HMA Crossover 1H with RSI, Stochastic RSI, and Trailing StopThe strategy script provided is a trading algorithm designed to help traders make informed buy and sell decisions based on certain technical indicators. Here’s a breakdown of what each part of the script does and how the strategy works:
Key Components:
Hull Moving Averages (HMA):
HMA 5: This is a Hull Moving Average calculated over 5 periods. HMAs are used to smooth out price data and identify trends more quickly than traditional moving averages.
HMA 20: This is another HMA but calculated over 20 periods, providing a broader view of the trend.
Relative Strength Index (RSI):
RSI 14: This is a momentum oscillator that measures the speed and change of price movements over a 14-period timeframe. It helps identify overbought or oversold conditions in the market.
Stochastic RSI:
%K: This is the main line of the Stochastic RSI, which combines the RSI and the Stochastic Oscillator to provide a more sensitive measure of overbought and oversold conditions. It is smoothed with a 3-period simple moving average.
Trading Signals:
Buy Signal:
Generated when the 5-period HMA crosses above the 20-period HMA, indicating a potential upward trend.
Additionally, the RSI must be below 45, suggesting that the market is not overbought.
The Stochastic RSI %K must also be below 39, confirming the oversold condition.
Sell Signal:
Generated when the 5-period HMA crosses below the 20-period HMA, indicating a potential downward trend.
The RSI must be above 60, suggesting that the market is not oversold.
The Stochastic RSI %K must also be above 63, confirming the overbought condition.
Trailing Stop Loss:
This feature helps protect profits by automatically selling the position if the price moves against the trade by 5%.
For sell positions, an additional trailing stop of 100 points is included.
Search in scripts for "algo"
MA MACD BB BackTesterOverview:
This Pine Script™ code provides a comprehensive backtesting tool that combines Moving Average (MA), Moving Average Convergence Divergence (MACD), and Bollinger Bands (BB). It is designed to help traders analyze market trends and make informed trading decisions by testing various strategies over historical data.
Key Features:
1. Customizable Indicators:
Moving Average (MA): Smooths out price data for clearer trend direction.
MACD: Measures trend momentum through MACD Line, Signal Line, and Histogram.
Bollinger Bands (BB): Identifies overbought or oversold conditions with upper and lower bands.
2. Flexible Trading Direction: Choose between long or short positions to adapt to different market conditions.
3. Risk Management: Efficiently allocate your capital with customizable position sizes.
4. Signal Generation:
Buy Signals: Triggered by crossovers for MACD, MA, and BB.
Sell Signals: Triggered by crossunders for MACD, MA, and BB.
5. Automated Trading: Automatically enter and exit trades based on signal conditions and strategy parameters.
How It Works:
1. Indicator Selection: Select your preferred indicator (MA, MACD, BB) and trading direction (Long/Short).
2. Risk Management Configuration: Set the percentage of capital to allocate per position to manage risk effectively.
3.Signal Detection: The algorithm identifies and plots buy/sell signals directly on the chart based on the chosen indicator.
4. Trade Execution: The strategy automatically enters and exits trades based on signal conditions and configured strategy parameters.
Use Cases:
- Backtesting: Evaluate the effectiveness of trading strategies using historical data to understand potential performance.
- Strategy Development: Customize and expand the strategy to incorporate additional indicators or conditions to fit specific trading styles.
ADDONS That Affect Strategy:
1. Indicator Parameters:
Adjustments to the settings of MACD (e.g., fast length, slow length), MA (e.g., length), and BB (e.g., length, multiplier) will directly impact the detection of signals and the strategy's performance.
2. Trading Direction:
Changing the trading direction (Long/Short) will alter the entry and exit conditions based on the detected signals.
3. Risk Management Settings:
Modifying the position size percentage affects capital allocation and overall risk exposure per trade.
ADDONS That Do Not Affect Strategy:
1. Visual Customizations:
Changes to the color, shape, and style of the plotted lines and signals do not impact the core functionality of the strategy but enhance visual clarity.
2. Text and Labels:
Modifying text labels for the signals (such as renaming "Buy MACD" to "MACD Buy Signal") is purely cosmetic and does not influence the strategy’s logic or outcomes.
Notes:
- Customization: The indicator is highly customizable to fit various trading styles and market conditions.
- Risk Management: Adjust position sizes and risk parameters according to your risk tolerance and account size.
- Optimization: Regularly backtest and optimize parameters to adapt to changing market dynamics for better performance.
Getting Started:
-Add the script to your chart.
-Adjust the input parameters to suit your analysis preferences.
-Observe the marked buy and sell signals on your chart to make informed trading decisions.
Fibonacci Trend Reversal StrategyIntroduction
This publication introduces the " Fibonacci Retracement Trend Reversal Strategy, " tailored for traders aiming to leverage shifts in market momentum through advanced trend analysis and risk management techniques. This strategy is designed to pinpoint potential reversal points, optimizing trading opportunities.
Overview
The strategy leverages Fibonacci retracement levels derived from @IMBA_TRADER's lance Algo to identify potential trend reversals. It's further enhanced by a method called " Trend Strength Over Time " (TSOT) (by @federalTacos5392b), which utilizes percentile rankings of price action to measure trend strength. This also has implemented Dynamic SL finder by utilizing @veryfid's ATR Stoploss Finder which works pretty well
Indicators:
Fibonacci Retracement Levels : Identifies critical reversal zones at 23.6%, 50%, and 78.6% levels.
TSOT (Trend Strength Over Time) : Employs percentile rankings across various timeframes to gauge the strength and direction of trends, aiding in the confirmation of Fibonacci-based signals.
ATR (Average True Range) : Implements dynamic stop-loss settings for both long and short positions, enhancing trade security.
Strategy Settings :
- Sensitivity: Set default at 18, adjustable for more frequent or sparse signals based on market volatility.
- ATR Stop Loss Finder: Multiplier set at 3.5, applying the ATR value to determine stop losses dynamically.
- ATR Length: Default set to 14 with RMA smoothing.
- TSOT Settings: Hard-coded to identify percentile ranks, with no user-adjustable inputs due to its intrinsic calculation method.
Trade Direction Options : Configurable to support long, short, or both directions, adaptable to the trader's market assessment.
Entry Conditions :
- Long Entry: Triggered when the price surpasses the mid Fibonacci level (50%) with a bullish TSOT signal.
