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A machine learning approach to stock screening with fundamental analysis

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hdl:2117/133070

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Alvarez Vecino, Pol
Tutor / directorArratia Quesada, Argimiro AlejandroMés informacióMés informacióMés informació
Document typeMaster thesis
Date2019-04-15
Rights accessOpen Access
All rights reserved. This work is protected by the corresponding intellectual and industrial property rights. Without prejudice to any existing legal exemptions, reproduction, distribution, public communication or transformation of this work are prohibited without permission of the copyright holder
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
DegreeMÀSTER UNIVERSITARI EN INNOVACIÓ I RECERCA EN INFORMÀTICA (Pla 2012)
URIhttp://hdl.handle.net/2117/133070
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  • Màsters oficials - Master in Innovation and Research in Informatics - MIRI [494]
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