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A comparative study of technicalindicator performances by stock sector: RSI, MACD, and Larry Williams %R applied to the Information Technology, Utilities, and Consumer Staples sectors.
KTH, School of Computer Science and Communication (CSC).
KTH, School of Computer Science and Communication (CSC).
2016 (English)Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
Abstract [en]

Technical indicators are used by experts in stock trading. The purpose of this report is to investigate whether or not some indicators perform better when applied to stocks of specific market sectors. The investigation was conducted by implementing one algorithm for each of three different technical indicators, Relative Strength Index, Moving Average Convergence-Divergence, and Larry Williams %R. Each algorithm considered one trading strategy. Three market sectors defined by the GICS were included in the tests, Consumer Staples, Utilities, Information Technology. For each of these sectors at least one stock from each industry were tested. Results suggest that the performance of the Relative Strength Index indicator may be related to the sector of the stock to which it is applied, while %R showed no such indication, and MACD showed only a slight performance deviation between sectors. Further and more in-depth studies are required to confirm the results and conclusions drawn in this report.

Place, publisher, year, edition, pages
2016.
National Category
Computer Science
Identifiers
URN: urn:nbn:se:kth:diva-186462OAI: oai:DiVA.org:kth-186462DiVA: diva2:927355
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Examiners
Available from: 2016-05-18 Created: 2016-05-11 Last updated: 2016-05-18Bibliographically approved

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Type fulltextMimetype application/pdf

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CiteExportLink to record
Permanent link

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Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf