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Feature Description
Data Collection: Collecting historical financial news articles and their corresponding sentiment scores.
Feature Engineering: Create features representing the sentiment scores and integrate them with the existing options data features.
Model Training: Train the enhanced model on the combined dataset of options and sentiment features. Evaluate the model's performance with and without sentiment features to assess the impact. RND Estimation:
Using the enhanced model to estimate the risk-neutral density from new options data, incorporating current market sentiment. Analyze the improvement in RND estimation accuracy due to sentiment integration.
Use Case
The current RND estimation approach does not incorporate external factors like market sentiment, which can significantly impact options prices and risk-neutral densities.
Benefits
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Add ScreenShots
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Priority
High
Record