mgroncki/IPythonScripts
Tutorials about Quantitative Finance in Python and QuantLib: Pricing, xVAs, Hedging, Portfolio Optimisation, Machine Learning and Deep Learning
This project helps quantitative finance professionals understand complex financial models and pricing techniques. It takes financial data and market scenarios as input and provides insights into asset pricing, risk management, and portfolio optimization strategies. The primary users are quants, financial engineers, and risk managers looking to apply advanced analytical methods.
174 stars.
Use this if you are a quantitative finance practitioner seeking to learn and apply Python and QuantLib for tasks like pricing derivatives, managing risk, or optimizing investment portfolios.
Not ideal if you are looking for a plug-and-play production system or a general-purpose data science tool outside of quantitative finance.
Stars
174
Forks
71
Language
Jupyter Notebook
License
BSD-3-Clause
Category
Last pushed
Feb 28, 2026
Commits (30d)
0
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