ARCH models in Python

ARMA-GARCH

Financial research data services for academics.

Thesis project about Unsupervised anomaly detection on the streaming time-series data of porfolio risk measures and returns.

Script to fit the Heston-Nandi GARCH(1,1) model. Includes MLE of parameters, future path simulation, Monte Carlo simulation for option price and computations of pdf and cdf.

Use ARIM, GARCH and VAR(Vector Autoregression Model) models to forecast the trend and value of the USD/EUR exchange rate.

MSc Finance dissertation project at Newcastle University. This project focused on forecasting the volatility of exchange rates involving the Great British Pound using EWMA, GARCH-type and Implied Volatility models.

项目主要构建了多混频Realized GARCH-MIDAS-X模型，结合社交媒体情绪和高频数据，与 不加社交媒体情绪指标的模型相比，加入后的模型显著提升了内地低碳市场波动预测的准确性。通过稳健 性检验，证明了研究结果的可靠性。该研究丰富了市场波动模型，并为低碳投资和宏观调控提供了参考。

Explore NVIDIA's stock dynamics with this project, using a mix of traditional and deep learning models to forecast stock prices and analyze the influence of market sentiment. Integrates ARIMA, LSTM, and more to provide deep insights.

Implementation of the Ritchken-Trevor algorithm to price American put options

A professional-grade quantitative finance platform combining classic financial models and advanced AI for option pricing, risk analysis, portfolio management, and crypto derivatives. Features include Black-Scholes, Heston, Monte Carlo, GARCH, exotic options, real-time risk monitoring, AI-enhanced trading, and interactive visualizations

Research project exploring predictive models for stock market behavior using machine learning and econometric techniques.

GARCH estimation using the arch package

this repository contains a comprehensive, end-to-end pipeline for forecasting stock prices using a blend of advanced statistical methods and deep learning models. The system is designed to download historical stock data, preprocess and engineer features, and then generate forecasts using multiple models before combining them with an ensemble.

Estimate GARCH models using the BHHH algorithm

Semi-parametric hedge fund portfolio optimization – MSc Finance thesis project (HEC Lausanne)

This project showcases an advanced GARCH implementation in Python, APARCH(1,1). It determines the parameters best defining a stock's returns variance, and then uses these in a Monte Carlo simulation to simulate future returns with asymmetric volatility clustering.

Modeling S&P 500 stock data volatility using GARCH/ ARCH

Data Science project for forecasting steel and crude oil prices

Symmetric and asymmetric GARCH models to predict return volatility