{"repo":"rustyneuron01/BTC-ETH-SOL-Price-Predict","free":true,"listed":false,"github":"https://github.com/rustyneuron01/BTC-ETH-SOL-Price-Predict","clone":"git clone https://github.com/rustyneuron01/BTC-ETH-SOL-Price-Predict.git","description":"Ensemble price forecasting with volatility prediction (XGBoost on cached features). Multiple simulated paths per request; CRPS scoring for calibration and sharpness. Synthetic price data for options and portfolio analytics. Python, XGBoost, NumPy, Pandas, properscoring, Pyth API, PostgreSQL, Pydantic, Docker.","language":"Python","stars":19,"topics":["btc","crps","docker-compose","ethereum","financial-data","machine-learning","numpy","pandas","pytest","solana"],"license":"MIT","category":"blockchain-web3","readme_excerpt":"BTC & ETH & SOL Price Predict --- Summary This project produces ensemble forecasts of future asset prices (many simulated paths per request) to capture full probability distributions of price movement, not just point estimates. Output is synthetic price data for training AI agents and for options pricing and portfolio risk analytics. Quality is measured with the Continuous Ranked Probability Score (CRPS) over ensemble predictions against realized prices, with focus on calibration and sharpness (e.g. volatility clustering, fat tails). --- Table of contents - 1. Overview - 1.1. Introduction - 1.2. Task Presented to Workers - 1.3. Coordinator's Scoring Methodology - 1.4. Calculation of Leaderboard Score - 1.5. Overall Purpose - 2. Tech stack - 3. Usage - 4. License --- 🔭 1. Overview 1.1. Introduction This system provides high-quality synthetic price data and probabilistic forecasting. Workers generate multiple simulated price paths per request; paths must reflect real-world dynamics (volatility clustering, fat-tailed distributions). Coordinators score workers using the Continuous Ranked Probability Score (CRPS), which measures both calibration and sharpness of forecasts against actual price movements. Recent performance is weighted more heavily; emissions are allocated by relative performance. The system aims to be a key source of synthetic price data for AI agents and for options trading and portfolio management. 1.2. Task Presented to Workers Workers provide probabilistic for","default_branch":null,"files":null,"tree":[],"storefront":"/r/rustyneuron01","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/rustyneuron01/BTC-ETH-SOL-Price-Predict/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."}