LiU Electronic Press
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Author:
Åslin, Fredrik (Linköping University, Department of Computer and Information Science)
Title:
Evaluation of Hierarchical Temporal Memory in algorithmic trading
Department:
Linköping University, Department of Computer and Information Science
Publication type:
Student thesis
Language:
English
Level:
Independent thesis Advanced level (professional degree), 10 credits / 15 HE credits
Undergraduate subject:
Computer science (10-credit final thesis, C level)
Uppsok:
Technology
Pages:
32
Year of publ.:
2010
URI:
urn:nbn:se:liu:diva-54235
Permanent link:
http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-54235
ISRN:
LIU-IDA/LITH-EX-G--10/005--SE
Subject category:
Computer Science
SVEP category:
Computer science
Keywords(en) :
Hierarchical Temporal Memory, Algorithmic Trading
Abstract(en) :

This thesis looks into how one could use Hierarchal Temporal Memory (HTM) networks to generate models that could be used as trading algorithms. The thesis begins with a brief introduction to algorithmic trading and commonly used concepts when developing trading algorithms. The thesis then proceeds to explain what an HTM is and how it works. To explore whether an HTM could be used to generate models that could be used as trading algorithms, the thesis conducts a series of experiments. The goal of the experiments is to iteratively optimize the settings for an HTM and try to generate a model that when used as a trading algorithm would have more profitable trades than losing trades. The setup of the experiments is to train an HTM to predict if it is a good time to buy some shares in a security and hold them for a fixed time before selling them again. A fair amount of the models generated during the experiments was profitable on data the model have never seen before, therefore the author concludes that it is possible to train an HTM so it can be used as a profitable trading algorithm.

Supervisor:
Heintz, Fredrik, Phd (Linköping University, Department of Computer and Information Science, KPLAB - Knowledge Processing Lab)
Examiner:
Dalenius, Peter, univ.adj. (Linköping University, Department of Computer and Information Science, KPLAB - Knowledge Processing Lab)
Available from:
2010-03-04
Created:
2010-03-04
Last updated:
2010-03-30
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