- Short Entry: Activated when the price falls below the mid Fibonacci level with a bearish TSOT indication.
Exit Conditions :
- Employs ATR-based dynamic stop losses, calibrated according to current market volatility, ensuring effective risk management.
Strategy Execution :
- Risk Management: Features adjustable risk-reward settings and enables partial take profits by default to systematically secure gains.
- Position Reversal: Includes an option to reverse positions based on new TSOT signals, improving the strategy's responsiveness to evolving market conditions.
The strategy is optimized for the BYBIT:WIFUSDT.P market on a scalping (5-minute) timeframe, using the default settings outlined above.
I spent a lot of time creating the dynamic exit strategies for partially taking profits and reversing positions so please make use of those and feel free to adjust the settings, tool tips are also provided.
For Developers: this is published as open-sourced code so that developers can learn something especially on dynamic exits and partial take profits!
Good Luck!
Disclaimer
This strategy is shared for educational purposes and must be thoroughly tested under diverse market conditions. Past performance does not guarantee future results. Traders are advised to integrate this strategy with other analytical tools and tailor it to specific market scenarios. I was only sharing what I've crafted while strategizing over a Solana Meme Coin.
NASDAQ 100 Peak Hours StrategyNASDAQ 100 Peak Hours Trading Strategy
Description
Our NASDAQ 100 Peak Hours Trading Strategy leverages a carefully designed algorithm to trade within specific hours of high market activity, particularly focusing on the first two hours of the trading session from 09:30 AM to 11:30 AM GMT-5. This period is identified for its increased volatility and liquidity, offering numerous trading opportunities.
The strategy incorporates a blend of technical indicators to identify entry and exit points for both long and short positions. These indicators include:
Exponential Moving Averages (EMAs) : A short-term 9-period EMA and a longer-term 21-period EMA to determine the market trend and momentum.
Relative Strength Index (RSI) : A 14-period RSI to gauge the market's momentum.
Average True Range (ATR) : A 14-period ATR to assess market volatility and to set dynamic stop losses and trailing stops.
Volume Weighted Average Price (VWAP) : To identify the market's average price weighted by volume, serving as a benchmark for the trading day.
Our strategy uniquely applies a volatility filter using the ATR, ensuring trades are only executed in conditions that favor our setup. Additionally, we consider the direction of the EMAs to confirm the market's trend before entering trades.
Originality and Usefulness
This strategy stands out by combining these indicators within the NASDAQ 100's peak hours, exploiting the specific market conditions that prevail during these times. The inclusion of a volatility filter and dynamic stop-loss mechanisms based on the ATR provides a robust method for managing risk.
By focusing on the early trading hours, the strategy aims to capture the initial market movements driven by overnight news and the opening rush, often characterized by higher volatility. This approach is particularly useful for traders looking to maximize gains from short-term fluctuations while limiting exposure to longer-term market uncertainty.
Strategy Results
To ensure the strategy's effectiveness and reliability, it has undergone rigorous backtesting over a significant dataset to produce a sample size of more than 100 trades. This testing phase helps in identifying the strategy's potential in various market conditions, its consistency, and its risk-to-reward ratio.
Our backtesting adheres to realistic trading conditions, accounting for slippage and commission to reflect actual trading scenarios accurately. The strategy is designed with a conservative approach to risk management, advising not to risk more than 5-10% of equity on a single trade. The default settings in the script align with these principles, ensuring that users can replicate our tested conditions.
Using the Strategy
The strategy is designed for simplicity and ease of use:
Trade Hours : Focuses on 09:30 AM to 11:30 AM GMT-5, during the NASDAQ 100's peak activity hours.
Entry Conditions : Trades are initiated based on the alignment of EMAs, RSI, VWAP, and the ATR's volatility filter within the designated time frame.
Exit Conditions : Includes dynamic trailing stops based on ATR, a predefined time exit strategy, and a trend reversal exit condition for risk management.
This script is a powerful tool for traders looking to leverage the NASDAQ 100's peak hours, providing a structured approach to navigating the early market hours with a robust set of criteria for making informed trading decisions.
Ehlers Combo Strategy🚀 Presenting the Enhanced Ehlers Combo Strategy 🚀
Hello Traders! 👋 I'm thrilled to share the latest version of the Ehlers Combo Strategy v2.0. This powerful algorithm combines Ehlers Elegant Oscillator, Decycler, Instantaneous Trendline, Spearman Rank, and introduces the Signal to Noise Ratio for even more precise trading signals.
📊 Strategy Highlights:
Ehlers Elegant Oscillator: Captures market momentum and turning points.
Ehlers Decycler: Filters out market noise for clearer trend signals.
Instantaneous Trendline: Offers a dynamic view of the market trend.
Spearman Rank: Analyzes market rank correlations for enhanced insights.
Signal to Noise Ratio (SNR): Filters out noise for more accurate signals.
💡 Key Features & Customizations:
Adaptive Length: Enable adaptive length based on the market's current conditions.
SNR Threshold: Set your desired SNR threshold for filtering signals.
Exit Length: Define the length for exit signals.
📈 Trading Signals:
Long Entry: Elegant Oscillator and Decycler cross above 0, source crosses above Decycler, source is greater than an increasing Instantaneous Trendline, Spearman Rank is positive, and SNR exceeds the threshold.
Long Exit: Source crosses below the Instantaneous Trendline after entering a long position.
Short Entry: Elegant Oscillator and Decycler cross below 0, source crosses below Decycler, source is less than a decreasing Instantaneous Trendline, Spearman Rank is negative, and SNR exceeds the threshold.
Short Exit: Source crosses above the Instantaneous Trendline after entering a short position.
📊 Insights & Enhancements:
Dynamic Length: The strategy adapts its length dynamically based on market conditions.
Improved SNR: Signal to Noise Ratio ensures better filtering of signals.
Enhanced Visualization: The Elegant Oscillator now features improved color coding for a clearer interpretation.
🚨 Disclaimer:
Trading involves risk, and this script should be used judiciously. It's not a guaranteed profit machine, but with careful use, it can be a valuable addition to your toolkit.
