This repository serves as a personal collection of strategies I've been exploring, with a focus on understanding and applying the principles of trend trading.
I develop trend trading strategies, which involve identifying and leveraging long-term market movements. Trend trading is based on the idea that markets exhibit persistent directions (trends) over time. These strategies often look for 'fat-tail' distributions, where rare, significant events provide substantial trading opportunities.
Before considering backtesting, I employ Monte-Carlo permutation tests. These simulations are crucial for understanding the role of randomness in a strategy's performance. They help in distinguishing between actual strategy effectiveness and outcomes influenced by chance. This is especially important in trend trading, where aligning with long-term market trends could be mistaken for random fluctuations.
After confirming a strategy's potential through Monte-Carlo testing, I move to backtesting it against historical data. This process is critical for assessing a strategy's viability and success probability in real-world conditions. It's important to conduct backtesting after Monte-Carlo tests to avoid overfitting strategies to historical data, which can give misleadingly optimistic results.
| Date Added | Strategy Name | Markets Tested On | P-Value | Profit Factor | No. of Parameters | Indicators Used | Original Source |
|---|---|---|---|---|---|---|---|
| 06/02/2023 | ATR Volatility Break | Bitcoin | < 0.005 | 1.6 (backtest) | 2 | SMA, ATR | N/A |
| 07/02/2023 | Trend Line Breakout | Crypto Portfolio | N/A | N/A | 1 | Trend Channel | N/A |
Note: This table will be updated as more strategies are developed and analyzed.
The p-value in the context of these strategies indicates the probability of achieving similar results by chance. A lower p-value suggests that the strategy's performance is less likely to be due to random fluctuations and more likely due to its inherent effectiveness.
This strategy utilizes the Average True Range (ATR), a measure of market volatility. It's designed to capitalize on market trends following significant volatility breakouts. The strategy is based on the premise that high volatility periods, indicated by an elevated ATR, can often precede major market trends.
This strategy focuses on the concept of trend line breaks. It operates on the principle that when a significant trend line is broken, a new trend is likely to start in the direction of the break. The strategy aims to identify these pivotal moments and capitalize on the ensuing trend, providing opportunities for strategic entry and exit points in the market.
While this is a personal project, I welcome feedback and contributions. Collaborative discussions and suggestions are invaluable for refining these strategies.
Please note that the content in this repository is for educational and professional purposes only and is not intended as financial advice. It should not be taken as a recommendation for any specific investment strategy or as a guarantee of performance.