Robust and flexible Python implementation of the willow tree lattice for derivatives pricing. A library for financial options pricing written in Python. Q-Fin – A Python library for mathematical finance. Complete python implementation of R package fOptions with partial implementation of fExoticOptions for pricing various options. Applications of Monte Carlo methods to financial engineering projects, in Python. Quantsbin – Tools for pricing and plotting of vanilla option prices, greeks and various other analysis around them. PME (Public Market Equivalent) calculation. High-performance TensorFlow library for quantitative finance.
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D-Tale – Visualizer for pandas dataframes and xarray datasets. Performant and effortless finance plotting for Python. QuantInvestStrats – Quantitative Investment Strategies (QIS) package implements Python analytics for visualisation of financial data, performance reporting, analysis of quantitative strategies. Xtensible Time Series: Provide for uniform handling of R’s different time-based data classes by extending zoo, maximizing native format information preservation and allowing for user level customization and extension, while simplifying cross-class interoperability. Analysis and interactive charting using market-prices and bqplot. Finviz analysis python library.
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QuantTools – Enhanced Quantitative Trading Modelling. Multi-currency portfolios. Actively maintained and developed. Transaction-oriented infrastructure for constructing trading systems and simulation. Provides portfolio support for multi-asset class. Transaction infrastructure for defining instruments, transactions, portfolios and accounts for trading systems and simulation. FactorAnalytics – The FactorAnalytics package contains fitting and analysis methods for the three main types of factor models used in conjunction with portfolio construction, optimization and risk management, namely fundamental factor models, time series factor models and statistical factor models. PerformanceAnalytics – Econometric tools for performance and risk analysis. Expected Returns – Solutions for enhancing portfolio diversification and replications of seminal papers with R, most of which are discussed in one of the best investment references of the recent decade, Expected Returns: An Investors Guide to Harvesting Market Rewards by Antti Ilmanen. Provides support for multi-asset class and multi-currency portfolios for backtesting and other financial research.
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Analysis of financial data. General Purpose Stock Extractors from Online Resources. Rapidly queries Yahoo Finance for multiple tickers. Stockex – Python wrapper for Yahoo! Finance API for Python. Get current exchange rate. Returns typed data for analysis. Python API to get Chinese stock price. API returns stock closing prices for current period of time and current stock ticker (i.e. APPL, GOOGL). FRB – Python Client for FRED® API. Real time stock. Option data. Retrieve stock quote data from Yahoo Finance. Obtains stock symbols and relating information for SP500, AMEX, NYSE, and NASDAQ.
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