Feel free to backtest, tweak, and make it your own! Let's conquer the markets together! 💪📈
🚀✨ Happy Trading! ✨🚀
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🙌 Credits:
A big shoutout to the original contributors:
@blackcat1402
@cheatcountry
@DasanC
Golden Transform The Golden Transform Oscillator contains multiple technical indicators and conditions for making buy and sell decisions. Here's a breakdown of its components and what it's trying to achieve:
Strategy Setup:
The GT is designed to be plotted on the chart without overlaying other indicators.
Rate of Change (ROC) Calculation:
The Rate of Change (ROC) indicator is calculated with a specified period ("Rate of Change Length").
The ROC measures the percentage change in price over the specified period.
Hull Modified TRIX Calculation:
The Hull Modified TRIX indicator is calculated with a specified period ("Hull TRIX Length").
The Hull MA (Moving Average) formula, a modified WMA, is used to calculate a modified TRIX indicator, which is a momentum oscillator.
Hull MA Calculation:
A Hull Moving Average (Hull MA) is calculated as an entry filter.
Fisher Transform Calculation:
The Fisher Transform indicator is calculated to serve as a preemptive exit filter.
It involves mathematical transformations of price data to create an oscillator that can help identify potential reversals. The Fisher Transform is further smoothed using a Hull Moving Average (HMA).
Conditions and Signals:
Long conditions are determined based on crossovers between ROC and TRIX, as well as price relative the the MA. Short conditions are inversed.
Exit Conditions:
Exit conditions are defined for both long and short positions.
For long positions, the strategy exits if ROC crosses under TRIX, or if the smoothed Fisher Transform crosses above a threshold and declines. Once again, short conditions are the inverse.
Visualization and Plotting:
The script uses background colors for entry and shapes for exits to highlight different levels and conditions for the ROC/TRIX correlation.
It plots the Fisher Transform values and a lag trigger on the chart.
Overall, this script is a complex algorithm that combines multiple technical indicators and conditions to generate trading signals and manage positions in the financial markets. It aims to identify potential entry and exit points based on the interplay of the mentioned indicators and conditions.
Crunchster's Turtle and Trend SystemThis is a combination of two popular systematic trading strategies - in the trend following category.
The strategy is designed for use on the daily timeframe. Specific features of this system are outlined below:
1. Two different strategies to choose from, "Trend" which is a volatility adjusted Exponential Moving Average (EMA) crossover strategy and "Breakout" which is my adaptation of the well documented "Turtle Strategy"
2. Uses advanced position sizing and risk management, usually reserved for institutional portfolio management, a proven technique utilised by Commodity Trading Advisors and Managed Futures funds (Algo/Quant funds).
"Trend" uses a fast (user defined) and slow EMA crossover, where the slow length is 5 times the fast length. The resulting signal is adjusted for the volatility of returns over a 252 lookback period, which helps to normalise the signal across different assets. The system goes long or short when it detects a new trend has formed.
"Break" uses the highest high or lowest low over a user defined lookback period to define the recent range. This is converted into a price normalised signal to allow the system to detect when a breakout occurs. The system goes long or short based off the breakout signal.
Position sizing is based on recent price volatility and the user defined annualised risk target. In essence positions are inverse volatility weighted, so larger size is opened during lower volatility and smaller size during increased volatility. Recent volatility is calculated as the standard deviation of returns with 14 period lookback, then extrapolated into an annualised volatility of expected returns. Annualised recent volatility is then referenced to the risk target set by the user to adjust the position size. The default settings are a conservative 15% annual risk target/volatility. Initial capital should be set as the maximum risk capital per trade (ie if $10,000 total capital and 10% risk per trade, initial capital should be $1000). Maximum leverage per position can be set independently, to facilitate hitting risk targets that are greater than the natural volatility of the traded asset, and to accommodate low volatility conditions, whilst maintaining overall risk controls. Direction (long or short) is at the user's discretion.
Hard stop losses are based on multiples of the average true range of recent price (14 period lookback), user configurable.
Strategy trailing stops are based off recent highest highs or lowest lows (user defined lookback) to cut the position if the trend or momentum is lost.
Although both strategies can be run simultaneously, optimal diversification will be achieved if ran separately/individually to avoid masking of entries.
Quantitative Trend Strategy- Uptrend longTrend Strategy #1
Indicators:
1. SMA
2. Pivot high/low functions derived from SMA
3. Step lines to plot support and resistance based on the pivot points
4. If the close is over the resistance line, green arrows plot above, and vice versa for red arrows below support.
Strategy:
1. Long Only
2. Mutable 2% TP/1.5% SL
3. 0.01% commission
4. When the close is greater than the pivot point of the sma pivot high, and the close is greater than the resistance step line, a long position is opened.
*At times, the 2% take profit may not trigger IF; the conditions for reentry are met at the time of candle closure + no exit conditions have been triggered.
5. If the position is in the green and the support step line crosses over the resistance step line, positions are exited.
How to use it and what makes it unique:
Use this strategy to trade an up-trending market using a simple moving average to determine the trend. This strategy is meant to capture a good risk/reward in a bullish market while staying active in an appropriate fashion. This strategy is unique due to it's inclusion of the step line function with statistics derived from myself.
This description tells the indicators combined to create a new strategy, with commissions and take profit/stop loss conditions included, and the process of strategy execution with a description on how to use it. If you have any questions feel free to PM me and boost if you enjoyed it. Thank you, pineUSERS!
Crunchster's Normalised Trend StrategyThis is a unique rules-based, systematic trading strategy - in the trend following category.
The strategy is designed for use on the daily timeframe. Specific features of this strategy are outlined below:
1. Uses a transformed price series (which I dub "real price") to generate signals rather than ticker price
2. Uses advanced position sizing and risk management, usually reserved for institutional portfolio management, a proven technique utilised by Commodity Trading Advisors and Managed Futures funds (Algo/Quant funds).
"Real Price" is a transformed price series derived from the sum of volatility adjusted (daily) returns, over the entire price series of an asset. The lookback period of the volatility adjustment is user defined.
A Hull moving average (HMA) is derived from the real price, and used as the main trend determinant. The lookback period of the HMA is user defined. Default lookback of 100 periods (days) ensures a responsive trend indicator, but without leading to over-trading from frequent crossovers (average holding period 14 days on BTC).
The core strategy is very simple, go long when real price crosses over HMA, go short when real price crosses under HMA. New position triggers automatically close open positions in the counter direction.
