multiple exits from overlapping and resulting in clearer trade execution.
The strategy is designed to execute trades swiftly, emphasizing real-time entry when conditions align. For long entries, the strategy initiates a buy when the 13 EMA is greater than the 33 EMA, indicating a bullish trend. For short entries, the 13 EMA crossing below the 33 EMA signals a bearish trend, prompting a short position. Importantly, the code includes built-in exit conditions for both long and short positions. Long positions are exited when the 13 EMA falls below the 33 EMA, while short positions are closed when the 13 EMA crosses above the 25 EMA.
A notable feature of the strategy is the use of trailing stops for both long and short positions. This dynamic exit method adjusts the stop level as the market moves favorably, locking in profits while reducing the risk of losses. The trailing stop for long positions is based on the high price of the current bar, while the trailing stop for short positions is set using the low price, providing flexibility in managing risk. This mechanism helps capture profits from favorable market movements while ensuring positions are exited if the market moves against them.
In summary, this strategy combines EMA crossovers with realistic trading conditions, including slippage and non-overlapping exits, to effectively identify and act upon market trends. This strategy works best on the 4H/Daily timeframe and is optimized for major cryptocurrency pairs. The 4H/Daily chart allows for the EMAs to provide more reliable signals, as the strategy is designed to capture broader trends rather than short-term market fluctuations. Using it on major crypto pairs increases its effectiveness as these assets tend to have strong and sustained trends, providing better opportunities for the strategy to perform well.
Enhanced Elliott Wave + SMCThe Pine Script you provided is a sophisticated trading strategy called "Enhanced Elliott Wave + SMC" (Smart Money Concepts) that combines multiple technical analysis concepts to generate trade signals. Here's a breakdown of its key components and functionality:
1. Core Concepts
Elliott Wave Theory: Identifies potential wave patterns using a 50-period SMA to determine trend direction and Fibonacci extensions (1.618 ratio) for price targets.
Smart Money Concepts (SMC): Focuses on institutional trading patterns like liquidity sweeps, supply/demand zones, and fair value gaps (FVGs).
2. Key Features
Liquidity Sweep Detection:
Identifies false breakouts where price briefly exceeds recent highs/lows before reversing.
Confirms institutional "stop hunts" to trap retail traders.
Supply/Demand Zones:
Marks areas of concentrated buying/selling pressure.
Zones persist on the chart (up to max_zones_displayed) and are triggered by liquidity sweeps.
Fair Value Gaps (FVG):
Detects price voids between candles, indicating potential reversal zones.
Bullish FVG (gap below) and Bearish FVG (gap above) highlighted.
Market Structure Lines:
Horizontal lines showing recent swing highs/lows (10-period extremes).
3. Indicators & Filters
RSI & CMO: Momentum filters (RSI >50/<50, CMO positive/negative).
Volume Confirmation: Optional filter requiring volume spikes (1.5x 20-period average).
ATR-Based Risk Management: Dynamic stop-loss and take-profit levels based on volatility.
4. Entry Conditions
Long Entry:
Price crosses above demand zone.
Bullish momentum (RSI >50, CMO >0).
Confirmed bullish liquidity sweep.
Volume spike (if enabled).
Short Entry:
Price crosses below supply zone.
Bearish momentum (RSI <50, CMO <0).
Confirmed bearish liquidity sweep.
Volume spike (if enabled).
5. Risk Management
Stop-Loss: Fixed percentage (2%) of price or ATR-based.
Risk/Reward Ratio: 3:1 profit targets derived from stop-loss distance.
6. Visualization
Colored lines/zones for Elliott Wave projections, FVGs, supply/demand areas, and market structure.
Labels and alerts for key events (liquidity sweeps, zone entries).
7. Strategy Logic
Bullish Scenario:
After a bearish liquidity sweep (trap shorts), enter long when price reclaims demand zone with momentum.
Target Fibonacci extension levels or supply zones.
Stop below recent swing low/ATR level.
Bearish Scenario:
After a bullish liquidity sweep (trap longs), enter short when price breaks below supply zone.
Target demand zones or Fibonacci projections.
Stop above recent swing high/ATR level.
8. Use Case
This strategy aims to:
Identify institutional order blocks (liquidity sweeps).
Catch reversals at key supply/demand zones.
Use Elliott Wave principles for profit targets.
Filter false signals with volume/momentum confirmation.
It's designed for swing trading and requires combining price action confirmation with the automated signals. The visual elements help traders quickly assess market structure and key levels.
Scalping 15min: EMA + MACD + RSI + ATR-based SL/TP📈 Strategy: 15-Minute Scalping — EMA + MACD + RSI + ATR-based SL/TP
This scalping strategy is designed for 15-minute charts and combines trend-following and momentum confirmation with dynamic stop loss and take profit levels based on volatility.
🔧 Indicators Used:
EMA 50 — identifies the main trend
MACD Histogram — confirms momentum direction
RSI (14) — filters overbought/oversold conditions
ATR (14) — dynamically sets SL and TP based on market volatility
📊 Entry Conditions:
Long Entry:
Price is above EMA 50
MACD histogram is positive
RSI is above 50 but below 70
Short Entry:
Price is below EMA 50
MACD histogram is negative
RSI is below 50 but above 30
🛑 Risk Management:
Stop Loss: 1×ATR (user-configurable)
Take Profit: 2×ATR (user-configurable)
These values can be adjusted in the script inputs depending on your risk/reward preference or market conditions.
⚠️ Notes:
Strategy is optimized for scalping fast-moving pairs (e.g. crypto, forex).
Works best in trending markets.
Use backtesting and forward testing before live trading.
50 EMA Crossover With Monthly DCARecommended Chart Interval = 1W
Overview:
This strategy combines trend-following principles with dollar-cost averaging (DCA), aiming to efficiently deploy capital while minimizing market timing risk.
How It Works:
When the Long Condition is Not Met (i.e., Price < 50 EMA):
- If the price is below the 50 EMA, a fixed DCA amount is added to a cash reserve every month.
- This ensures that capital is consistently accumulated, even when the strategy isn't in a long position.
When the Long Condition is Met (i.e., Price > 50 EMA):
- A long position is opened when the price is above the 50 EMA.
- At this point, the entire capital, including the accumulated cash reserve, is deployed into the market.
- While the strategy is long, a DCA buy order is placed every month using the set DCA amount, continuously investing as the market conditions allow.
Exit Strategy:
If the price falls below the 50 EMA, the strategy closes all positions, and the cash reserve accumulation process begins again.
Key Benefits:
✔ Systematic Investing: Ensures consistent capital deployment while following trend signals.
✔ Cash Efficiency: Accumulates uninvested funds when conditions aren’t met and deploys them at optimal moments.
✔ Risk Management: Exits when the price trend weakens, protecting capital.
Conclusion:
This method allows for efficient capital growth by combining a trend-following approach with disciplined DCA, ensuring risk is managed while capital is deployed systematically at optimal points in the market. 🚀
Trailing Monster StrategyTrailing Monster Strategy
This is an experimental trend-following strategy that incorporates a custom adaptive moving average (PKAMA), RSI-based momentum filtering, and dynamic trailing stop-loss logic. It is designed for educational and research purposes only, and may require further optimization or risk management considerations prior to live deployment.
Strategy Logic
The strategy attempts to participate in sustained price trends by combining:
- A Power Kaufman Adaptive Moving Average (PKAMA) for dynamic trend detection,
- RSI and Simple Moving Average (SMA) filters for market condition confirmation,
- A delayed trailing stop-loss to manage exits once a trade is in profit.
Entry Conditions
Long Entry:
- RSI exceeds the overbought threshold (default: 70),
- Price is trading above the 200-period SMA,
- PKAMA slope is positive (indicating upward momentum),
- A minimum number of bars have passed since the last entry.
Short Entry:
- RSI falls below the oversold threshold (default: 30),
- Price is trading below the 200-period SMA,
- PKAMA slope is negative (indicating downward momentum),
-A minimum number of bars have passed since the last entry.
Exit Conditions
- A trailing stop-loss is applied once the position has been open for a user-defined number of bars.
- The trailing distance is calculated as a fixed percentage of the average entry price.
Technical Notes
This script implements a custom version of the Power Kaufman Adaptive Moving Average (PKAMA), conceptually inspired by alexgrover’s public implementation on TradingView .
Unlike traditional moving averages, PKAMA dynamically adjusts its responsiveness based on recent market volatility, allowing it to better capture trend changes in fast-moving assets like altcoins.
Disclaimer
This strategy is provided for educational purposes only.
It is not financial advice, and no guarantee of profitability is implied.
Always conduct thorough backtesting and forward testing before using any strategy in a live environment.
Adjust inputs based on your individual risk tolerance, asset class, and trading style.
Feedback is encouraged. You are welcome to fork and modify this script to suit your own preferences and market approach.
RSI Reversal with EMA Filter Strategy## 3. RSI Reversal with EMA Filter Strategy
This strategy combines the power of RSI for identifying oversold/overbought conditions with EMA crossovers for trend confirmation.
### Strategy Overview:
The RSI (Relative Strength Index) with a short lookback period quickly identifies potential reversal points, while EMAs confirm the trend direction.
### Rules:
1. **Indicator Settings:**
- RSI Period: 2-6 (shorter period works best for intraday)
- EMA Fast: 9
- EMA Slow: 21
2. **Entry Criteria:**
- Buy when RSI < 15 and EMA 9 crosses above EMA 21
- Sell when RSI > 85 and EMA 9 crosses below EMA 21
3. **Exit Rules:**
- Target: 100 points
- Stop Loss: 20 points
### Performance Metrics:
- **Win Rate:** Up to 70% with proper risk management
- **Reward-to-Risk Ratio:** 5:1
- **Historical Performance:** RSI with shorter periods (2-6) has shown superior results for intraday trading
According to backtesting, RSI with shorter lookback periods (2-6 days) has consistently outperformed strategies using the traditional 14-period RSI setting.
SHORT_TRADING📈 EMA34 (Exponential Moving Average - 34 Period)
EMA34 is a technical analysis indicator that calculates the average price of an asset over the past 34 periods, giving more weight to recent prices. This makes it more responsive to recent price changes compared to a simple moving average.
🔍 Key Features:
Period: 34 candles (can be minutes, hours, days, depending on the chart timeframe)
Type: Exponential (faster reaction to price movements)
Purpose: Helps identify the current trend direction and potential support/resistance levels
📊 How Traders Use EMA34:
Trend Identification:
Price above EMA34 → uptrend
Price below EMA34 → downtrend
Dynamic Support/Resistance:
During uptrends, EMA34 often acts as a support
During downtrends, it acts as resistance
Entry/Exit Signals:
Crossovers with other EMAs (like EMA13 or EMA200) can signal potential trade setups
🧠 Common Pairing:
EMA34 is often used with shorter EMAs like EMA13 or longer ones like EMA55/EMA200 to create a moving average ribbon or crossover strategy.
Multi-Timeframe Reversal StrategyThis is my first published indicator. In spirit of this community it is free and I welcome any input to make it better. working on future projects on volume and taking tips from more experienced developers.
TRIX Strategy)trix strategy with rsi
this is a winning strategy if used with good setting can get 140 pesent roi per year
this is true i have done that with this strategy jast play with the setting to get the best result
XRP/USD Advanced Trading StrategyKey Features:
Triple Confirmation System combines:
Moving Average crossover (9-period vs 21-period)
RSI oversold/overbought conditions (14-period)
MACD histogram crossover
Risk Management:
Built-in stop loss/profit taking (modify via strategy settings)
Margin requirements specified (100:1 leverage)
Visual Elements:
Clean price chart overlay
Clear buy/sell arrows with labels
Moving average plots for trend identification
Optimization Tips:
Adjust MA lengths for different timeframes (shorter for day trading)
Modify RSI levels based on market volatility
Combine with Ichimoku Cloud for additional confirmation
Use Bollinger Bands® to filter false breakouts
Backtesting:
Test on multiple timeframes (4h/daily weekly)
Check performance during different market conditions
Optimize parameters using Strategy Tester
This strategy reduces false signals by requiring confirmation from three different technical indicators while maintaining clarity in signal generation. Always validate with fundamental analysis and market news before executing trade
Z-Score Normalized VIX StrategyThis strategy leverages the concept of the Z-score applied to multiple VIX-based volatility indices, specifically designed to capture market reversals based on the normalization of volatility. The strategy takes advantage of VIX-related indicators to measure extreme levels of market fear or greed and adjusts its position accordingly.
1. Overview of the Z-Score Methodology
The Z-score is a statistical measure that describes the position of a value relative to the mean of a distribution in terms of standard deviations. In this strategy, the Z-score is calculated for various volatility indices to assess how far their values are from their historical averages, thus normalizing volatility levels. The Z-score is calculated as follows:
Z = \frac{X - \mu}{\sigma}
Where:
• X is the current value of the volatility index.
• \mu is the mean of the index over a specified period.
• \sigma is the standard deviation of the index over the same period.
This measure tells us how many standard deviations the current value of the index is away from its average, indicating whether the market is experiencing unusually high or low volatility (fear or calm).
2. VIX Indices Used in the Strategy
The strategy utilizes four commonly referenced volatility indices:
• VIX (CBOE Volatility Index): Measures the market’s expectations of 30-day volatility based on S&P 500 options.
• VIX3M (3-Month VIX): Reflects expectations of volatility over the next three months.
• VIX9D (9-Day VIX): Reflects shorter-term volatility expectations.
• VVIX (VIX of VIX): Measures the volatility of the VIX itself, indicating the level of uncertainty in the volatility index.
These indices provide a comprehensive view of the current volatility landscape across different time horizons.
3. Strategy Logic
The strategy follows a long entry condition and an exit condition based on the combined Z-score of the selected volatility indices:
• Long Entry Condition: The strategy enters a long position when the combined Z-score of the selected VIX indices falls below a user-defined threshold, indicating an abnormally low level of volatility (suggesting a potential market bottom and a bullish reversal). The threshold is set as a negative value (e.g., -1), where a more negative Z-score implies greater deviation below the mean.
• Exit Condition: The strategy exits the long position when the combined Z-score exceeds the threshold (i.e., when the market volatility increases above the threshold, indicating a shift in market sentiment and reduced likelihood of continued upward momentum).
4. User Inputs
• Z-Score Lookback Period: The user can adjust the lookback period for calculating the Z-score (e.g., 6 periods).
• Z-Score Threshold: A customizable threshold value to define when the market has reached an extreme volatility level, triggering entries and exits.
The strategy also allows users to select which VIX indices to use, with checkboxes to enable or disable each index in the calculation of the combined Z-score.
5. Trade Execution Parameters
• Initial Capital: The strategy assumes an initial capital of $20,000.
• Pyramiding: The strategy does not allow pyramiding (multiple positions in the same direction).
• Commission and Slippage: The commission is set at $0.05 per contract, and slippage is set at 1 tick.
6. Statistical Basis of the Z-Score Approach
The Z-score methodology is a standard technique in statistics and finance, commonly used in risk management and for identifying outliers or unusual events. According to Dumas, Fleming, and Whaley (1998), volatility indices like the VIX serve as a useful proxy for market sentiment, particularly during periods of high uncertainty. By calculating the Z-score, we normalize volatility and quantify the degree to which the current volatility deviates from historical norms, allowing for systematic entry and exit based on these deviations.
7. Implications of the Strategy
This strategy aims to exploit market conditions where volatility has deviated significantly from its historical mean. When the Z-score falls below the threshold, it suggests that the market has become excessively calm, potentially indicating an overreaction to past market events. Entering long positions under such conditions could capture market reversals as fear subsides and volatility normalizes. Conversely, when the Z-score rises above the threshold, it signals increased volatility, which could be indicative of a bearish shift in the market, prompting an exit from the position.
By applying this Z-score normalized approach, the strategy seeks to achieve more consistent entry and exit points by reducing reliance on subjective interpretation of market conditions.
8. Scientific Sources
• Dumas, B., Fleming, J., & Whaley, R. (1998). “Implied Volatility Functions: Empirical Tests”. The Journal of Finance, 53(6), 2059-2106. This paper discusses the use of volatility indices and their empirical behavior, providing context for volatility-based strategies.
• Black, F., & Scholes, M. (1973). “The Pricing of Options and Corporate Liabilities”. Journal of Political Economy, 81(3), 637-654. The original Black-Scholes model, which forms the basis for many volatility-related strategies.
NEW Non-Directional Market StrategyFinal New Non Directional Trading Strategy! which can be used for all markets , the candles will turn grey during the choppy conditions.
Reversal Trading Bot Strategy[BullByte]Overview :
The indicator Reversal Trading Bot Strategy is crafted to capture potential market reversal points by combining momentum, volatility, and trend alignment filters. It uses a blend of technical indicators to identify both bullish and bearish reversal setups, ensuring that multiple market conditions are met before entering a trade.
Core Components :
Technical Indicators Used :
RSI (Relative Strength Index) :
Purpose : Detects divergence conditions by comparing recent lows/highs in price with the RSI.
Parameter : Length of 8.
Bollinger Bands (BB) :
Purpose : Measures volatility and identifies price levels that are statistically extreme.
Parameter : Length of 20 and a 2-standard deviation multiplier.
ADX (Average Directional Index) & DMI (Directional Movement Index) :
Purpose : Quantifies the strength of the trend. The ADX threshold is set at 20, and additional filters check for the alignment of the directional indicators (DI+ and DI–).
ATR (Average True Range) :
Purpose : Provides a volatility measure used to set stop levels and determine risk through trailing stops.
Volume SMA (Simple Moving Average of Volume ):
Purpose : Helps confirm strength by comparing the current volume against a 20-period average, with an optional filter to ensure volume is at least twice the SMA.
User-Defined Toggle Filters :
Volume Filter : Confirms that the volume is above average (or twice the SMA) before taking trades.
ADX Trend Alignment Filter : Checks that the ADX’s directional indicators support the trade direction.
BB Close Confirmation : Optionally refines the entry by requiring price to be beyond the upper or lower Bollinger Band rather than just above or below.
RSI Divergence Exit : Allows the script to close positions if RSI divergence is detected.
BB Mean Reversion Exit : Closes positions if the price reverts to the Bollinger Bands’ middle line.
Risk/Reward Filter : Ensures that the potential reward is at least twice the risk by comparing the distance to the Bollinger Band with the ATR.
Candle Movement Filter : Optional filter to require a minimum percentage move in the candle to confirm momentum.
ADX Trend Exit : Closes positions if the ADX falls below the threshold and the directional indicators reverse.
Entry Conditions :
Bullish Entry :
RSI Divergence : Checks if the current close is lower than a previous low while the RSI is above the previous low, suggesting bullish divergence.
Bollinger Confirmation : Requires that the price is above the lower (or upper if confirmation is toggled) Bollinger Band.
Volume & Trend Filters : Combines volume condition, ADX strength, and an optional candle momentum condition.
Risk/Reward Check : Validates that the trade meets a favorable risk-to-reward ratio.
Bearish Entry :
Uses a mirror logic of the bullish entry by checking for bearish divergence, ensuring the price is below the appropriate Bollinger level, and confirming volume, trend strength, candle pattern, and risk/reward criteria.
Trade Execution and Exit Strateg y:
Trade Execution :
Upon meeting the entry conditions, the strategy initiates a long or short position.
Stop Loss & Trailing Stops :
A stop-loss is dynamically set using the ATR value, and trailing stops are implemented as a percentage of the close price.
Exit Conditions :
Additional exit filters can trigger early closures based on RSI divergence, mean reversion (via the middle Bollinger Band), or a weakening trend as signaled by ADX falling below its threshold.
This multi-layered exit strategy is designed to lock in gains or minimize losses if the market begins to reverse unexpectedly.
How the Strategy Works in Different Market Conditions :
Trending Markets :
The ADX filter ensures that trades are only taken when the trend is strong. When the market is trending, the directional movement indicators help confirm the momentum, making the reversal signal more reliable.
Ranging Markets :
In choppy markets, the Bollinger Bands expand and contract, while the RSI divergence can highlight potential turning points. The optional filters can be adjusted to avoid false signals in low-volume or low-volatility conditions.
Volatility Management :
With ATR-based stop-losses and a risk/reward filter, the strategy adapts to current market volatility, ensuring that risk is managed consistently.
Recommendation on using this Strategy with a Trading Bot :
This strategy is well-suited for high-frequency trading (HFT) due to its ability to quickly identify reversal setups and execute trades dynamically with automated stop-loss and trailing exits. By integrating this script with a TradingView webhook-based bot or an API-driven execution system, traders can automate trade entries and exits in real-time, reducing manual execution delays and capitalizing on fast market movements.
Disclaimer :
This script is provided for educational and informational purposes only. It is not intended as investment advice. Trading involves significant risk, and you should always conduct your own research and analysis before making any trading decisions. The author is not responsible for any losses incurred while using this script.
EMA 34 Crossover with Break Even Stop LossEMA 34 Crossover with Break Even Stop Loss Strategy
This trading strategy is based on the 34-period Exponential Moving Average (EMA) and aims to enter long positions when the price crosses above the EMA 34. The strategy is designed to manage risk effectively with a dynamic stop loss and take-profit mechanism.
Key Features:
EMA 34 Crossover:
The strategy generates a long entry signal when the closing price of the current bar crosses above the 34-period EMA, with the condition that the previous closing price was below the EMA. This crossover indicates a potential upward trend.
Risk Management:
Upon entering a trade, the strategy sets a stop loss at the low of the previous bar. This helps in controlling the downside risk.
A take profit level is set at a 10:1 risk-to-reward ratio, meaning the potential profit is ten times the amount risked on the trade.
Break-even Stop Loss:
As the price moves in favor of the trade and reaches a 3:1 risk-to-reward ratio, the strategy moves the stop loss to the entry price (break-even). This ensures that no loss will be incurred if the market reverses, effectively protecting profits.
Exit Conditions:
The strategy exits the trade when either the stop loss is hit (if the price drops below the stop loss level) or the take profit target is reached (if the price rises to the take profit level).
If the price reaches the break-even level (entry price), the stop loss is adjusted to lock in profits and prevent any loss.
Visualization:
The stop loss and take profit levels are plotted on the chart for easy visualization, helping traders track the status of their trade.
Trade Management Summary:
Long Entry: When price crosses above the 34-period EMA.
Stop Loss: Set to the low of the previous candle.
Take Profit: Set to a 10:1 risk-to-reward ratio.
Break-even: Stop loss is moved to entry price when a 3:1 risk-to-reward ratio is reached.
Exit: The trade is closed either when the stop loss or take profit levels are hit.
This strategy is designed to minimize losses by employing a dynamic stop loss and to maximize gains by setting a favorable risk-to-reward ratio, making it suitable for traders who prefer a structured, automated approach to risk management and trend-following.
BTC/USDC 50x Futures Strategy with Multi-TPScript in the workings for btc/usdt 50x leverage trading at 1% portfolio margin. Please do not use to save your money
BTC Trading RobotOverview
This Pine Script strategy is designed for trading Bitcoin (BTC) by placing pending orders (BuyStop and SellStop) based on local price extremes. The script also implements a trailing stop mechanism to protect profits once a position becomes sufficiently profitable.
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Inputs and Parameter Setup
1. Trading Profile:
o The strategy is set up specifically for BTC trading.
o The systemType input is set to 1, which means the strategy will calculate trade parameters using the BTC-specific inputs.
2. Common Trading Inputs:
o Risk Parameters: Although RiskPercent is defined, its actual use (e.g., for position sizing) isn’t implemented in this version.
o Trading Hours Filter:
SHInput and EHInput let you restrict trading to a specific hour range. If these are set (non-zero), orders will only be placed during the allowed hours.
3. BTC-Specific Inputs:
o Take Profit (TP) and Stop Loss (SL) Percentages:
TPasPctBTC and SLasPctBTC are used to determine the TP and SL levels as a percentage of the current price.
o Trailing Stop Parameters:
TSLasPctofTPBTC and TSLTgrasPctofTPBTC determine when and by how much a trailing stop is applied, again as percentages of the TP.
4. Other Parameters:
o BarsN is used to define the window (number of bars) over which the local high and low are calculated.
o OrderDistPoints acts as a buffer to prevent the entry orders from being triggered too early.
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Trade Parameter Calculation
• Price Reference:
o The strategy uses the current closing price as the reference for calculations.
• Calculation of TP and SL Levels:
o If the systemType is set to BTC (value 1), then:
Take Profit Points (Tppoints) are calculated by multiplying the current price by TPasPctBTC.
Stop Loss Points (Slpoints) are calculated similarly using SLasPctBTC.
A buffer (OrderDistPoints) is set to half of the take profit points.
Trailing Stop Levels:
TslPoints is calculated as a fraction of the TP (using TSLTgrasPctofTPBTC).
TslTriggerPoints is similarly determined, which sets the profit level at which the trailing stop will start to activate.
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Time Filtering
• Session Control:
o The current hour is compared against SHInput (start hour) and EHInput (end hour).
o If the current time falls outside the allowed window, the script will not place any new orders.
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Entry Orders
• Local Price Extremes:
o The strategy calculates a local high and local low using a window of BarsN * 2 + 1 bars.
• Placing Stop Orders:
o BuyStop Order:
A long entry is triggered if the current price is less than the local high minus the order distance buffer.
The BuyStop order is set to trigger at the level of the local high.
o SellStop Order:
A short entry is triggered if the current price is greater than the local low plus the order distance buffer.
The SellStop order is set to trigger at the level of the local low.
Note: Orders are only placed if there is no current open position and if the session conditions are met.
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Trailing Stop Logic
Once a position is open, the strategy monitors profit levels to protect gains:
• For Long Positions:
o The script calculates the profit as the difference between the current price and the average entry price.
o If this profit exceeds the TslTriggerPoints threshold, a trailing stop is applied by placing an exit order.
o The stop price is set at a distance below the current price, while a limit (profit target) is also defined.
• For Short Positions:
o The profit is calculated as the difference between the average entry price and the current price.
o A similar trailing stop exit is applied if the profit exceeds the trigger threshold.
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Summary
In essence, this strategy works by:
• Defining entry levels based on recent local highs and lows.
• Placing pending stop orders to enter the market when those levels are breached.
• Filtering orders by time, ensuring trades are only taken during specified hours.
• Implementing a trailing stop mechanism to secure profits once the trade moves favorably.
This approach is designed to automate BTC trading based on price action and dynamic risk management, although further enhancements (like dynamic position sizing based on RiskPercent) could be added for a more complete risk management system.
