Popular GitHub Repositories for Implied Volatility

Differentiable SDE solvers with GPU support and efficient sensitivity analysis.

ARCH models in Python

?This repo contains detailed notes and multiple projects implemented in Python related to AI and Finance. Follow the blog here: https://purvasingh.medium.com

daily stock screening by using Mark Minervini's volatility contraction pattern detection, stage 2 template searching and news sentiment analysis by openAi api

TensorFlow implementation of the HARNet model for realized volatility forecasting.

Machine learning for financial risk management

一个模型上下文协议（MCP）服务器，它将 Volatility 3 内存取证框架与 Claude 集成在一起。

R code and Realized Volatility (RV) series set for fitting NN-based-HAR models to multinational RV series.

An attempt to predict stock market volatility, return and trading volume of tech stocks using Semantic Vectors and Google Trends, which reflects real-time popularity of search terms

这个仓库托管着一个用于Volatility 3.x版本的内存取证服务器。

Implied volatility is a key aspect when it comes to derivatives pricing. With the growing influence of machine learning in finance, I have investigated the use of LSTMs to forecast 1-day forward Implied Volatility.

A framework for predicting spikes in IV for the S&P 500 using deep learning

SECUBIAN is a French Linux distribution focused on evidence processing during Incident Response.

Asset analysis : downloading assets and correlated assets for analysis with neural nets

An algorithmic trading strategy incursion using Adaboost machine learning classifier, to create the first volatility security suitable for long term investors.

Bayesian analysis and forecasting of Bitcoin volatility. Definition of GARCH and ARCH models through MCMC sampling.

时间序列分析书籍列表，并附带代码链接（如有）

Developed a machine learning model for predicting intraday and interday stock returns on winton historical return dataset with a focus on feature engineering and volatility analysis investigating return patterns & volatility

This project analyzes stock market data for six major stocks (AAPL, AMZN, NVDA, TSLA, GOOG, SPY) using Python and Power BI. It explores trends, volatility, and correlations.

Vortex-Sentiment Adaptive Volatility (VSAV) Strategy - MET ABA Hackathon