Libraries for Computational Finance

QuantLib is a free/open-source library for quantitative finance, providing classes and functions for financial modeling, trading, and risk management.

The scipy.stats module provides a collection of classes and functions for working with statistical distributions.

Statsmodels is a Python library that provides a collection of statistical models and tools for time series analysis, regression analysis, and exploratory data analysis.

The pandas.DataFrame object is a two-dimensional, size-mutable, potentially heterogeneous tabular data structure with labeled axes (rows and columns).

yfinance is a Python library that provides a simple interface to download historical and real-time financial data from Yahoo Finance.

CVXPY is a modeling language for convex optimization problems.

PyPortfolioOpt is a Python library that provides a collection of tools and algorithms for portfolio optimization.

Riskmanager is a Python library that provides a collection of tools and algorithms for risk management, including value at risk (VaR) and expected shortfall (ES) calculations.

SimPy is a Python library that provides a collection of tools and algorithms for Monte Carlo simulations.

Finta is a Python library that provides a collection of tools and algorithms for technical analysis of financial data.

Zipline is a Python library that provides a framework for backtesting trading strategies.

Alphalens is a Python library that provides a collection of tools and algorithms for alpha analysis, including factor analysis and performance attribution.

Quantopian is a Python library that provides a platform for algorithmic trading.

Pyfolio is a Python library that provides a collection of tools and algorithms for portfolio analysis, including performance evaluation and risk management.

CCXT is a Python library that provides a unified interface for interacting with cryptocurrency exchanges.