{"repo":"LeoRigasaki/stock-market-prediction-engine","free":true,"listed":false,"github":"https://github.com/LeoRigasaki/stock-market-prediction-engine","clone":"git clone https://github.com/LeoRigasaki/stock-market-prediction-engine.git","description":"Advanced ML system for stock market prediction with real-time data and multiple algorithms","language":"Python","stars":10,"topics":["docker","ensemble-learning","fastapi","feature-engineering","hyperparameter-optimization","lightgbm","machine-learning","ml-pipeline","python","quantitative-finance"],"license":null,"category":"trading","readme_excerpt":"Stock Market Prediction Engine Research-oriented stock prediction and portfolio analytics system built with FastAPI, Streamlit, and classical/ensemble ML models. This repository is best understood as an end-to-end applied data science project, not proof of deployable trading alpha. It includes: - live inference from current market data - saved walk-forward validation artifacts - risk and portfolio analysis - a dashboard and API for inspection Reality Check The strongest improvement in this revision is methodological honesty: - performance metrics are now annualized on the correct 5-day forecast horizon - dashboard and API performance tiles now use cost-adjusted risk metrics - live inference no longer hardcodes one \"best\" model and instead ranks models from the saved evaluation summary - validation pages now surface predictive quality metrics directly instead of hiding behind Sharpe alone If you are reviewing this as a hiring or client project, the right takeaway is: - good engineering depth - real artifact pipeline - useful ML and risk tooling - still a research system with meaningful predictive limitations Verified Evaluation Snapshot The current saved evaluation reflects a 5-day forecast horizon with a 10 bps transaction-cost assumption per evaluation period. Cost-Adjusted Risk Summary Metric Value Source --- ---: --- Best net Sharpe 3.72 data/processed/day11 risk summary.csv Best gross Sharpe 4.00 data/processed/day11 risk summary.csv Best model Ensemble SimpleAverage data","default_branch":null,"files":null,"tree":[],"storefront":"/r/LeoRigasaki","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/LeoRigasaki/stock-market-prediction-engine/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}