Combo 2/20 EMA & Bandpass Filter by TamarokDescription:
This strategy combines a 2/20 exponential moving average (EMA) crossover with a custom bandpass filter to generate buy and sell signals.
Use the Fast EMA and Slow EMA inputs to adjust trend sensitivity, and the Bandpass Filter Length, Delta, and Zones to fine-tune momentum turns.
Signals occur when both EMA and BPF agree in direction, with optional reversal and time filters.
How to use:
1. Add the script to your chart in TradingView.
2. Adjust the EMA and BP Filter parameters to match your asset’s volatility.
3. Enable ‘Reverse Signals’ to trade counter-trend, or use the time filter to limit sessions.
4. Set alerts on Long Alert and Short Alert for automated notifications.
Inspiration:
Based on HPotter’s original combo strategy (Stocks & Commodities Mar 2010).
Updated to Pine Script v6 with streamlined code and alerts.
WARNING:
For purpose educate only
ابحث في النصوص البرمجية عن "bands"
EMA 20 and Anchored VWAP with Typical PriceIntraday scalping using EMA 20 and VWAP along with targets and Stoploss
SOXL Trend Surge v3.0.2 – Profit-Only RunnerSOXL Trend Surge v3.0.2 – Profit-Only Runner
This is a trend-following strategy built for leveraged ETFs like SOXL, designed to ride high-momentum waves with minimal interference. Unlike most short-term scalping scripts, this model allows trades to develop over multiple days to even several months, capitalizing on the full power of extended directional moves — all without using a stop-loss.
🔍 How It Works
Entry Logic:
Price is above the 200 EMA (long-term trend confirmation)
Supertrend is bullish (momentum confirmation)
ATR is rising (volatility expansion)
Volume is above its 20-bar average (liquidity filter)
Price is outside a small buffer zone from the 200 EMA (to avoid whipsaws)
Trades are restricted to market hours only (9 AM to 2 PM EST)
Cooldown of 15 bars after each exit to prevent overtrading
Exit Strategy:
Takes partial profit at +2× ATR if held for at least 2 bars
Rides the remaining position with a trailing stop at 1.5× ATR
No hard stop-loss — giving space for volatile pullbacks
⚙️ Strategy Settings
Initial Capital: $500
Risk per Trade: 100% of equity (fully allocated per entry)
Commission: 0.1%
Slippage: 1 tick
Recalculate after order is filled
Fill orders on bar close
Timeframe Optimized For: 45-minute chart
These parameters simulate an aggressive, high-volatility trading model meant for forward-testing compounding potential under realistic trading costs.
✅ What Makes This Unique
No stop-loss = fewer premature exits
Partial profit-taking helps lock in early wins
Trailing logic gives room to ride large multi-week moves
Uses strict filters (volume, ATR, EMA bias) to enter only during high-probability windows
Ideal for leveraged ETF swing or position traders looking to hold longer than the typical intraday or 2–3 day strategies
⚠️ Important Note
This is a high-risk, high-reward strategy meant for educational and testing purposes. Without a stop-loss, trades can experience deep drawdowns that may take weeks or even months to recover. Always test thoroughly and adjust position sizing to suit your risk tolerance. Past results do not guarantee future returns. Backtest range: May 8, 2020 – May 23, 2025
SmartScale Envelope DCA This is a Dollar-Cost Averaging (DCA) long strategy that buys when price dips below a moving average envelope and adds to the position in a stepwise, risk-controlled way. It uses up to 8 buy-ins, applies a cooldown between entries, and exits based on either a take profit from average entry price or a stop loss. Backtest range limits trades to the last 365 days for backtest control.
All input settings can and should be adjusted to the chart, as volatility in price action varies. Simply go into the inputs settings, and start from the top and move down to get better backtest results. Moving from the top down has been proven to give the best results. Then, move to properties and set your order size, pyramiding, and so on. It may be necessary to then fine tune your adjustments a second time to dial it in.
Works well on 1 hour time frames and in volatility.
Happy Trading!
PowerZone Trading StrategyExplanation of the PowerZone Trading Strategy for Your Users
The PowerZone Trading Strategy is an automated trading strategy that detects strong price movements (called "PowerZones") and generates signals to enter a long (buy) or short (sell) position, complete with predefined take profit and stop loss levels. Here’s how it works, step by step:
1. What is a PowerZone?
A "PowerZone" (PZ) is a zone on the chart where the price has shown a significant and consistent movement over a specific number of candles (bars). There are two types:
Bullish PowerZone (Bullish PZ): Occurs when the price rises consistently over several candles after an initial bearish candle.
Bearish PowerZone (Bearish PZ): Occurs when the price falls consistently over several candles after an initial bullish candle.
