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Stock forecasting using ensemble neural betworks
KTH, School of Electrical Engineering and Computer Science (EECS).
KTH, School of Electrical Engineering and Computer Science (EECS).
2018 (English)Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesisAlternative title
Aktieprediktion med kombinerade neurala nätverk (Swedish)
Abstract [en]

This paper explores the viability of creating an artificial neural network for stock forecasting using an ensemble method, where each network is differentiated with a different set of input parameters. The inputs were chosen based on previous research and by using a stepwise addition parameter search method. The problem was approached as both a regression and a classification problem, where we evaluated the networks performance for the purpose of stock forecasting using relevant measurements. For the regression part, the result was negative: the neural network was not able to beat a naive prediction strategy. However, for classification, a modest but significant positive result was achieved.

Abstract [sv]

Den här rapporten utforskar förmågorna hos neurala nätverk för syftet av att förutspå aktiekurser genom att använda kompositionsmetoder, där nätverken utskiljs genom deras inmatningsparametrar. Dessa parametrar valdes baserat på tidigare forskning och med valda genom en stegvisa tillägg-metod. Problemet behandlades som både ett regressions och ett klassifikationsproblem, och nätverkets prestanda utvärderades där vi evaluerade nätverkets prestanda med relevanta mått. Gällande regressionsmetoden så var vårt resultat negativt, då nätverket inte kunde prestera bättre än naiva strategier. För klassifieringsprediktion av kursens riktning erhölls dock ett blygsamt men signifikant positivt resultat.

Place, publisher, year, edition, pages
2018.
Series
TRITA-EECS-EX ; 2018:210
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:kth:diva-229798OAI: oai:DiVA.org:kth-229798DiVA, id: diva2:1214480
Subject / course
Computer Science
Supervisors
Examiners
Available from: 2018-07-10 Created: 2018-06-06 Last updated: 2018-07-10Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
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Output format
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