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ffn is a library that contains many useful functions for those who work in quantitative finance. It stands on the shoulders of giants (Pandas, Numpy, Scipy, etc.) and provides a vast array of utilities, from performance measurement and evaluation to graphing and common data transformations.
If the problem persists, check the GitHub status page or contact support . pmorissette has 13 repositories available. Follow their code on GitHub.
- Montreal, QC, Canada
bt is a flexible backtesting framework for Python used to test quantitative trading strategies. Backtesting is the process of testing a strategy over a given data set. This framework allows you to easily create strategies that mix and match different Algos.
In this post I will be reviewing and running through examples of using the brilliant python module, “ffn – Financial Functions for Python“, which has been created by Philippe Morissette and released on the MIT license.
Philippe Morissette est ingénieur minier, diplômé du programme de baccalauréat coopératif en génie des mines et de la minéralurgie de l’Université Laval. Il a fait un doctorat au Lassonde Institute of Mining, à l’Université de Toronto.
Philippe Morissette. Faculty of Science and Engineering. Department of Mining, Metallurgical and Materials Engineering.
