A nimble options backtesting library for Python
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Updated
Jul 6, 2024 - Python
A nimble options backtesting library for Python
Quantitative Finance tools
A Python library for mathematical finance
Option pricing based on Black-Scholes processes, Monte-Carlo simulations with Geometric Brownian Motion, historical volatility, implied volatility, Greeks hedging
Python Financial ENGineering (PyFENG package in PyPI.org)
Vanilla option pricing and visualisation using Black-Scholes model in pure Python
Python implementation of pricing analytics and Monte Carlo simulations for stochastic volatility models including log-normal SV model, Heston
The Python Library For QtsApp which displays the option chain in near real-time. This program retrieves this data from the QtsApp site and then generates useful analysis of the Option Chain for the specified Index or Stock. It also continuously refreshes the Option Chain along with Implied Volatatlity (IV), Open Interest (OI), Delta, Theta, Vega…
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Simple python/streamlit web app for European option pricing using Black-Scholes model, Monte Carlo simulation and Binomial model. Spot prices for the underlying are fetched from Yahoo Finance API.
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.
FFT-based Option Pricing Methods in Python
A library for black-scholes euro options pricing, algorithmic delta hedging, and visualization
Python Code for Option Analysis
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Deep Learning methods to solve path-dependent PDEs / to price path-dependent derivatives like exotic options
A tool to analyze leveraged liquidity mining and find optimal option strategy for hedging.
A numerical library for High-Dimensional option Pricing problems, including Fourier transform methods, Monte Carlo methods and the Deep Galerkin method
Library for simulation and analysis of vanilla and exotic options
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