Experimental scenario analysis for real-life events forecasting with Codex or Claude

A quantitative finance and market forecasting project that analyzes historical financial data using statistical and machine learning techniques to identify trends, generate predictive insights, and simulate data-driven trading and investment decisions. It involves POSITIONAL TRADING.

This repository contains two distinct approaches for forecasting market returns. The challenge involves predicting an intraday-varying target variable `y` (hypothesized to represent log returns) across multiple symbols using time-series data with 26 features.