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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