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A Multi-Factor Stock Market Model with Regime-Switches, Student's T Margins, and Copula Dependencies
Linköping University, Department of Management and Engineering, Production Economics.
Linköping University, Department of Management and Engineering, Production Economics.
2017 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

Investors constantly seek information that provides an edge over the market. One of the conventional methods is to find factors which can predict asset returns. In this study we improve the Fama and French Five-Factor model with Regime-Switches, student's t distributions and copula dependencies. We also add price momentum as a sixth factor and add a one-day lag to the factors. The Regime-Switches are obtained from a Hidden Markov Model with conditional Student's t distributions. For the return process we use factor data as input, Student's t distributed residuals, and Student's t copula dependencies. To fit the copulas, we develop a novel approach based on the Expectation-Maximisation algorithm. The results are promising as the quantiles for most of the portfolios show a good fit to the theoretical quantiles. Using a sophisticated Stochastic Programming model, we back-test the predictive power over a 26 year period out-of-sample. Furthermore we analyse the performance of different factors during different market regimes.

Place, publisher, year, edition, pages
2017. , p. 76
Keywords [en]
finance, statistics, stock market, stocks, factor, factors, probability, probability distribution, students t distrbution, students t, copula, markov chain, hidden markov model, regime switching, stochastic programming, optimisation, optimization, multi factor model, arbitrage pricing theory, return, performance, back test, expectation maximisation, expectation maximization, multiple linear regression, stochastic process, primal-dual interior point, qq-plot, qq plot, excess return, market regimes, bear market, bull market, market index, index
National Category
Probability Theory and Statistics
Identifiers
URN: urn:nbn:se:liu:diva-143715ISRN: LIU-IEI-TEK-A--17/02968--SEOAI: oai:DiVA.org:liu-143715DiVA, id: diva2:1166419
External cooperation
Pontus Schröder, Carnegie Investment Bank
Subject / course
Mathematics
Presentation
2017-11-10, Linköping, 13:15 (Swedish)
Supervisors
Examiners
Available from: 2018-01-15 Created: 2017-12-14 Last updated: 2018-01-15Bibliographically approved

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CiteExportLink to record
Permanent link

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Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • 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