Python implementation of 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.

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).

R Finance packages not listed in the Empirical Finance Task View

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.

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"

R Time series packages not included in CRAN Task View: Time Series Analysis

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

Investigating Wiener Processes

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

A repo which deals with Computational Methods in Mathematics, mainly applied in the context of Mathematical Finance, even though it can be applied to almost any domain where you need Probability, Partial Differential Equations, Stochastic Differential Equations, Characteristic Functions, Lévy Processes, Stochastic Volatility, FFT, etc.

List of books on time series analysis, with links to code where available

Financial Engineering in IRFX in C++

Simulate from and fit a discrete-time autoregressive log stochastic volatility model

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

implement Heston model, which describe stochastic volatility.

Code for Master Thesis titled: "Dynamic Factor Model with Time-Varying Parameters: Simulation Study & Application to International Inflation Dynamics"