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

Vanilla and exotic option pricing library to support quantitative R&D. Focus on pricing interesting/useful models and contracts (including and beyond Black-Scholes), as well as calibration of financial models to market data.

Python implementation of the Markov-Switching Multifractal model (MSM) of Calvet & Fisher (2004, 2008).

Financial analysis and demonstration of the classic algorithmic trading method, pair trading. This analysis compares the portfolio's growth with the underlying assets value and volatility over time.

A UI-friendly program calculating Black-Scholes options pricing with advanced algorithms incorporating option Greeks, IV, Heston model, etc. Reads input from users, files, databases, and real-time, external market feeds (e.g. APIs).

Bayesian Estimation of Heteroskedastic Structural Vector Autoregressions with Markov-Switching and Time-Varying Identification of the Structural Matrix

Stochastic Volatility Estimated by MCMC (Markov Chain Monte Carlo) Method

TVP-GVAR-FSVM model proposed in "Measuring international uncertainty using global vector autoregressions with drifting parameters"

This repository provides TensorFlow compatible code for some stochastic volatility models widely used in derivatives pricing.

American and European options pricer web app build with Flask and React

The workings for a very interesting exercise from the Econometrics of Financial Markets module of the MSc Quantitative Finance 2023/24 course at Bayes Business School (formerly Cass).

Investigating Wiener Processes

Financial Engineering in IRFX in C++

Config files for my GitHub profile.

Discretize VAR(1) of arbitrary size, with arbitrary covariance matrix for innovations, and optional stochastic volatility.

implement Heston model, which describe stochastic volatility.