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Multi-Scale Predictability for Emerging Foreign Exchange Markets
Linköping University, Department of Management and Engineering, Economics.
Linköping University, Department of Management and Engineering, Economics.
2016 (English)Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
Abstract [en]

Expanding the work done by Bekiros and Marcellino [2013] to emerging markets will give a better understanding of the prediction power of artificial neural networks with a wavelet design. The finan- cial perspective discussed will be from an investor or traders view with possible strategies and policies. Investors who seek a better un- derstanding of future volatility or a trader that wishes to improve the prediction of returns can learn from our conclusions. Continu- ously improving prediction models is a difficult but rewarding task, especially considering the effort and resources already invested in the area. The investments in emerging markets have been on a de- cline the past years but still has the possibility to bloom into a more attractive choice. 

Place, publisher, year, edition, pages
2016. , p. 51
National Category
Economics
Identifiers
URN: urn:nbn:se:liu:diva-134394ISRN: LIU-IEI-FIL-G--16/01600--SEOAI: oai:DiVA.org:liu-134394DiVA, id: diva2:1072813
Subject / course
Bachelor Thesis in Economics
Available from: 2017-02-14 Created: 2017-02-08 Last updated: 2017-02-14Bibliographically 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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