Project Description: 

QF-Lib is a Python library that provides high quality tools for quantitative finance. Among the features, there are modules for portfolio construction, time series analysis, risk monitoring and a diverse charting package. The library provides extensive functionality for financial data analysis in addition to a wide variety of tools for data processing and presentation of the results.

QF-Lib is a convenient environment for conducting your own analysis. The results are presented in a practical form including a variety of charts and statistical measures. 

An extensive part of the libraries is dedicated to backtesting investment strategies. The Backtester uses an event-driven architecture and simulates the events such as daily market opening or closing. Thanks to the architecture based on interfaces, it is easily to customise. Tested strategies may consist of different alpha models, position-sizing techniques, risk management settings and specify commission pricing or slippage models. After testing a strategy on historical data, the user can apply it to a trading environment without any modifications.

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