QF-Lib Guide¶
QF-Lib is a Python library that provides high quality tools for quantitative finance. A large part of the project is dedicated to backtesting investment strategies. The Backtester uses an event-driven architecture and simulates events such as daily market opening or closing. It is designed to test and evaluate any custom investment strategy. For more details check the Projects Website.
Getting started¶
- Installation
How to install this library.
- Configuration
Library configuration and customization options.
Backtesting¶
- backtesting
Code of the Backtester, which uses an event-driven architecture.
- data_providers
Data providers whose purpose is to download the financial data from various vendors such as Bloomberg or Quandl.
- containers
Data structures that extend the functionality of pandas Series, pandas DataFrame and numpy DataArray containers and facilitate the computations performed on time-indexed structures of prices or price returns.
- common
Various generic tools.
Analysis¶
- analysis
Analyze strategy progress and generate files containing the analysis results
- plotting
Chart templates along with some easy-to-use decorators.
- document_utils
Templates, styles and components used to export the results and save them.
- indicators
Market indicators that can be implemented in strategies or used for the analysis.
- portfolio_construction
Components which facilitate the process of portfolio construction. The construction process involves covariance matrix optimization with one of the implemented optimizers.