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Linear Regression
Linear Regression (LLM Features)
Linear RegressionClaude & GPT-4
Predict percent change via ridge regression using market cap, momentum, and LLM-quantified qualitative features extracted from the press release and clinical trial data. The LLM acts as a feature extractor, not a direct predictor.
Overview
Strategy Type
Linear Regression
Number of Steps
1 step
Models Used
Claude & GPT-4
Output Format
Regression features (numeric features for linear model)
Prompt Details
1
LLM Feature Extraction
You are a biotech equity analyst. Extract numeric features from the press release and clinical trial data to help a linear regression predict immediate post-catalyst percent change. Use only information known at or before the catalyst date. Output strict JSON only.
Provide the following fields (JSON only):
{
"expected_direction": float in [-1,1],
"expected_magnitude": float in [0,1],
"trial_strength": float in [0,1],
"safety_risk": float in [0,1],
"priced_in": float in [0,1],
"surprise": float in [0,1],
"data_quality_confidence": float in [0,1]
}
CATALYST INFO:
- Ticker: {ticker}
- Company: {company}
- Drug: {drug}
- Phase: {phase}
- Indication: {indication}
- Event Type: {cat_type}
CLINICAL TRIAL (JSON):
{clinical_trial}
PRESS RELEASE:
{pr_text}
Expected Output Format
This prompt expects a JSON response. See the user prompt template for the exact structure.
Template Variables Reference
These variables are dynamically replaced with actual values when the strategy is executed:
{
"expected_direction": float in [-1,1],
"expected_magnitude": float in [0,1],
"trial_strength": float in [0,1],
"safety_risk": float in [0,1],
"priced_in": float in [0,1],
"surprise": float in [0,1],
"data_quality_confidence": float in [0,1]
}Custom variable{cat_type}Catalyst event type (e.g., FDA approval, trial results){clinical_trial}Clinical trial data in JSON format{company}Company name{drug}Drug or therapy name{indication}Medical indication/disease being treated{phase}Clinical trial phase (1, 2, 3, etc.){pr_text}Full press release text{ticker}Company stock ticker symbol