Position sizing is based on recent price volatility and the user defined annualised risk target. In essence positions are inverse volatility weighted, so larger size is opened during lower volatility and smaller size during increased volatility. Recent volatility is calculated as the standard deviation of returns with 14 period lookback, then extrapolated into an annualised volatility of expected returns. Annualised recent volatility is then referenced to the risk target set by the user to adjust the position size. The default settings are a very conservative 10% annual risk target. Initial capital should be set as the maximum risk capital per trade (ie if $10,000 total capital and 10% risk per trade, initial capital should be $1000). Maximum leverage per position can be set independently, to facilitate hitting risk targets that are greater than the natural volatility of the traded asset, and to accommodate low volatility conditions, whilst maintaining overall risk controls.
Hard stop losses are based on multiples of the average true range of recent price (14 period lookback), user configurable.
Please leave comments regarding further features or refinements. I plan to develop further adding alternative moving average selections and the ability to select/deselect long and short strategies.
3 hours ago
Release Notes:
Added option to compound profits versus using a fixed position capital. Be mindful that compounding will potentially increase profits, but also increase drawdowns and overall risk. Leverage will still cap overall exposure with compounding and therefore provides an additional layer of risk control.
2 hours ago
Release Notes:
Added function to toggle long/short strategy legs on and off.
Volatility Breakout Strategy [Angel Algo]As traders, we're always looking for opportunities to profit from sudden price breakouts, and the Volatility Breakout Strategy aims to do just that.
This script is the perfect starting point for traders who want to experiment with capturing price movements resulting from increased volatility. The script plots the Average True Range (ATR) on the chart, which is a measure of the asset's volatility over a specified period. By setting the "Length" parameter, you can customize the period over which the volatility is measured.
Using the ATR, the strategy calculates upper and lower breakout levels and plots them on the chart. The signals for long and short positions are generated when the price crosses above the upper breakout level or below the lower breakout level, respectively. They are confirmed by checking the current bar state.
The strategy also fills the space between the upper and lower breakout levels with a color that indicates the latest signal direction. This feature helps traders quickly identify the prevailing trend.
The strategy uses the generated signals to enter trades. When a long or short signal is confirmed, and there is no open position in the direction of the signal, the strategy enters a long or short trade, respectively.
Choice of parameters.
Choosing the right value for the Length input parameter is crucial for tailoring the Volatility Breakout Strategy to suit your trading preferences. In general, a higher Length value implies a focus on capturing longer price moves. For instance, in this script, we have set the Length value to 20, resulting in trades that span approximately 100 candles. These trades encompass price trends consisting of multiple swings.
However, if your goal is to trade individual swings rather than longer trends, it's advisable to experiment with smaller values for the Length parameter. By reducing the Length, you can target shorter-term price movements and potentially increase the frequency of trades.
It's important to note that while a higher Length value tends to lead to longer trades, there is no strict correlation between the Length parameter and the average length of trades. This can vary across different markets. Therefore, it's essential to conduct thorough experimentation with various Length values and closely observe the length of trades they generate. Comparing these trade lengths with the average trend or swing length in the specific market can provide valuable insights.
Ideally, you should aim to select a Length value that aligns with the average trend or swing length observed in the market you are trading. This way, you can optimize the strategy to capture price movements that closely match the prevailing market conditions.
Remember, finding the optimal Length value is a process of trial and error, combined with careful observation of trade lengths and their correlation with market trends. So, don't be afraid to experiment and refine the Length parameter to maximize the effectiveness of the Volatility Breakout Strategy in your chosen market.
Disclaimer: This trading strategy is provided for educational and informational purposes only.Trading involves risk, and past performance is not indicative of future results.
Advanced Trend Detection StrategyThe Advanced Trend Detection Strategy is a sophisticated trading algorithm based on the indicator "Percent Levels From Previous Close".
This strategy is based on calculating the Pearson's correlation coefficient of logarithmic-scale linear regression channels across a range of lengths from 50 to 1000. It then selects the highest value to determine the length for the channel used in the strategy, as well as for the computation of the Simple Moving Average (SMA) that is incorporated into the strategy.
In this methodology, a script is applied to an equity in which multiple length inputs are taken into consideration. For each of these lengths, the slope, average, and intercept are calculated using logarithmic values. Deviation, the Pearson's correlation coefficient, and upper and lower deviations are also computed for each length.
The strategy then selects the length with the highest Pearson's correlation coefficient. This selected length is used in the channel of the strategy and also for the calculation of the SMA. The chosen length is ultimately the one that best fits the logarithmic regression line, as indicated by the highest Pearson's correlation coefficient.
In short, this strategy leverages the power of Pearson's correlation coefficient in a logarithmic scale linear regression framework to identify optimal trend channels across a broad range of lengths, assisting traders in making more informed decisions.
Wolfe Strategy [Trendoscope]Hello Everyone,
Wish you all Merry X-Mas and happy new year. Lets start 2023 with fresh new strategy built on Wolfe Indicator. Details of the indicator can be found here
🎲 Wolfe Concept
Wolfe concept is simple. Whenever a wedge is formed, draw a line joining pivot 1 and 4 as shown in the chart below:
For simplicity, we will only consider static value for Target and Stop. But, entry is done based on breaking the triangle. Revised strategy looks something like this:
🎲 Settings
Settings are simple and details of each are provided via tooltips.
Out of these, the most important one is minimum risk reward ratio. If you set lower risk reward threshold then losing few trades may generate more losses than more winning trades. Similarly higher value will filter out most of the trades and may not work efficiently. Default value set to 1 to make sure optimal risk reward is present before placing trade. Also make note that since the entry bar is always moving towards stop, as and when pattern progress, the RR will also increase. Hence, a pattern which is below RR threshold may become good to trade at certain point of time in future.
🎲 Strategy Parameters
Default strategy parameters are initialised via definition. Margins are set to 100 to disable leveraged trades. Appropriate values are chosen for other parameters. These can be altered based on individual strategy and trading plan.
As the strategy concentrates on the single pattern, number of trades generated are comparatively less. But, there is chance to increase the algorithm further to catch more such patterns on larger scale. Will try to work on them in next versions.
🎲 Pine Strategy limitations
Backtest can only be done on one direction as pine strategy cannot have both long and short open trades together. Hence, it is mandatory to chose either long/short trades in settings.