The code analyzes:
A set number of candles (e.g., 5, adjustable via "Periods").
A minimum percentage move (adjustable via "Min % Move for PowerZone") to qualify as a strong zone.
Whether to use the full candle range (highs and lows) or just open/close prices (toggle with "Use Full Range ").
2. How Does It Detect PowerZones?
Bullish PowerZone:
Looks for an initial bearish candle (close below open).
Checks that the next candles (e.g., 5) are all bullish (close above open).
Ensures the total price movement exceeds the minimum percentage set.
Defines a range: from the high (or open) to the low of the initial candle.
Bearish PowerZone:
Looks for an initial bullish candle (close above open).
Checks that the next candles are all bearish (close below open).
Ensures the total price movement exceeds the minimum percentage.
Defines a range: from the high to the low (or close) of the initial candle.
These zones are drawn on the chart with lines: green or white for bullish, red or blue for bearish, depending on the color scheme ("DARK" or "BRIGHT").
3. When Does It Enter a Trade?
The strategy waits for a breakout from the PowerZone range to enter a trade:
Buy (Long): When the price breaks above the high of a Bullish PowerZone.
Sell (Short): When the price breaks below the low of a Bearish PowerZone.
The position size is set to 100% of available equity (adjustable in the code).
4. Take Profit and Stop Loss
Take Profit (TP): Calculated as a multiple (adjustable via "Take Profit Factor," default 1.5) of the PowerZone height. For example:
For a buy, TP = Entry price + (PZ height × 1.5).
For a sell, TP = Entry price - (PZ height × 1.5).
Stop Loss (SL): Calculated as a multiple (adjustable via "Stop Loss Factor," default 1.0) of the PZ height, placed below the range for buys or above for sells.
5. Visualization on the Chart
PowerZones are displayed with lines on the chart (you can hide them with "Show Bullish Channel" or "Show Bearish Channel").
An optional info panel ("Show Info Panel") displays key levels: PZ high and low, TP, and SL.
You can also enable brief documentation on the chart ("Show Documentation") explaining the basic rules.
6. Alerts
The code generates automatic alerts in TradingView:
For a bullish breakout: "Bullish PowerZone Breakout - LONG!"
For a bearish breakdown: "Bearish PowerZone Breakdown - SHORT!"
7. Customization
You can tweak:
The number of candles to detect a PZ ("Periods").
The minimum percentage move ("Min % Move").
Whether to use highs/lows or just open/close ("Use Full Range").
The TP and SL factors.
The color scheme and what elements to display on the chart.
Practical Example
Imagine you set "Periods = 5" and "Min % Move = 2%":
An initial bearish candle appears, followed by 5 consecutive bullish candles.
The total move exceeds 2%.
A Bullish PowerZone is drawn with a high and low.
If the price breaks above the high, you enter a long position with a TP 1.5 times the PZ height and an SL equal to the height below.
The system executes the trade and exits automatically at TP or SL.
Conclusion
This strategy is great for capturing strong price movements after consolidation or momentum zones. It’s automated, visual, and customizable, making it useful for both beginner and advanced traders. Try it out and adjust it to fit your trading style!
Dual Keltner Channels Strategy [Eastgate3194]This strategy utilised 2 Keltner Channels to perform counter trade.
The strategy have 2 steps:
Long Position:
Step 1. Close price must cross under Outer Lower band of Keltner Channel.
Step 2. Close price cross over Inner Lower band of Keltner Channel.
Short Position:
Step 1. Close price must cross over Outer Upper band of Keltner Channel.
Step 2. Close price cross under Inner Upper band of Keltner Channel.
NSE Index Strategy with Entry/Exit MarkersExplanation of the Code
Trend Filter (200 SMA):
The line trendSMA = ta.sma(close, smaPeriod) calculates the 200‑period simple moving average. By trading only when the current price is above this SMA (inUptrend = close > trendSMA), we aim to trade in the direction of the dominant trend.
RSI Entry Signal:
The RSI is calculated with rsiValue = ta.rsi(close, rsiPeriod). The script checks for an RSI crossover above the oversold threshold using ta.crossover(rsiValue, rsiOversold). This helps capture a potential reversal from a minor pullback in an uptrend.
ATR-Based Exits:
ATR is computed by atrValue = ta.atr(atrPeriod) and is used to set the stop loss and take profit levels:
Stop Loss: stopLossPrice = close - atrMultiplier * atrValue
Take Profit: takeProfitPrice = close + atrMultiplier * atrValue
This dynamic approach allows the exit levels to adjust according to the current market volatility.
Risk and Money Management:
The strategy uses a fixed percentage of equity (10% by default) for each trade. The built‑in commission parameter helps simulate real-world trading costs.
