As the new year approaches
I’m at a crossroads - should I stick with my current investment portfolio, enjoying the stability it offers, or dive back into trading, where the thrill of the market comes with both higher stakes and the potential for greater rewards?
At times good enough is good enough
I've refined my approach and the initial results aren't too shabby.
As the new year approaches
I’ve decided to embrace both investing and trading simultaneously. Why choose one over the other when I can enjoy the benefits of both? Investing for dividends and franking credits provides stability, while trading offers the thrill and potential for significant capital growth. Trading has always been kind to me, and frankly, investing can be as exciting as "watching paint dry". My records show that investing yields around 9%, but my trading returns since 2015 have been significantly higher.
This morning, while browsing the platform ‘X’
I came across an invitation to try Grok2. Intrigued, I asked Grok2 to evaluate my trading strategy for the new year. My Amibroker Strategy, which contains 1129 lines of code, was fully accepted and quickly evaluated by Grok2, something most free ‘AI’ tools can’t handle.
Grok2’s response was insightful and valuable to me, though it might not be as interesting to others. It’s been challenging to find engaging content to post about lately, but I’m excited to share the Grok2 evaluation unaltered with highlights added. General warnings are displayed in red.
As the new year approaches
I’ve decided to embrace both investing and trading simultaneously. Why choose one over the other when I can enjoy the benefits of both? Investing for dividends and franking credits provides stability, while trading offers the thrill and potential for significant capital growth. Trading has always been kind to me, and frankly, investing can be as exciting as "watching paint dry". My records show that investing yields around 9%, but my trading returns since 2015 have been significantly higher.
This morning, while browsing platform ‘X’
I came across an invitation to try Grok2. Intrigued, I asked Grok2 to evaluate my trading strategy for the new year. My Amibroker Strategy, which contains 1129 lines of code, was fully accepted and quickly evaluated by Grok2, something most free ‘AI’ tools can’t handle.
Grok2’s Insights: A Personal Take
Grok2’s response was insightful and valuable to me, though it might not be as interesting to others. It’s been challenging to find engaging content to post about lately, but I’m excited to share this unaltered evaluation with “warnings” highlighted in RED.
MY QUESTION to Grok2 - "Please evaluate my Amibroker Trading Strategy"
Your Amibroker Trading Strategy appears to be a comprehensive and well-thought-out approach to trading, especially tailored for weekly interval analysis. Here's an evaluation of its key components:
General Observations:
Complexity and Adaptability: The strategy incorporates multiple filters and parameters, making it highly adaptable but also complex.
This could be a double-edged sword; it provides flexibility but might be overwhelming for users less familiar with Amibroker or trading algorithms.
Market and Security Selection:
Price Filter: Helps in focusing on stocks within a specific price range, which can be crucial for managing risk or targeting specific market segments.
Turnover, Volume, and Volatility Filters:
These combined filters aim to select securities with adequate liquidity and within manageable volatility, potentially reducing slippage and improving trade execution.
Trend and Momentum Analysis:
The strategy uses Exponential Moving Averages (EMA), Rate of Change (ROC), and Relative Strength Index (RSI) for entry signals, which is good for capturing trends and momentum.
However, the reliance on multiple indicators might lead to over-optimization unless carefully backtested across different market conditions.
Entry and Exit Rules:
Entry Signals: Based on conditions like price above support levels, EMA crossovers, and RSI thresholds, which are traditional momentum and trend-following techniques.
Exit Strategy: Incorporates a trailing stop with different levels based on market direction, a time-based exit, and a take-profit mechanism. The use of different stop types (trailing, stale, profit take) shows a nuanced approach to risk management, which is commendable.
Risk Management:
The strategy includes parameters for setting stop-loss levels dynamically and considering position sizing based on fixed risk amounts or equity percentages. This is a strong aspect, as proper risk management can significantly impact long-term performance.
Visualization and Reporting:
Extensive use of graphical functions for title display and charts, which can enhance user interaction and decision-making. The exploration mode offers various views on trade setup and performance, which is excellent for analysis.
Potential Areas for Improvement:
Parameter Sensitivity:
Given the many parameters, there's a risk of overfitting. Regular out-of-sample testing and possibly reducing the number of variables or using more robust optimization methods might mitigate this.
Backtesting and Validation:
While the code includes custom backtesting, ensuring this is done across various market conditions, including bull, bear, and sideways markets, would validate the strategy's robustness.
Execution Considerations:
The strategy's weekly timeframe might not be ideal for all markets or securities, especially in faster-moving or less liquid environments. Adjusting for different intervals or testing on different time frames could be beneficial.
Code Efficiency:
The use of loops for performance-sensitive tasks like updating arrays could potentially be optimized using vector operations if possible, to increase speed in backtesting or real-time analysis.
Debugging and Logging:
More extensive logging could help in diagnosing issues during live trading or backtesting, especially for complex logic like the stop calculations.
Conclusion:
Overall, your strategy is detailed and seems designed with a good balance of trend following, momentum capture, and risk management. The key to success will be in rigorous testing, perhaps with some simplification of parameters to avoid overfitting, and continuous adjustment based on market feedback. Also, consider how this strategy performs in different market environments and possibly how it could be adjusted for different securities or market types.
Skate.