Since pyramiding is limited to 1, there is possibility of a pattern not generating trade even though the entry conditions are met. They are just based on pine limitations and not necessarily mean patterns are not good for placing trades.
FFT Strategy Bi-Directional Stop/Profit/Trailing + VMA + AroonThis strategy uses the Fast Fourier Transform inspired from the source code of @tbiktag for the Fast Fourier Transform & @lazybear for the VMA filter.
If you are not familiar with the Fast Fourier transform it is a variation of the Discrete Fourier Transform. Veritasium on youtube has a great video on it with a follow up recommendation from 3brown1blue. In short it will extract all the frequencies from a set of data. @tbiktag laid the groundwork for creating the indicator which will allow you to isolate only those signals which are the most relevant and remove the noise. I recommend having @tbiktag's FFT Transform indicator side by side with this to understand what my variation is doing by setting similar settings .
Using this idea, you can then optimize a strategy to the frequencies that are best. The main entry signal is when the FFT Signal crosses above or below the 0 line .
Included with this strategy is the ability to optionally bi-directionally set:
Stop Loss
Trailing Stop Loss
Take Profit
Trailing Take Profit
Entries are optionally further filtered by use of the VMA using the algorithm from LazyBear which allows you to adjust a variable moving average with 3 market trend detections. Green represents upwards momentum; Blue sideways trading and Red downwards momentum. The idea being to filter out buy or sell entries unless the market is moving in that direction, and this makes a big difference as you can see for yourself when you turn it off or on. Turning it off will change the color of the FFT signal to orange instead of the green, blue, red colors .
I have added 2 custom stop loss types as well for experimentation:
1. VMA Filter stop loss to exit the trade if the VMA detects a market trend direction change matching the rules you have set. I have set this to off by default, but it is there so you can see what affect it may have on other tickers. It can increase the profit factor but usually at a cost of net profit.
2. The Aroon Filter stop loss with different lengths for the short or long direction. For the Aroon strategy (which is a trend change detector) it is considered bullish if the upper line (green in my code) is above 70 and the lower line (red in my code) is below 30 and the opposite for the bearish case. With this in mind, I have set it to filter by default only the extreme ends (99 and 1) to increase profit factor and net profit but I encourage you to try different settings and see how it affects things. Turning this off yields much higher net profit but at the cost of the profit factor and drawdown . To disable this just uncheck the 'Use Aroon Filter Long' (or short) and it will also hide the aroon graphics and crosses on the plot.
I will be adding more features in an attempt to lower the drawdown on this strategy but I hope you enjoy what I have so far!
Double Inside Bar & Trend Strategy - KaspricciDouble Inside Bar & Trend Strategy - Kaspricci
This strategy combines the Double Inside Bar candlestick pattern with a trend filter. Once the second inside bar closes and price is above trend moving average, a buy stop order is placed at high of the candle. If price is below trend moving average, a sell stop order is placed at the low of the candle.
This strategy is for educational purposes only! It is not meant to be a financial advice.
Settings
Trend source, type of moving average and length for calculating trend
Stop Loss Type - default: ATR. You can switch between stop loss calculation based on Average True Range value or fixed value.
ATR Length / Factor / TP Ratio - default: 14 / 2.0 / 2.0. Used to calculate the Stop Loss as ATR * Factor and Take Profit as Stop Loss * TP Ratio.
FIX Stop Loss / Take Profit - default: 10 pips / 20 pips. In case you select Stop Loss Type = FIX, these value swill be used.
Risk in % - default: 1%, option to adjust the quantity of a trade based on a defined risk percentage. If enabled, it will overwrite the quantity parameter of the strategy settings.
On top you can filter trades by start and end date as well as time of the day.
Linear EDCA v1.2Strategy Description:
Linear EDCA (Linear Enhanced Dollar Cost Averaging) is an enhanced version of the DCA fixed investment strategy. It has the following features:
1. Take the 1100-day SMA as a reference indicator, enter the buy range below the moving average, and enter the sell range above the moving average
2. The order to buy and sell is carried out at different "speed", which are set with two linear functions, and you can change the slope of the linear function to achieve different trading position control purposes
3. This fixed investment is a low-frequency strategy and only works on a daily level cycle
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Strategy backtest performance:
BTCUSD (September 2014~September 2022): Net profit margin 26378%, maximum floating loss 47.12% (2015-01-14)
ETHUSD (August 2018~September 2022): Net profit margin 1669%, maximum floating loss 49.63% (2018-12-14)
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How the strategy works:
Buying Conditions:
The closing price of the day is below the 1100 SMA, and the ratio of buying positions is determined by the deviation of the closing price from the moving average and the buySlope parameter
Selling Conditions:
The closing price of the day is above the 1100 SMA, and the ratio of the selling position is determined by the deviation of the closing price and the moving average and the sellSlope parameter
special case:
When the sellOffset parameter>0, it will maintain a small buy within a certain range above the 1100 SMA to avoid prematurely starting to sell
The maximum ratio of a single buy position does not exceed defInvestRatio * maxBuyRate
The maximum ratio of a single sell position does not exceed defInvestRatio * maxSellRate
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Version Information:
Current version v1.2 (the first officially released version)
v1.2 version setting parameter description:
defInvestRatio: The default fixed investment ratio, the strategy will calculate the position ratio of a single fixed investment based on this ratio and a linear function. The default 0.025 represents 2.5% of the position
buySlope: the slope of the linear function of the order to buy, used to control the position ratio of a single buy
sellSlope: the slope of the linear function of the order to sell, used to control the position ratio of a single sell
sellOffset: The offset of the order to sell. If it is greater than 0, it will keep a small buy within a certain range to avoid starting to sell too early
maxSellRate: Controls the maximum sell multiple. The maximum ratio of a single sell position does not exceed defInvestRatio * maxSellRate
maxBuyRate: Controls the maximum buy multiple. The maximum ratio of a single buy position does not exceed defInvestRatio * maxBuyRate
maPeriod: the length of the moving average, 1100-day MA is used by default
smoothing: moving average smoothing algorithm, SMA is used by default
useDateFilter: Whether to specify a date range when backtesting
settleOnEnd: If useDateFilter==true, whether to close the position after the end date
startDate: If useDateFilter==true, specify the backtest start date
endDate: If useDateFilter==true, specify the end date of the backtest
investDayofweek: Invest on the day of the week, the default is to close on Monday
intervalDays: The minimum number of days between each invest. Since it is calculated on a weekly basis, this number must be 7 or a multiple of 7
The v1.2 version data window indicator description (only important indicators are listed):
MA: 1100-day SMA
RoR%: floating profit and loss of the current position
maxLoss%: The maximum floating loss of the position. Note that this floating loss represents the floating loss of the position, and does not represent the floating loss of the overall account. For example, the current position is 1%, the floating loss is 50%, the overall account floating loss is 0.5%, but the position floating loss is 50%
maxGain%: The maximum floating profit of the position. Note that this floating profit represents the floating profit of the position, and does not represent the floating profit of the overall account.
