A machine learning approach to stock screening with fundamental analysis

Alvarez Vecino, Pol

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Alvarez Vecino, Pol

Tutor / director / evaluatorArratia Quesada, Argimiro Alejandro

Document typeMaster thesis

Date2019-04-15

Rights accessOpen Access

Abstract

We present HPC.FASSR, a High-Performance Computation Fundamental Analysis Stock Screener and Ranker to compare many ML models and the criteria of famous Benjamin Graham for stock investing using fundamental data. FASSR is distributed so it can explore massive amounts of models in short time.

SubjectsMachine learning, High performance computing, Artificial intelligence, Aprenentatge automàtic, Càlcul intensiu (Informàtica), Intel·ligència artificial

URIhttp://hdl.handle.net/2117/133070

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Màsters Oficials - Master in Innovation and Research in Informatics - MIRI [254]

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