There are 11 repositories under derivatives-pricing topic.
A Python Finance Library that focuses on the pricing and risk-management of Financial Derivatives, including fixed-income, equity, FX and credit derivatives.
Quantitative analysis, strategies and backtests
Robust and flexible Python implementation of the willow tree lattice for derivatives pricing.
The Greatest Collection of anything related to finance and crypto
High-Performance PyTorch Library for Derivatives Pricing
Deep Hedging Demo - An Example of Using Machine Learning for Derivative Pricing.
Vanilla option pricing and visualisation using Black-Scholes model in pure Python
A fixed income library for pricing bonds and bond futures, and derivatives such as IRS, cross-currency and FX swaps. Contains tools for full Curveset construction with market standard optimisers and automatic differention (AD) and risk sensitivity calculations including delta and cross-gamma.
Options and Option Strategies analytics for educational purpose using the Black-Scholes Model
Quantum Machine Learning Library for Quant Finance
Trade stocks and ETFs with free brokerage Robinhood and Perl
A Python Script To Fetch The Government Securities T-Bills Interest Rates From RBI Website.
Pricing and Analysis of Financial Derivative by Credit Suisse using Monte Carlo, Geometric Brownian Motion, Heston Model, CIR model, estimating greeks such as delta, gamma etc, Local volatility model incorporated with variance reduction.(For MH4518 Project)
modeling FICC market with QuantLib
Tool to visualize changes in the Black–Scholes model with respect to other variables. 2D or 3D data output. Can also be used to get current Greeks for a given option. European style options.
Derivatives pricing in modern C++.
An Excel integration of OpenGamma Strata.
Introduction to options pricing theory and advanced numerical methods for pricing both vanilla and exotic options.
This repository contains pricing methods for equity European and American options. Monte Carlo and tree methods have been implemented for Black Scholes extensions (standard, with discrete dividend, and with single and double Normal jumps for corporate actions). This repository also contains an implementation of a Differential Evolution algorithm to back-solve model parameters given market data (read from JSON).
RSCAM Group 1 Project (Multilevel Monte Carlo for SDEs)
Black-Scholes Pricing Model: An intuitive and sophisticated tool for accurately calculating European option prices. Leverage the mathematical elegance of the Black-Scholes formula to explore how varying market conditions impact option pricing with real-time interactive visualizations.
Contains financial studies work, including capital markets, corporate finance and other topics.
Derivatives Pricing
Quant. Research project - Cutting-Edge project (In collaboration with Milliman & University of Paris-Saclay)
Excel/Python application of stochastic methods for financial analysis
"Structured Products in Python" project from Paris-Dauphine University lecture. This project is aimed to create a pricing engine for derivatives and structured products
An interactive app on the Black Scholes Option Pricing Model, Option Greeks.
The binomial tree model is a commonly used approach for pricing derivatives, such as options. The basic idea behind the model is to create a tree of possible stock prices over time, based on a set of input parameters
Generation of realistic OHLC financial data
The main focus of this repository is to analysis the fair price and the risk of the Auto-callable Reverse Convertible issued by Credit Suisse AG on 24/10/2017
Repository of the 'Stochastic Volatility Models' Student Lab
This repository provides TensorFlow compatible code for some stochastic volatility models widely used in derivatives pricing.