positionPercent%: position percentage
positionAvgPrice: position average holding cost
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策略说明：
Linear EDCA（Linear Enhanced Dollar Cost Averaging）是一个DCA定投策略的增强版本，它具有如下特性：
1. 以1100日SMA均线作为参考指标，在均线以下进入定买区间，在均线以上进入定卖区间
2. 定买和定卖以不同的“速率”进行，它们用两条线性函数设定，并且你可以通过改变线性函数的斜率，以达到不同的买卖仓位控制的目的
3. 本定投作为低频策略，只在日级别周期工作
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策略回测表现：
BTCUSD（2014年09月~2022年09月）：净利润率26378%，最大浮亏47.12%（2015-01-14）
ETHUSD（2018年08~2022年09月）：净利润率1669%，最大浮亏49.63%（2018-12-14）
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策略工作原理：
买入条件：
当日收盘价在 1100 SMA 之下，由收盘价和均线的偏离度，以及buySlope参数决定买入仓位比例
卖出条件：
当日收盘价在 1100 SMA之上，由收盘价和均线的偏离度，以及sellSlope参数决定卖出仓位比例
特例：
当sellOffset参数>0，则在 1100 SMA以上一定范围内还会保持小幅买入，避免过早开始卖出
单次买入仓位比例最大不超过 defInvestRatio * maxBuyRate
单次卖出仓位比例最大不超过 defInvestRatio * maxSellRate
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版本信息：
当前版本v1.2（第一个正式发布的版本）
v1.2版本设置参数说明：
defInvestRatio: 默认定投比例，策略会根据此比例和线性函数计算得出单次定投的仓位比例。默认0.025代表2.5%仓位
buySlope: 定买的线性函数斜率，用来控制单次买入的仓位倍率
sellSlope: 定卖的线性函数斜率，用来控制单次卖出的仓位倍率
sellOffset: 定卖的偏移度，如果大于0，则在一定范围内还会保持小幅买入，避免过早开始卖出
maxSellRate: 控制最大卖出倍率。单次卖出仓位比例最大不超过 defInvestRatio * maxSellRate
maxBuyRate: 控制最大买入倍率。单次买入仓位比例最大不超过 defInvestRatio * maxBuyRate
maPeriod: 均线长度，默认使用1100日MA
smoothing: 均线平滑算法，默认使用SMA
useDateFilter: 回测时是否要指定日期范围
settleOnEnd: 如果useDateFilter==true，在结束日之后是否平仓所持有的仓位平仓
startDate: 如果useDateFilter==true，指定回测开始日期
endDate: 如果useDateFilter==true，指定回测结束日期
investDayofweek: 每次在周几定投，默认在每周一收盘
intervalDays: 每次定投之间的最小间隔天数，由于是按周计算，所以此数字必须是7或7的倍数
v1.2版本数据窗口指标说明（只列出重要指标）：
MA：1100日SMA
RoR%: 当前仓位的浮动盈亏
maxLoss%: 仓位曾经的最大浮动亏损，注意此浮亏代表持仓仓位的浮亏情况，并不代表整体账户浮亏情况。例如当前仓位是1%，浮亏50%，整体账户浮亏是0.5%，但仓位浮亏是50%
maxGain%: 仓位曾经的最大浮动盈利，注意此浮盈代表持仓仓位的浮盈情况，并不代表整体账户浮盈情况。
positionPercent%: 仓位持仓占比
positionAvgPrice: 仓位平均持仓成本
The Only EURUSD Trading Strategy You Need - KaspricciThe Only EURUSD Trading Strategy You Need
I got the idea to this strategy from a youtube video uploaded by Trade Beta. It is designed to capture the early market move of major forex pair EURUSD at beginning of New York Stock Exchange (13:30 GMT). Trade Beta tested his strategy on the 5 minute chart. I have set all parameters to same values as shown in the video.
The strategy creates two pending orders at the recent swing high and low. Once the first pending order entered, the remaining one is cancelled. Latest at the end of market session all pending orders are cancelled and all open trade are closed as well.
In rare case that price at session opening is above swing high, only a pending sell stop order is created at swing high price. And in case price is below swing low, a pending buy stop order is created.
Settings
Trading Time - default: New York Stock Exchange opening hours. Pending orders are created at the close of the first candle within the session.
Swing High Source / Bars - default: High / 5 bars. Used to find the latest swing high within a range of 5 bars left and right. Price is used for buy stop order.
Swing Low Source / Bars - default: Low / 5 bars. Used to find the latest swing low within a range of 5 bars left and right. Price is used for sell stop order.
Stop Loss Type - default: ATR. You can switch between stop loss calculation based on Average True Range value or fixed value.
ATR Length / Factor / TP Ratio - default: 14 / 2.0 / 2.0. Used to calculate the Stop Loss as ATR * Factor and Take Profit as Stop Loss * TP Ratio.
FIX Stop Loss / Take Profit - default: 10 pips / 20 pips. In case you select Stop Loss Type = FIX, these value swill be used.
This strategy is for educational purposes only! It is not meant to be a financial advice.
50 Pips A Day Strategy - Kaspricci50 Pips A Day Strategy
This strategy is designed to work on 1 hour timeframe. It is designed to capture the early market move of major forex pairs like EURUSD or GBPUSD. It takes the high and low of the first candle (7 a.m. GMT, London Stock Exchange opens) and places to pending orders at these prices levels.
High + additional gap in pips = buy stop pending order
Low + additional gap in pips = sell stop pending order
For both orders a stop loss of 15 pips and a take profit of 50 pips is used as a default. As soon as price triggers one pending order, the remaining pending order is cancelled. At the end of the configured session time all open and pending orders are closed / cancelled.
Settings
Trading Time - start and end time of session. It is configured for Monday to Friday only. At the beginning the first candle is used to define stop prices for pending orders.
Source for Buy Stop order - Default: high. Used to calculate buy stop order. You can add additional pips as a gap.
Source for Sell Stop order - Default: low. Used to calculate sell stop order. You can add additional pips as a gap.
Stop Loss in Pips - Default: 15. Used for both pending orders.
Take Profit in Pips - Default: 50. Used for both pending orders.
This strategy is for educational purposes only! It is not meant to be a financial recommendation.
TradeIQ - Crazy Scalping Trading Strategy [Kaspricci]This strategy script is a combination of two indicators developed by LuxAlgo:
Triangular Momentum Oscillator & Real Time Divergences ( TMO )
Adjustable MA & Alternating Extremities (AMA)
The script combines the BUY and SELL signals from the TMO indicator with the BUY and SELL extremities shown by the AMA script and waits for the smoothed candles to grow in size. It places a SHORT or LONG order and sets a stop loss at the latest swing high or low (highes high or lowest low for a defined number of recent bars). A new LONG trade is highlighted by a green background. A new SHORT trade is highlighted by red background.
The trades will be closed once a new TMO indicator BUY or SELL signal appears or the color of the AMA extremities is switching from green to red and vice versa.
All parameters of TOM and AMA indicators are added as well and work the same way as in the original scripts provided by LuxAlgo.
The idea to combine these two indicators has been provided to me by TradIQ in his youtube video.
Please leave a comment in case you find a bug. In case you find a combination of parameters with a high win rat and high PnL I would be interested as well.
Andean ScalpingAndean Scalping Implementation - BETA
- Uses Andean Oscillator: alpaca.markets
- Implements a threshold moving average (SMA 1000) on the Andean Signal line at 1.1 factor to filter out small moves
- TP/SL using ATR bands at 3x multiplier
VXD SupercycleVXD is a brand new indicator and still developing. to minimize stop losses and overcome sideways market conditions, Higher Timeframe are recommended
Trend lines
-using Rolling VWAP as trend line to determined if Volume related to a certain price.
-you can switch RVWAP to EMA in the setting
ATR
-trailing 12*ATR and 2.4 Mutiplier
Pivot point and Rejected Block
Pivot show last High and low of a price in past bars
Rejected Block show when that High or Low price are important level to determined if it's Hidden Divergence or Divergence
Symbols on chart show Premium and Discount Prices
X-Cross - show potential reversal trend with weak volume .
O-circle - show potential reversal trend with strong volume .
Setting
Momentum: RSI = 25 , RSI MA = 14
Trend: Rolling VWAP and ATR and Subhag
Trailing STOP: ATR 12 x 2.4
Highlight Bars color when volume is above SMA 6
SMA200 act as TP Line
Risk:Reward Calculation
if Buy your Stoploss will be previous Pivot low
if Sell your Stoploss will be previous Pivot high and will be calculated form there, then show TP in Orange color line
VXD เป็นระบบเทรดที่ผมทดลองเอาหลาย ๆ ไอเดีย ทั้งจาก Youtube facebook และกลุ่มคนต่าง ๆ มารวบรวมไว้ แล้วตกผลึกขึ้นมาเป็นระบบนี้ ใน Timeframe ใหญ่ ๆ สามารถลากได้ทั้ง Cycle กันเลย
Trend lines
-ใช้ Rolling VWAP ของแอพ Tradingview (สามารถตั้งแค่าเป็น EMA ได้)
ATR
-ใช้ค่า ATR 12 Mutiplier 2.4
Pivot point and Rejected Block
Pivot โชว์เส้น High low และมีผลกับออเดอร์ หากแท่งเทียนปิดทะลุเส้นนี้
Rejected Block วาดแนวรับ-ต้าน อัตโนมัติ ใช้ประกอบ RSI ว่ามี Divergence หรือไม่
สัญลักษณ์ต่าง ๆ
X-Cross - แท่งกลืนกิน วอลุ่มน้อย
O-circle - แท่งกลืนกิน มีวอลุ่ม
Setting
Momentum: RSI = 25 , RSI MA = 14
Trend: Rolling VWAP and ATR and Subhag
Trailing STOP: ATR 12 x 2.4
Highlight Bars color when volume is above SMA 6
SMA200 act as TP Line
Risk:Reward Calculation
หาก Buy จุด SL จะอยู่ที่ Pivot low
หาก Sell จุด SL จะอยู่ที่ Pivot high และระบบจะคำนวณจากตรงนั้น จากนั้นแสดงเป็นเส้น TP สีส้ม
This Strategy Combined the following indicators and conditioning by me
ATR , RSI , EMA , SMA
Rolling VWAP - /script/ZU2UUu9T-Rolling-VWAP/
Regression Lines - Subhag form Subhag Ghosh /script/LHHBVpQu-Subhag-Ghosh-Algo-Version-for-banknifty/
Rejection Block , Pivots , High Volume Bars and PPDD form Super OrderBlock / FVG / BoS Tools by makuchaku & eFe /script/aZACDmTC-Super-OrderBlock-FVG-BoS-Tools-by-makuchaku-eFe/
ขอให้รวยครับ.
Estrategia Larry Connors [JoseMetal]============
ENGLISH
============
- Description:
This strategy is based on the original Larry Connors strategy, using 2 SMAs and RSI.
The strategy has been optimized for better total profit and works better on 4H (tested on BTCUSDT).
LONG:
Price must be ABOVE the slow SMA.
When a candle closes in RSI oversold area, the next candle closes out of the oversold area and the closing price is BELOW the fast SMA = open LONG.
LONG is closed when a candle closes ABOVE the fast SMA.
SHORT:
Price must be BELOW the slow SMA.
When a candle closes in RSI overbought area, the next candle closes out of the overbought area and the closing price is ABOVE the fast SMA = open SHORT.
SHORT is closed when a candle closes BELOW the fast SMA.
*Larry Connor's strategy does NOT use a fixed Stop Loss or Take Profit, as he said, that reduces performance significantly.
- Visual:
Both SMAs (fast and slow) are shown in the chart.
By default, the fast SMA is aqua color, the slow changes between green and red depending on the "trend" (price over slow SMA = bullish, below = bearish).
