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This library provides high-performance components leveraging the hardware acceleration support and automatic differentiation of TensorFlow. The library will provide TensorFlow support for foundational mathematical methods, mid-level methods, and specific pricing models. The coverage is being rapidly expanded over the next few months. Foundational methods. Core mathematical methods - optimisation, interpolation, root finders, linear algebra, random and quasi-random number generation, etc.
Alphalens is a Python Library for performance analysis of predictive (alpha) stock factors. Alphalens works great with the Zipline open source backtesting library, and Pyfolio which provides performance and risk analysis of financial portfolios.Check out the example notebooks for more on how to read and use the factor tear sheet.
This is a free open source project for software tools in financial economics. We develop code for research notebooks which are executable scripts capable of statistical computations, as well as, collection of raw data in real-time. This serves to verify theoretical ideas and practical methods interactively. Economic and financial data, both historical and the most current.
Hi! You found the MLiFC GitHub repository. What is MLiFC you ask? MLiFC is short for machine learning in financial context, a new textbook that aims to teach business, economics and social science students practical machine learning and its applications in business and finance. It is written for the MLiFC bootcamp, taught at turing society rotterdam, also known as 'Bletchley'. The content here is mostly developed by Jannes Klaas with the support of a community of technical and non-technical people. You are welcome to join us.