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Quantitative Portfolio Construction Using Stochastic Programming
KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematical Statistics.
KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematical Statistics.
2018 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesisAlternative title
Kvantitativ portföljkonstruktion med användning av stokastisk programmering : En studie inom portföljoptimering (Swedish)
Abstract [en]

In this study within quantitative portfolio optimization, stochastic programming is investigated as an investment decision tool. This research takes the direction of scenario based Mean-Absolute Deviation and is compared with the traditional Mean-Variance model and widely used Risk Parity portfolio. Furthermore, this thesis is done in collaboration with the First Swedish National Pension Fund, AP1, and the implemented multi-asset portfolios are thus tailored to match their investment style. The models are evaluated on two different fund management levels, in order to study if the portfolio performance benefits from a more restricted feasible domain. This research concludes that stochastic programming over the investigated time period is inferior to Risk Parity, but outperforms the Mean-Variance Model. The biggest aw of the model is its poor performance during periods of market stress. However, the model showed superior results during normal market conditions.

Abstract [sv]

I denna studie inom kvantitativ portföljoptimering undersöks stokastisk programmering som ett investeringsbeslutsverktyg. Denna studie tar riktningen för scenariobaserad Mean-Absolute Deviation och jämförs med den traditionella Mean-Variance-modellen samt den utbrett använda Risk Parity-portföljen. Avhandlingen görs i samarbete med Första AP-fonden, och de implementerade portföljerna, med era tillgångsslag, är därför skräddarsydda för att matcha deras investeringsstil. Modellerna utvärderas på två olika fondhanteringsnivåer för att studera om portföljens prestanda drar nytta av en mer restrektiv optimeringsmodell. Den här undersökningen visar att stokastisk programmering under undersökta tidsperioder presterar något sämre än Risk Parity, men överträffar Mean-Variance. Modellens största brist är dess prestanda under perioder av marknadsstress. Modellen visade dock något bättre resultat under normala marknadsförhållanden.

Place, publisher, year, edition, pages
2018.
Series
TRITA-SCI-GRU ; 2018:267
Keywords [en]
Asset Allocation, Dynamic Portfolio Construction, Stochastic Programming, Scenario Generation, Multivariate GARCH, DCC-GARCH, Copula-GARCH, Transaction Costs, Mean-Absolute Deviation, Risk Parity, Mean-Variance
Keywords [sv]
Tillgångsallokering, Dynamisk Portfölj Konstruktion, Stokastisk Programmering, Scenario Generation, Multivariat GARCH, DCC-GARCH, Copula- GARCH, Transaktionskostnader, Mean-Absolute Deviation, Risk Parity, Mean-Variance
National Category
Computational Mathematics
Identifiers
URN: urn:nbn:se:kth:diva-230243OAI: oai:DiVA.org:kth-230243DiVA, id: diva2:1229555
External cooperation
AP 1
Subject / course
Financial Mathematics
Educational program
Master of Science - Applied and Computational Mathematics
Supervisors
Examiners
Available from: 2018-07-01 Created: 2018-07-01 Last updated: 2018-07-01Bibliographically approved

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CiteExportLink to record
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