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.

Ubiquant Market Prediction

Market Analysis and Prediction

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.

Microservices-based AI trading architecture integrating multi-source data scraping, Transformer-based price prediction, and an autonomous Deep Reinforcement Learning trader, deployed under centralized supervision.

Machine learning process to predict financial instrument prices up to 3 days

AI-based Trading Strategies applies deep learning models (LSTM, GRU, CNN-LSTM, Transformer) to market prediction and asset allocation. The models are evaluated with transaction cost sensitivity and cross-validation, using metrics like the Sharpe ratio.

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

Project analyzing the relationship between El Niño weather patterns and cocoa futures market volatility using NASA satellite data and financial market analysis.

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)

This is a stock market prediction app that vizualizes market data and predicts on-going trends.

Python application that integrates multiple APIs and an external AI prediction system to analyze stock trends and provide investment recommendations (buy, sell, or hold) for the upcoming period.

Multi agent-based LLM pipeline for market analysis

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.

Moth Flame Optimization with Relative Momentum Index for market prediction