Tutorials about Quantitative Finance in Python and QuantLib: Pricing, xVAs, Hedging, Portfolio Optimisation, Machine Learning and Deep Learning

Useful functions for Black–Scholes Model in the Julia Language

Financial Library ( Economic Scenario Generator, Asset Liability Management, Pricing )

Julia Package for Financial Monte Carlo Simulations

Pricing derivatives using the explicit finite-difference method

An Excel integration of OpenGamma Strata.

PyRedukti is a Python library for Interest Rate Swaps and Fras, supports bootstrapping of Interest Rate Curves, computing NPV and sensitivities using automatic/algorithmic differentiation. It wraps the OpenRedukti library.

OpenRedukti is a C++ library for Interest Rate Swaps and Fras, supports bootstrapping of Interest Rate Curves, computing NPV and sensitivities using automatic/algorithmic differentiation. It provides a scripting environment in Python and Ravi (a Lua dialect).

Demonstrates how to price derivatives in a Heston framework, using successive approximations of the invariant distribution of a Markov ergodic diffusion with decreasing time discretization steps. The framework is that of G. Pagès & F. Panloup.

A dynamic strategy that replicates the payoff of a derivative described as a stochastic process

Some applications in Financial Mathematics.

functions and scripts for the course Computational Finance a.c. 2016/2017

Auxiliary material course Quantitative Finance (Tilburg University)

Black Scholes Option Pricing calculator with Greeks and implied volatility computations. Geometric Brownian Motion simulator with payoff value diagram and volatility smile plots. Java GUI.

Matlab code and tools for Quant Research, Data Manipulation and Robust Decision Making

Monte Carlo Pricing with extendable PayOff model

Implementation of the Carr-Madan formula for fast derivative pricing of European options.

Dockerized development environment with QuantLib C++ library based on Alpine Linux

Homepage of Boris Saulnier