volatility-modeling topic

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

chibui191

A vectorized implementation of py_vollib, that supports numpy arrays and pandas Series and DataFrames.

marcdemers

Implementation with a Jupyter Notebook of the VIX index modelization provided in its CBOE white paper.

qlero

Implement pricing analytics and Monte Carlo simulations for stochastic volatility models including log-normal SV model, Heston

ArturSepp

SABR Implied volatility asymptotics

JackJacquier

Undergraduate thesis, Seoul National University Dept. of Economics — "Modeling Volatility and Risk Spillover Between the Financial Markets of US and China Using GARCH Value-at-Risk Forecasting and Gra...

MajorLift

Market Data & Derivatives Pricing Tutorial based on Jupyter notebooks

frontmark

Traditionally, volatility is modeled using parametric models. This project focuses on predicting EUR/USD volatility using more flexible, machine-learning methods.

csatzky

Machine learning for financial risk management

SiruiJi