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Assessing the impact of news on oil prices: a text mining approach
2009 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

This research adds to the scarce literature that exists on the issue of commodity pricing. Within the realms of marketing commodity pricing has not attracted that much attention since pricing in marketing has mainly focused on the issue of pricing of branded products and not homogenous products such as commodities. We will add to the literature by investigating the effects of news as a sentiment creating factor on prices of oil. The emergence of text mining techniques as tools to analyze large amounts of unstructured text gives us the ability to accomplish this task without the need for human intervention. To overcome this issue we have used a text mining methodology and implemented with the use of several programming languages to see to what extent news affects oil prices. Our results show that there is a major correlation between news and oil prices and oil prices are inefficient to a large extent. Also we found out that there is a major predictive power in news and it could be used to predict oil prices with great accuracy.

Place, publisher, year, edition, pages
2009.
Keyword [en]
Social Behaviour Law, Oil price, pricing, text mining, data mining
Keyword [sv]
Samhälls-, beteendevetenskap, juridik
Identifiers
URN: urn:nbn:se:ltu:diva-58782ISRN: LTU-PB-EX--09/099--SELocal ID: f5877ac8-13aa-49dc-9f62-8c20698d4a75OAI: oai:DiVA.org:ltu-58782DiVA: diva2:1032170
Subject / course
Student thesis, at least 30 credits
Educational program
Electronic Commerce, master's level
Examiners
Note
Validerat; 20101217 (root)Available from: 2016-10-04 Created: 2016-10-04Bibliographically approved

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Type fulltextMimetype application/pdf

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CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • 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