GM+For a Short Trade:
When a bullish candle (close > open) is larger than the previous candle and the MACD histogram for the past three bars is consecutively lower (suggesting weakening upward momentum), the script enters a short position.
For a Long Trade:
When a bearish candle (close < open) is larger (in body size) than the previous candle and the MACD histogram for the past three bars is consecutively higher (suggesting the downward move is losing strength), the script enters a long position.
Position Management:
There are no stop loss or take profit levels. The position is closed only when an opposite signal appears.
Moving Average Crossover StrategyCertainly! Below is an example of a professional trading strategy implemented in Pine Script for TradingView. This strategy is a simple moving average crossover strategy, which is a common approach used by many traders. It uses two moving averages (a short-term and a long-term) to generate buy and sell signals.
Input Parameters:
shortLength: The length of the short-term moving average.
longLength: The length of the long-term moving average.
Moving Averages:
shortMA: The short-term simple moving average (SMA).
longMA: The long-term simple moving average (SMA).
Conditions:
longCondition: A buy signal is generated when the short-term MA crosses above the long-term MA.
shortCondition: A sell signal is generated when the short-term MA crosses below the long-term MA.
Trade Execution:
The strategy enters a long position when the longCondition is met.
The strategy enters a short position when the shortCondition is met.
Plotting:
The moving averages are plotted on the chart.
Buy and sell signals are plotted as labels on the chart.
How to Use:
Copy the script into TradingView's Pine Script editor.
Adjust the shortLength and longLength parameters to fit your trading style.
Add the script to your chart and apply it to your desired timeframe.
Backtest the strategy to see how it performs on historical data.
This is a basic example, and professional traders often enhance such strategies with additional filters, risk management rules, and other indicators to improve performance.
Advanced Multi-Timeframe Trading System (Risk Managed)Description:
This strategy is an original approach that combines two main analytical components to identify potential trade opportunities while simulating realistic trading conditions:
1. Market Trend Analysis via an Approximate Hurst Exponent
• What It Does:
The strategy computes a rough measure of market trending using an approximate Hurst exponent. A value above 0.5 suggests persistent, trending behavior, while a value below 0.5 indicates a tendency toward mean-reversion.
• How It’s Used:
The Hurst exponent is calculated on both the chart’s current timeframe and a higher timeframe (default: Daily) to capture both local and broader market dynamics.
2. Fibonacci Retracement Levels
• What It Does:
Using daily high and low data from a selected timeframe (default: Daily), the script computes key Fibonacci retracement levels.
• How It’s Used:
• The 61.8% level (Golden Ratio) serves as a key threshold:
• A long entry is signaled when the price crosses above this level if the daily Hurst exponent confirms a trending market.
• The 38.2% level is used to identify short-entry opportunities when the price crosses below it and the daily Hurst indicates non-trending conditions.
Signal Logic:
• Long Entry:
When the price crosses above the 61.8% Fibonacci level (Golden Ratio) and the daily Hurst exponent is greater than 0.5, suggesting a trending market.
• Short Entry:
When the price crosses below the 38.2% Fibonacci level and the daily Hurst exponent is less than 0.5, indicating a less trending or potentially reversing market.
Risk Management & Trade Execution:
• Stop-Loss:
Each trade is risk-managed with a stop-loss set at 2% below (for longs) or above (for shorts) the entry price. This ensures that no single trade risks more than a small, sustainable portion of the account.
• Take Profit:
A take profit order targets a risk-reward ratio of 1:2 (i.e., the target profit is twice the amount risked).
• Position Sizing:
Trades are executed with a fixed position size equal to 10% of account equity.
• Trade Frequency Limits:
• Daily Limit: A maximum of 5 trades per day
• Overall Limit: No more than 510 trades during the backtesting period (e.g., since 2019)
These limits are imposed to simulate realistic trading frequency and to avoid overtrading in backtest results.
Backtesting Parameters:
• Initial Capital: $10,000
• Commission: 0.1% per trade
• Slippage: 1 tick per bar
These settings aim to reflect the conditions faced by the average trader and help ensure that the backtesting results are realistic and not misleading.
Chart Overlays & Visual Aids:
• Fibonacci Levels:
The key Fibonacci retracement levels are plotted on the chart, and the zone between the 61.8% and 38.2% levels is highlighted to show a key retracement area.
• Market Trend Background:
The chart background is tinted green when the daily Hurst exponent indicates a trending market (value > 0.5) and red otherwise.
• Information Table:
An on-chart table displays key parameters such as the current Hurst exponent, daily Hurst value, the number of trades executed today, and the global trade count.
Disclaimer:
Past performance is not indicative of future results. This strategy is experimental and provided solely for educational purposes. It is essential that you backtest and paper trade using your own settings before considering any live deployment. The Hurst exponent calculation is an approximation and should be interpreted as a rough gauge of market behavior. Adjust the parameters and risk management settings according to your personal risk tolerance and market conditions.
Additional Notes:
• Originality & Usefulness:
This script is an original mashup that combines trend analysis with Fibonacci retracement methods. The description above explains how these components work together to provide trading signals.
• Realistic Results:
The strategy uses realistic account sizes, commission rates, slippage, and risk management rules to generate backtesting results that are representative of real-world trading.
• Educational Purpose:
This script is intended to support the TradingView community by offering insights into combining multiple analysis techniques in one strategy. It is not a “get-rich-quick” system but rather an educational tool to help traders understand risk management and trade signal logic.
By using this script, you acknowledge that trading involves risk and that you are responsible for testing and adjusting the strategy to fit your own trading environment. This publication is fully open source, and any modifications should include proper attribution if significant portions of the code are reused.
HOD/LOD/PMH/PML/PDH/PDL Strategy by @tradingbauhaus This script is a trading strategy @tradingbauhaus designed to trade based on key price levels, such as the High of Day (HOD), Low of Day (LOD), Premarket High (PMH), Premarket Low (PML), Previous Day High (PDH), and Previous Day Low (PDL). Below, I’ll explain in detail what the script does:
Core Functionality of the Script:
Calculates Key Price Levels:
HOD (High of Day): The highest price of the current day.
LOD (Low of Day): The lowest price of the current day.
PMH (Premarket High): The highest price during the premarket session (before the market opens).
PML (Premarket Low): The lowest price during the premarket session.
PDH (Previous Day High): The highest price of the previous day.
PDL (Previous Day Low): The lowest price of the previous day.
Draws Horizontal Lines on the Chart:
Plots horizontal lines on the chart for each key level (HOD, LOD, PMH, PML, PDH, PDL) with specific colors for easy visual identification.
Defines Entry and Exit Rules:
Long Entry (Buy): If the price crosses above the PMH (Premarket High) or the PDH (Previous Day High).
Short Entry (Sell): If the price crosses below the PML (Premarket Low) or the PDL (Previous Day Low).
Long Exit: If the price reaches the HOD (High of Day) during a long position.
Short Exit: If the price reaches the LOD (Low of Day) during a short position.
How the Script Works Step by Step:
Calculates Key Levels:
Uses the request.security function to fetch the HOD and LOD of the current day, as well as the highs and lows of the previous day (PDH and PDL).
Calculates the PMH and PML during the premarket session (before 9:30 AM).
Plots Levels on the Chart:
Uses the plot function to draw horizontal lines on the chart representing the key levels (HOD, LOD, PMH, PML, PDH, PDL).
Each level has a specific color for easy identification:
HOD: White.
LOD: Purple.
PDH: Orange.
PDL: Blue.
PMH: Green.
PML: Red.
Defines Trading Rules:
Uses conditions with ta.crossover and ta.crossunder to detect when the price crosses key levels.
Long Entry: If the price crosses above the PMH or PDH, a long position (buy) is opened.
Short Entry: If the price crosses below the PML or PDL, a short position (sell) is opened.
Long Exit: If the price reaches the HOD during a long position, the position is closed.
Short Exit: If the price reaches the LOD during a short position, the position is closed.
Executes Orders Automatically:
Uses the strategy.entry and strategy.close functions to open and close positions automatically based on the defined rules.
Advantages of This Strategy:
Based on Key Levels: Uses important price levels that often act as support and resistance.
Easy to Visualize: Horizontal lines on the chart make it easy to identify levels.
Automated: Entries and exits are executed automatically based on the defined rules.
Limitations of This Strategy:
Dependent on Volatility: Works best in markets with significant price movements.
False Crosses: There may be false crosses that generate incorrect signals.
No Advanced Risk Management: Does not include dynamic stop-loss or take-profit mechanisms.
How to Improve the Strategy:
Add Stop-Loss and Take-Profit: To limit losses and lock in profits.
Filter Signals with Indicators: Use RSI, MACD, or other indicators to confirm signals.
Optimize Levels: Adjust key levels based on the asset’s behavior.
In summary, this script is a trading strategy that operates based on key price levels, such as HOD, LOD, PMH, PML, PDH, and PDL. It is useful for traders who want to trade based on significant support and resistance levels.
IU EMA Channel StrategyIU EMA Channel Strategy
Overview:
The IU EMA Channel Strategy is a simple yet effective trend-following strategy that uses two Exponential Moving Averages (EMAs) based on the high and low prices. It provides clear entry and exit signals by identifying price crossovers relative to the EMAs while incorporating a built-in Risk-to-Reward Ratio (RTR) for effective risk management.
Inputs ( Settings ):
- RTR (Risk-to-Reward Ratio): Define the ratio for risk-to-reward (default = 2).
- EMA Length: Adjust the length of the EMA channels (default = 100).
How the Strategy Works
1. EMA Channels:
- High-based EMA: EMA calculated on the high price.
- Low-based EMA: EMA calculated on the low price.
The area between these two EMAs creates a "channel" that visually highlights potential support and resistance zones.
2. Entry Rules:
- Long Entry: When the price closes above the high-based EMA (crossover).
- Short Entry: When the price closes below the low-based EMA (crossunder).
These entries ensure trades are taken in the direction of momentum.
3. Stop Loss (SL) and Take Profit (TP):
- Stop Loss:
- For long positions, the SL is set at the previous bar's low.
- For short positions, the SL is set at the previous bar's high.
- Take Profit:
- TP is automatically calculated using the Risk-to-Reward Ratio (RTR) you define.
- Example: If RTR = 2, the TP will be 2x the risk distance.
4. Exit Rules:
- Positions are closed at either the stop loss or the take profit level.
- The strategy manages exits automatically to enforce disciplined risk management.
Visual Features
1. EMA Channels:
- The high and low EMAs are dynamically color-coded:
- Green: Price is above the EMA (bullish condition).
- Red: Price is below the EMA (bearish condition).
- The area between the EMAs is shaded for better visual clarity.
2. Stop Loss and Take Profit Zones:
- SL and TP levels are plotted for both long and short positions.
- Zones are filled with:
- Red: Stop Loss area.
- Green: Take Profit area.
Be sure to manage your risk and position size properly.
Statistical ArbitrageThe Statistical Arbitrage Strategy, also known as pairs trading, is a quantitative trading method that capitalizes on price discrepancies between two correlated assets. The strategy assumes that over time, the prices of these two assets will revert to their historical relationship. The core idea is to take advantage of mean reversion, a principle suggesting that asset prices will revert to their long-term average after deviating significantly.
Strategy Mechanics:
1. Selection of Correlated Assets:
• The strategy focuses on two historically correlated assets (e.g., equity index futures like Dow Jones Mini and S&P 500 Mini). These assets tend to move in the same direction due to similar underlying fundamentals, such as overall market conditions. By tracking their relative prices, the strategy seeks to exploit temporary mispricings.
2. Spread Calculation:
• The spread is the difference between the prices of the two assets. This spread represents the relationship between the assets and serves as the basis for determining when to enter or exit trades.
3. Mean and Standard Deviation:
• The historical average (mean) of the spread is calculated using a Simple Moving Average (SMA) over a chosen period. The strategy also computes the standard deviation (volatility) of the spread, which measures how far the spread has deviated from the mean over time. This allows the strategy to define statistically significant price deviations.
4. Entry Signal (Mean Reversion):
• A buy signal is triggered when the spread falls below the mean by a multiple (e.g., two) of the standard deviation. This indicates that one asset is temporarily undervalued relative to the other, and the strategy expects the spread to revert to its mean, generating profits as the prices converge.
5. Exit Signal:
• The strategy exits the trade when the spread reverts to the mean. At this point, the mispricing has been corrected, and the profit from the mean reversion is realized.
Academic Support:
Statistical arbitrage has been widely studied in finance and economics. Gatev, Goetzmann, and Rouwenhorst’s (2006) landmark study on pairs trading demonstrated that this strategy could generate excess returns in equity markets. Their research found that by focusing on historically correlated stocks, traders could identify pricing anomalies and profit from their eventual correction.
Additionally, Avellaneda and Lee (2010) explored statistical arbitrage in different asset classes and found that exploiting deviations in price relationships can offer a robust, market-neutral trading strategy. In these studies, the strategy’s success hinges on the stability of the relationship between the assets and the timely execution of trades when deviations occur.
Risks of Statistical Arbitrage:
1. Correlation Breakdown:
• One of the primary risks is the breakdown of correlation between the two assets. Statistical arbitrage assumes that the historical relationship between the assets will hold in the future. However, market conditions, company fundamentals, or external shocks (e.g., macroeconomic changes) can cause these assets to deviate permanently, leading to potential losses.
• For instance, if two equity indices historically move together but experience divergent economic conditions or policy changes, their prices may no longer revert to the expected mean.
2. Execution Risk:
• This strategy relies on efficient execution and tight spreads. In volatile or illiquid markets, the actual price at which trades are executed may differ significantly from expected prices, leading to slippage and reduced profits.
3. Market Risk:
• Although statistical arbitrage is designed to be market-neutral (i.e., not dependent on the overall market direction), it is not entirely risk-free. Systematic market shocks, such as financial crises or sudden shifts in market sentiment, can affect both assets simultaneously, causing the spread to widen rather than revert to the mean.
4. Model Risk:
• The assumptions underlying the strategy, particularly regarding mean reversion, may not always hold true. The model assumes that asset prices will return to their historical averages within a certain timeframe, but the timing and magnitude of mean reversion can be uncertain. Misestimating this timeframe can lead to extended drawdowns or unrealized losses.
5. Overfitting:
• Over-reliance on historical data to fine-tune the strategy parameters (e.g., the lookback period or standard deviation thresholds) may result in overfitting. This means that the strategy works well on past data but fails to perform in live markets due to changing conditions.
Conclusion:
The Statistical Arbitrage Strategy offers a systematic and quantitative approach to trading that capitalizes on temporary price inefficiencies between correlated assets. It has been proven to generate returns in academic studies and is widely used by hedge funds and institutional traders for its market-neutral characteristics. However, traders must be aware of the inherent risks, including correlation breakdown, execution risks, and the potential for prolonged deviations from the mean. Effective risk management, diversification, and constant monitoring are essential for successfully implementing this strategy in live markets.
Strategy:Reversal-CatcherWhat
This is a plain and vanilla reversal based strategy for intraday (15m) timeframe on Futures prices of the assets.
Now what all it comprises of?
It finds out the dynamic support & resistance from Bollinger Band (20 period, 1.5 std dev).
It finds out the potential divergence of price deviation from 5 period exponential moving average (EMA).
If the previous candle (N-1) shows a divergence it confirms the reversal by checking the present candle (N) to be closed inside the Bollinger Band.
It confirms the momentum by checking RSI shows a crossover/crossunder to oversold (30) / overbought (70) region.
It also confirms whether the trend is up (then only reversal trade to short) or down (then only reversal trade to long). The trend is checked with EMA-21 and EMA-50.
Re-affirmation Condition : It re-affirms the position of two successive candles called as `hhLLong` and `hhLLShort` in the script.
Why
In Indian context, retail participants are pre-dominantly (yes- 80% of Indian daily volume) Options buyers mainly in weekly indices (Nifty, BankNifty, FinNifty, CNXMidcap, Sensex, Bankx .. well everyday is expiry now in India, except -- Thank God -- Saturday & Sunday).
And in Index Options the momentum plays a big role.
If one can catch a good reversal point the potential of high Risk-to-Reward trade (hence earn handsomely) is very likely (please note: there is no holy grail in trading. Nothing works 100%).
So this is the attempt to catch a reversal.
Re-affirmation of Reversal
hhLLong : It's a reversal point after an uptrend. It checks the relative positioning of current candle compared to that of previous candle. [The details are in the script. Check for variable hhLLong in script.
hhLLShort : It's a reversal point after a downtrend. It checks the relative positioning of current candle compared to that of previous candle. [The details are in the script. Check for variable hhLLShort in script.
Unique-ness
What's unique in it? Why we decided to publicly share this:
Already given the context of The Great Indian Options Buyers community. It should be helpful to them, we believe.
It takes Very Less Number of Trades with High Accuracy . Please check the result in NSE:NIFTY1! in 15m timeframe. 71% accuracy with roughly a trade in a month.
There is no point giving brokers' the brokerages taking 10 trades a day and ending not-so-good EoD. Better lets take less trades with better result possibility. .
Mention
There are many people uses this variation of Bolling Band, 5EMA
Many people use RSI, trends and relative positioning of candles.
--> We are grateful to all of them. It's really difficult to mention everyone's name. But all people somehow influence the thought process. Thanks for all of them.
Statutory Disclaimer
There is no silver bullet / holy grail in trading. Nothing works 100% time. One has to be careful about the loss (s)he can bear in case of the trade goes against.
We, as the author of this script, is not responsible for any trading or position decision one is taken based on the outcome of this.
It is our sole discretion to change, add, delete the portion or withdraw the whole script without any prior notice or intimation.
In Indian Context : We are not SEBI registered, will never be SEBI registered.
Hull Kaufman SuperTrend Cloud (HKST Cloud)TLDR: This is a long only trend following system that uses highest and lowest values of three trend following indicators to form a "cloud". Enter when the candle high crosses above the highest band. Close if the low or close crosses below the lowest band.
3 indicators
1. Kaufman Adaptive moving Average - set at 20
2. Hull Moving Average (of the Kaufman Adaptive moving average) - set at 20
3. SuperTrend - I believe this is set at 5 periods and 3*atr but this can be changed
Cloud
the upper band is the highest of the 3 indicators
the lower band is the lowest of the 3 indicators
Entry and Exit:
Enter when the high crosses above the upper band of the cloud.
