Performance analysis of predictive (alpha) stock factors

All notes and materials for the CS229: Machine Learning course by Stanford University

Providing the solutions for high-frequency trading (HFT) strategies using data science approaches (Machine Learning) on Full Orderbook Tick Data.

专注于分享Python在金融领域的应用，欢迎关注微信公众号: Python金融量化 （id：tkfy920）

GARCH and Multivariate LSTM forecasting models for Bitcoin realized volatility with potential applications in crypto options trading, hedging, portfolio management, and risk management

A repository with self studied material and answers.

My notes for Stanford's CS229 course

Cryptocurrency Analysis

Python implementation of popular machine learning algorithm

Contains all code from paper: "Data-Driven Estimation in Equilibrium: An Inverse Variational Inequality Approach"

Minimax Optimization, Monotone Variational Inequalities

The Stanford's Machine Learning Course gave me a solid mathematical foundation for Machine Learning! Here are my problem set solutions for the course.

Calibration and Simulation Engine for Local Volatility Models