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

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

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

Market Data & Derivatives Pricing Tutorial based on Jupyter notebooks

SABR Implied volatility asymptotics

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

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

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 Granger Causality."

Implementation of option pricing models using Numba that performs better. This entire project has utilized as little libraries as possible, even though certain models have their own Machine Learning Model with assessment and performance.

Collection of numerical methods for high frequency data, in Python notebooks

Python wrappers around QuantLib and Pandas to easily generate volatility surfaces

Machine learning for financial risk management

The project aims to profile stocks with similar weekly percentage returns using K-Means Clustering. The project calculates realized volatility for each stock and predicts realized volatility for each stock using classical volatility models and machine learning models and comparing their performance. This is a capstone project for CIVE 7100 Time …

IBOVESPA volatility forecasting

Measure market risk by CAViaR model

Code for the paper "Realized Semi(Co)Variation: Signs that All Volatilities are Not Created Equal"

Study on volatility transmission and protuberance among developed and developing stock markets using multivariate GARCH

In this repo you will find some tools related to pricing and risk measurement of options. You can find tools to calculate the price of an option like de Black-Scholes or Heston Model, or to get implied volatilities.

computes Volatility Spillover between Cryptocurrency (BTC/USD) and S&P 500 index