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market-prediction

Here are 31 public repositories matching this topic...

Polymarket trading bot for prediction markets — browse CLOB markets, watch the order book in the terminal, run edge detection, liquidity provision and cross-market arbitrage strategies with paper trading and risk limits. Educational open-source toolkit — not financial advice. Unofficial community project, not affiliated with Polymarket.

  • Updated Sep 26, 2026
  • Python

Simple Finance Forecasting Ai. This Ai Model uses historical price data to forecast future prices. The model is trained on data downloaded from Yahoo Finance using the yfinance library, and predictions are made using a linear regression Ai model from sklearn. The model supports all the symbols supported by Yahoo Finance.

  • Updated Dec 28, 2024
  • Python

An end-to-end Python implementation of Cao et al.'s (2025) HLPPL methodology for the identification of financial (asset price) bubbles. Implements 7-parameter Log-Periodic Power Law model fitting, confidence-weighted sentiment analysis, regime-dependent 'BubbleScore' fusion, and Transformer-based forecasting with a backtesting framework.

  • Updated Oct 16, 2025
  • Jupyter Notebook

AI-driven Polymarket trading bot designed to analyze prediction market data and execute semi-automated trades using OpenAI and Claude models. The system evaluates market sentiment, probabilities, and trading signals to assist with intelligent decision making in prediction markets.

  • Updated Mar 9, 2026
  • TypeScript

AI-powered finance platform: a FastAPI + XGBoost prediction agent with purged walk-forward CV and conformal uncertainty bands, behind a full digital-wallet frontend.

  • Updated Sep 17, 2026
  • Python

This repository contains a Generative Adversarial Network (GAN) model designed to predict the closing prices in the financial market. The GAN utilizes a combination of generator and discriminator networks to generate synthetic closing price data, which can be used for forecasting and analysis purposes.

  • Updated May 25, 2023
  • Jupyter Notebook

Hull Tactical v7.1: A regime-aware "grey box" strategy for S&P 500 prediction. Combines Econophysics (Chaos/Entropy) with LightGBM and "Smart Noise" logic to challenge the EMH. (Mean Adj. Sharpe: 0.806)

  • Updated Dec 21, 2025
  • Jupyter Notebook

Analyze and forecast natural gas prices using time series data, with seasonality decomposition and signal detection for trading strategy insights.

  • Updated Mar 12, 2026
  • Jupyter Notebook

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