Real time stock and option data.
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Updated
Jul 6, 2024 - Python
Real time stock and option data.
A Python library for evaluating option trading strategies.
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.
High-frequency statistical arbitrage
Financial Derivatives Calculator with 171+ Models (Options Calculator)
Quant Option Pricing - Exotic/Vanilla: Barrier, Asian, European, American, Parisian, Lookback, Cliquet, Variance Swap, Swing, Forward Starting, Step, Fader
OptionStratLib is a comprehensive Rust library for options trading and strategy development across multiple asset classes.
Python Financial ENGineering (PyFENG package in PyPI.org)
Option Calculator using Black-Scholes model and Binomial model
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.
Vanilla option pricing and visualisation using Black-Scholes model in pure Python
European/American/Asian option pricing module. BSM/Monte Carlo/Binomial
A software to shortlist and find the best options spread available for a given stock and help it visualise using payoff graphs.
Option pricing with various models (Black-Scholes, Heston, Merton jump diffusion, etc) and methods (Monte Carlo, finite difference, Fourier).
Implementations of Leading Algorithms in Quantitative Finance
I have been deeply interested in algorithmic trading and systematic trading algorithms. This Repository contains the code of what I have learnt on the way. It starts form some basic simple statistics and will lead up to complex machine learning algorithms.
Useful functions for Black–Scholes Model in the Julia Language
A collection of educational notebooks covering key mathematical concepts and their applications in quantitative finance
Predict stock market pricing over 180 minutes using Black-Scholes stochastic modeling and parallel Monte-Carlo simulations.
Functions, examples and data from the first and the second edition of "Numerical Methods and Optimization in Finance" by M. Gilli, D. Maringer and E. Schumann (2019, ISBN:978-0128150658). This repository mirrors https://gitlab.com/NMOF/NMOF .
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