(This means you will only get a long signal if the high was previously below the upper band of the cloud and then crosses over.)
Exit when the low crosses below the lower band of the cloud .
(This means that this rule will only close if the low was previously above the upper band and then crosses under)
The "Exit" may not trigger if the low (the wick) never gets above the band. In this case the long order will close if the closing price is below the cloud.
Logic
Kaufamn is the best moving average i have found at responding to changes in volatility. This means it moves up or down quickly during expansive moves but becoming very flat during relative choppiness. However, getting flat causes the the Kaufman AMA to trigger a lot of false signals when volatility is transitioning from high to low. This is why the Hull moving average (with its rounded turns) keeps a lot of the false continuations contained because usually prices need to decisively move higher in order to over come the Hull moving average which continues to increase/decrease during the candles after an expansive move.
The super trend places a stagnant floor and ceiling which acts as a great stoploss or trigger as price action attempts to trend in a certain direction. The super trend allows for the user to adjust the likely hood of this cloud indicator changing from bullish to bearish based on the volatility of the asset that is being analyzed.
individually all of these are great. Together the trader can use this cloud to create a trend following or anlysis system that captures the bulk of moves.
Not my best explanation but this indicator is actually pretty simple.
Hope this helps. Happy Trades
-Snarky Puppy
Strategy Myth-Busting #20 - HalfTrend+HullButterfly - [MYN]#20 on the Myth-Busting bench, we are automating the " I Found Super Easy 1 Minute Scalping System And Backtest It 100 Times " strategy from " Jessy Trading " who claims 30.58% net profit over 100 trades in a couple of weeks with a 51% win rate and profit factor of 1.56 on EURUSD .
This one surprised us quite a bit. Despite the title of this strategy indicating this is on the 1 min timeframe, the author demonstrates the backtesting manually on the 5 minute timeframe. Given the simplicity of this strategy only incorporating a couple of indicators, it's robustness being able to be profitable in both low and high timeframes and on multiple symbols was quite refreshing.
The 3 settings which we need to pay most attention to here is the Hull Butterfly length, HalfTrend amplitude and the Max Number Of Bars Between Hull and HalfTrend Trigger. Depending on the timeframe and symbol, these settings greatly impact the performance outcomes of the strategy. I've listed a couple of these below.
And as always, If you know of or have a strategy you want to see myth-busted or just have an idea for one, please feel free to message me.
This strategy uses a combination of 3 open-source public indicators:
Hull Butterfly Oscillator by LuxAlgo
HalfTrend by Everget
Trading Rules
5 min candles but higher / lower candles work too.
Stop loss at swing high/low
Take Profit 1.5x the risk
Long
Hull Butterfly gives us green column, Wait for HalfTrend to present an up arrow and enter trade.
Short
Hull Butterfly gives us a red column , Wait for HalfTrend to present a down arrow and enter trade.
Alternative Trading Settings for different time frames
1 Minute Timeframe
Move the Hull Butterfly length from the default 11 to 9
Move the HalfTrend Amplitude from the default 2 to 1
Enabling ADX Filter with a 25 threshold
2 Hour Timeframe
Move the HalfTrend Amplitude from the default 2 to 1
Laddered Take Profits from 14.5% to 19% with an 8% SL
Click Draw TrendLine [UhoKang] v2
This is an indicator that directly draws a trend line by clicking on the candle.
Click to Create Trend lines !!
Create a trend line by connecting A, B, and C with three vertices.
1. Draw Bear Trend line
Click pivot high : First pivothigh of the downtrend line
Click pivot low : pivotlow of the downtrend line
Click pivot high : Second pivothigh of the downtrend line
2. Draw Bull Trend line
Click pivot low : First pivotlow of the uptrend line
Click pivot high : pivothigh of the uptrend line
Click pivot low : Second pivotlow of the uptrend line
Modefiy Trendlines
1. Edit Bear Trend line
Drag Red , ,
2. Edit Bull Trend line
Drag Green , ,
Oscillating SSL Channel Strategy - 3m & 5m Time FramesThis script is pretty self-explanatory. I will suggest trying some different exits to get that win rate above 20% (I'd start with Take Profit and Stop Loss percentages).
Enjoy!
Rob Booker - ADX Breakout updated to pinescript V5Rob Booker - ADX Breakout. The strategy remains unchanged but the code has been updated to pinescript V5. This enables compatibility with all new Tradingview features. Additonally, indicators have been made more easily visible, default cash settings as well as input descriptions have been added.
Rob Booker - ADX Breakout: (Directly taken from the official Tradingview V1 version of the script)
Definition
Rob Booker’s Average Directional Index (ADX) Breakout is a trend strength indicator that affirms the belief that trading in the direction of a trend and continuing to follow its pull is more profitable for traders, while simultaneously reducing risk.
History
ADX was traditionally used and developed to determine a price’s trend strength. It is commonly known as a tool from the arsenal of Rob Booker, experienced entrepreneur and currency trader.
Calculations
Calculations for the ADX Breakout indicator are based on a moving average of price range expansion over a specific period of time. By default, the setting rests at 14 bars, this however is not mandatory, as other periods are routinely used for analysis as well.
Takeaways
The ADX line is used to measure and determine the strength of a trend, and so the direction of this line and its interpretation are crucial in a trader’s analysis. As the ADX line rises, a trend increases in strength and price moves in the trend’s direction. Similarly, if the ADX line is falling, a trend decreases in strength and price then enters a period of consolidation, or retracement.
Traditionally, the ADX is plotted on the chart as a single line that consists of values that range from 0-100. The line is non-directional, meaning that it always measures trend strength regardless of the position of a price’s trend (up or down). Essentially, ADX quantifies trend strength by presenting in both uptrends and downtrends of the line.
What to look for
The values associated with the ADX line help traders determine the most profitable trades and where risk lies in the current trend. It is important to know how to quantify trend strength and distinguish between the varying values in order to understand the differences in trending vs. non-trending conditions. Let’s take a look at ADX values and what they mean for trend strength.
ADX Value:
0-25: Signifies an absent of weak trend
25-50: Signifies a strong trend
50-75: Signifies a very strong trend
75-100: Signifies an extremely strong trend
To delve into this a bit further, let’s assess the meaning of ADX if it is valued below 25. If the ADX line remains below 25 for more than 30 or so bars, price then enters range conditions, making price patterns more distinguishable and visible to traders. Price will move up and down between resistance and support in order to determine selling and buying interest and may then eventually break out into a trend or pattern.
The way in which ADX peaks, ebs, and flows is also a signifier of its overall pattern and trend momentum. The line can clearly indicate to the trader when trend strength is strong versus when it is weak. When ADX peaks are pictured as higher, it points towards an increase in trend momentum. If ADX peaks are pictured as lower - you guessed it - it points towards a decrease in trend momentum. A trend of lower ADX peaks could be a warning for traders to watch prices and manage and assess risk before a trade gets out of hand. Similarly, whenever there is a sudden move that seems out of place or a change in trend character that goes against what you’ve seen before, this should be a clear sign to watch prices and assess risk.
Summary
The ADX Breakout indicator is a trend strength indicator that analyzes price movements relative to trend strength to signal a user when is best for a trade and when is best to manage risk and assess patterns. As long as a trader recognizes strong trends and assesses the risk of each trade properly, they should have no problem using this indicator and utilizing it to work in their favor. In addition, the ADX helps identify trending conditions, but while doing so, also aids traders in finding strong trends to trade. The indicator can even alert traders to specific changes in trend momentum, allowing them to be primed for risk management.
[Pt] Premarket Breakout StrategyThis is a 1 trade per day strategy for trading SPY or QQQ index. By default, this is designed for 1 min time frame. This was an experimental script that seems to be profitable at the time of publication.
How it works:
Pre-market high and low is defined per trading day between 9:00 to 9:30 EST.
Then we looking for the first breakout on either PM high or PM low.
- Breakout high = long trade
- Breakout low = short trade
If long trade, we wait until Stochastic RSI D signal line to hit a lower threshold (18 by default). Then we enter long when K crosses above D line.
If short trade, we wait until Stochastic RSI D signal line to hit an upper threshold (82 by default). Then we enter short when K crosses below D line.
Stop loss for long
- set to PM low if entry is above PM high + %ATR buffer
- or set to PM range + %ATR buffer
Stop loss for short
- set to PM high if entry is below PM low + %ATR buffer
- or set to PM range + %ATR buffer
Profit target is set to 2x the risk by default.
*Note: Different Stochastic RSI lengths should be used if trading 5 min time frame. See tooltip.
Happy trading~~!
PB Trend ScalperA moving average strategy using a long period RMA and a short period EMA. It has a trailing stop loss based on the previous higher high or lower low. It also has a no trade band surrounding the RMA whose thickness can be changed.
Check out the settings to see what elements values can be changed.
The strategy is set to use the whole balance on each trade currently.
Leverage can be adjusted as well as take profit target as %.
The default values are set up for the 1 hour on BTCUSD.
These can be tweaked to suit any timeframe or market.