RSI can't be shown because TradingView doesn't allow to show both overlay and panel indicators, so candles get a RED color when RSI is in OVERBOUGHT area and GREEN when they're on OVERSOLD area to help with that.
Background is colored when conditions are met and a position is going to be open, green for LONGs red for SHORTs.
- Usage and recommendations:
As this is a coded strategy, you don't even have to check for indicators, just open and close trades as the strategy shows.
The original strategy uses a 5 period SMA instead of the 10, and 10/90 for oversold/overbought levels, this has been optimized after the testings and results but feel free to change settings and test by yourself.
Also, the original strategy was developed for daily, but seems to work better en 4H.
- Customization:
As usual I like to make as many aspects of my indicators/strategies customizable, indicators, colors etc., feel free to ask if you feel that something that should be configurable is missing or if you have any ideas to optimize the strategy.
============
ESPAÑOL
============
- Descripción:
Esta estrategia está basada en la estrategia original de Larry Connors, utilizando 2 SMAs y RSI.
La estrategia ha sido optimizada para un mejor beneficio total y funciona mejor en 4H (probado en BTCUSDT).
LONG:
El precio debe estar por encima de la SMA lenta.
Cuando una vela cierra en la zona de sobreventa del RSI, la siguiente vela cierra fuera de la zona de sobreventa y el precio de cierre está POR DEBAJO de la SMA rápida = abre LONG.
Se cierra cuando una vela cierra POR ENCIMA de la SMA rápida.
SHORT:
El precio debe estar POR DEBAJO de la SMA lenta.
Cuando una vela cierra en la zona de sobrecompra del RSI, la siguiente vela cierra fuera de la zona de sobrecompra y el precio de cierre está POR ENCIMA de la SMA rápida = abre SHORT.
Se cierra cuando una vela cierra POR DEBAJO de la SMA rápida.
*La estrategia de Larry Connor NO utiliza un Stop Loss o Take Profit fijo, como él dijo, eso reduce el rendimiento significativamente.
- Visual:
Ambas SMAs (rápida y lenta) se muestran en el gráfico.
Por defecto, la SMA rápida es de color aqua, la lenta cambia entre verde y rojo dependiendo de la "tendencia" (precio por encima de la SMA lenta = alcista, por debajo = bajista).
El RSI no puede mostrarse porque TradingView no permite mostrar tanto los indicadores superpuestos como los del panel, así que las velas obtienen un color ROJO cuando el RSI está en el área de SOBRECOMPRA y VERDE cuando están en el área de VENTA para ayudar a ello.
El fondo se colorea cuando se cumplen las condiciones y se va a abrir una posición, verde para LONGs rojo para SHORTs.
- Uso y recomendaciones:
Como se trata de una estrategia ya programada, ni siquiera hay que comprobar los indicadores, sólo hay que abrir y cerrar las operaciones tal y como muestra la estrategia en el gráfico.
La estrategia original utiliza una SMA de 5 periodos en lugar de 10, y 10/90 para los niveles de sobreventa/sobrecompra, esto ha sido optimizado después de las pruebas y los resultados, pero sé libre de cambiar la configuración y probarla por sí mismo.
Además, la estrategia original fue desarrollada para diario, pero parece funcionar mejor en 4H.
- Personalización:
Como siempre me gusta hacer personalizables todos los aspectos de mis indicadores/estrategias, indicadores, colores, etc., preguntar si notas que falta algo que debería ser configurable o si tienes alguna idea para optimizar la estrategia.
Portfolio Performance - Effects of RebalancingFunction:
- Can be used to evaluate the performance of a portfolio containing 2 assets over a set time interval
- Shows the % return of the portfolio over the time interval defined by the user
- Includes a threshold rebalancing algorithm to show the effects that rebalancing has on the portfolio over the long term
- Created to evaluate of the performance of portfolios containing different weightings of stocks and bonds over time assuming that the user would rebalance the portfolio when asset weights crossed a threshold
Instructions:
- To be used with dividends adjustments turned on
- Add this script to a symbol. e.g. AMEX:SPY
- Click the chart to define the entry time and the exit time. i.e. the time interval
- Define the initial investment of the portfolio. Default setting is $100,000
- Define the second asset to be included in the portfolio. e.g. BATS:AGG
- The strategy comes pre-populated with a portfolio that has a weight of 80% asset 1 and 20% asset 2. i.e. 80% AMEX:SPY and 20% BATS:AGG if the symbols mentioned above were chosen
- The 7 lines show the weighted % return of each portfolio over the time period defined by the user
- Each line (except the blue) is the return based on a different rebalancing threshold. The default settings are 1%, 2.5%, 5%, 10%, 15%, 20%, 30%
- The blue line is the % return of a portfolio that was made up of 100% asset 1 over the time interval. i.e. 100% AMEX:SPY
- Asset weights and rebalancing thresholds are adjustable via the settings
- Each plot can be turned on and turned off via a tick box in the settings
B.Bands | Augmented | Intra-range | Long-OnlyHere you have the essential trading engine based on Bollinger Bands .
The idea behind is to trade the intra-range of the bands.
How is going to work?
Define which Bollinger Bands we want to use. Classic Bollinger Bands or Augmented Bollinger Bands . Without selecting, the algorithm doesn't show a strategy.
Define the length of the Moving Average and the Standard Deviation by default the classic 20-2.
Define the Bollinger Bands Spread Max Range (Upper-Lower) to be able to determine wheter or not you're in a price range or potential breakout.
Define data source to trigger exit and entry points.
Define profit based on Middle Band or Opposite Band.
Define Stop Loss % and activate Trailing Stop if desired with the percentage required.
Determine if you want to sell only on profit after triggering the entry signal. * Note Stop Loss remains activated.
Choose a date range if you want to study a specific period.
Bear in mind, this is the essential trading engine, open for you to test, try and improve under your requirements. You can determinate when is the ideal market to implement it based on many other indicators. Maybe you wish to change the stop loss settings for ATR, previous low, etc. Totally up to you.
Note the script comes with initial capital, fee % and slippage by deault. This may change for your assets. Make sure you define it in advance.
NOTE: If you trade assets such BTC, you must update the initial capital. By default 5000 (USD) The script doesn't support fraction trading such 0.01BTC.
Will be updated on next version.
Feel free to get in touch if you've got any question.
