Optimize Your Equity Holdings with AI-Driven Covered Call Strategies

Understanding the Metrics

Classification Metrics: These metrics—Precision, Recall, F1-Score, and Support—quantify the predictive accuracy and reliability of our models based on filtered results that meet a specified confidence threshold. Precision represents the ratio of true positive identifications to total positive predictions, crucial for minimizing false positives in investment strategies. Recall measures the proportion of actual positives accurately captured by the model. A low recall score is not inherently bad as potentially profitable contracts may be missed due to risk management. The F1-Score provides a balanced measure of precision and recall, useful for assessing model performance in variable market conditions. Support indicates the number of samples for each class above the confidence threshold, verifying the robustness of model predictions.

Financial Metrics: 'Average Return' and 'High Confidence Average Return' specifically refer to the incremental profit gained from the covered call strategy over mere equity holding. These metrics are pivotal for evaluating the added value brought by strategic underwriting, focusing on actual gains that exceed typical market returns.