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A quantitative study of optimal asset allocation in a mean-CVaR & mean-variance framework
Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
2014 (English)Independent thesis Advanced level (professional degree), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

Optimal portfolio selection has been an area of great focus ever since the inception of modern portfolio theory as proposed by Harry Markowitz. This project has applied Markowitz modern portfolio theory to an invest- ment universe created from the output of an economic scenario genera- tor. This project is a collaboration between the author and the Swedish reinsurer Sirius International. The investment universe stems from Sir- ius International’s own modeling of assets. In this universe, a frame- work for extracting optimal portfolios is developed using the risk mea- sures Conditional-Value-at-Risk (CVaR) and the variance. The project analyses how a set of efficient portfolios perform in terms of risk versus reward, creating both a mean-CVaR and a mean-variance framwork. The project also analyses the cost of constraints enforced in the optimization of efficient portfolios.

Its main findings conclude that the mean-CVaR framework is prefer- able for an insurance company for several reasons. The mean-CVaR frame- work is more reliable than a mean-variance framework because it relies on the modeling of the tails of the loss distribution, whereas the mean- variance optimization will only capture the variance of a loss distribution. The mean-variance framework will as such only reflect the risks in their entirety for an underlying normal distribution. Furthermore, the mean- CVaR framework offers more stability, making it favorable for a dynamic investor who may want to adjust their portfolio holdings according to shifting market conditions. The report also concludes that the additional constraints enforced in the optimization can be quantified in terms of a limited return tradeoff. 

Place, publisher, year, edition, pages
2014. , 45 p.
National Category
Mathematics
Identifiers
URN: urn:nbn:se:umu:diva-90611OAI: oai:DiVA.org:umu-90611DiVA: diva2:728924
External cooperation
Sirius International Försäkrings AB
Educational program
Master of Science in Engineering and Management
Supervisors
Examiners
Available from: 2014-10-15 Created: 2014-06-25 Last updated: 2014-10-15Bibliographically approved

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A Quantitative Study of Optimal Asset Allocation in a Mean-CVaR & Mean-Variance Framework(3192 kB)1025 downloads
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CiteExportLink to record
Permanent link

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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
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  • Other locale
More languages
Output format
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