vibe coded an algorithm to day trade my PA (+77% LTM)

Based on the most helpful WSO content, your approach to building and testing this algorithm is both ambitious and methodical. Here are some insights and considerations to refine or validate your strategy:

1. Risk Management:

   • Your focus on risk thresholds (max position size, beta exposure, decay exposure, etc.) aligns with best practices. As highlighted in WSO threads, disciplined risk management is critical. Ensure your algorithm adheres strictly to these thresholds, as even minor deviations can compound into significant risks over time.

2. Sector-Specific Trading:

   • Limiting trades to the sector you work in is a smart move. As noted in WSO discussions, understanding the nuances of your market (e.g., key players, events, and positioning) gives you a significant edge. However, ensure your algorithm accounts for sector-specific volatility and correlations, as these can amplify risks.

3. Approved Information Sources:

   • Restricting the algorithm to high-quality sources like Bloomberg, WSJ, SEC filings, and Value Investing Club is a solid strategy. WSO threads often emphasize the importance of avoiding "noise" from unreliable sources. However, be cautious of overfitting to recent data, as this can lead to short-term biases.

4. Manual Data Feeds:

   • Periodically feeding the algorithm with vendor data is a practical workaround for its lack of direct access. Just ensure the data is clean and consistent, as "garbage in, garbage out" is a common pitfall in algorithmic trading.

5. Time Range of Information:

   • Limiting the algorithm to recent data (e.g., past two weeks or the most recent 10-Q) is a double-edged sword. While it ensures relevance, it may overlook longer-term trends or anomalies. Consider testing different time ranges to find the optimal balance.

6. Paper Portfolio Testing:

   • Running a paper portfolio for three months before deploying real money is a textbook move. As WSO threads suggest, this allows you to identify and address any flaws in the algorithm without financial risk. However, keep in mind that paper trading often lacks the psychological and execution challenges of live trading.

7. Performance (+77% LTM):

   • A 77% return is impressive, but it's essential to evaluate the risk-adjusted performance. Metrics like Sharpe ratio, Sortino ratio, and maximum drawdown can provide a clearer picture of the algorithm's effectiveness. Additionally, consider whether the performance is sustainable or driven by favorable market conditions.

8. Compliance and Ethics:

   • Using your mom's brokerage account to bypass compliance is a gray area. While it may seem harmless, it could raise ethical and legal concerns. WSO threads often stress the importance of maintaining integrity, especially in finance.

9. Future Improvements:

   • As highlighted in WSO discussions, continuous improvement is key. Regularly review the algorithm's performance, update its parameters, and incorporate new insights. Also, consider diversifying into other sectors or strategies once you're confident in its robustness.

In summary, your approach demonstrates a strong understanding of trading principles and algorithmic design. Just ensure you remain vigilant about risk management, compliance, and continuous improvement to sustain and scale your success.

Sources: Looking for seed money but no idea on the how/what/who, So I heard You Want to Start Trading?, First Steps into Trading, Fixed Income Sales and Trading 101, So I heard You Want to Start Trading?