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Evaluation of a Portfolio in Dow Jones Industrial Average Optimized by Mean-Variance Analysis
KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematical Statistics.
KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematical Statistics.
2020 (English)Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesisAlternative title
Utvärdering av en portfölj i Dow Jones Industrial Average optimerad genom mean-variance analysis (Swedish)
Abstract [en]

This thesis evaluates the mean-variance analysis framework by comparing the performance of an optimized portfolio consisting of stocks from the Dow Jones Industrial Average to the performance of the Dow Jones Industrial Average index itself. The results show that the optimized portfolio performs better than the corresponding index when evaluated on the period between 2015 and 2019. However, the variance of the returns are high and therefore it is difficult to determine if mean-variance analysis performs better than its corresponding index in the general case. Furthermore, it is shown that individual stocks can still influence the movement of an optimized portfolio significantly, even though the model is supposed to diversify firm-specific risk. Thus, the authors recommend modifying the model by restricting the amount that is allowed to be invested in a single stock, if one wishes to apply mean-variance analysis in reality. To be able to draw further conclusions, more practical research within the subject needs to be done.

Abstract [sv]

Denna uppsats utvärderar ramverket ”mean-variance analysis” genom att jämföra prestandan av en optimerad portfölj bestående av aktier från Dow Jones Industrial Average med prestandan av indexet Dow Jones Industrial Average självt. Resultaten visar att att den optimerade portföljen presterar bättre än motsvarande index när de utvärderas på perioden 2015 till 2019. Dock är variansen av avkastningen hög och det är därför svårt att bedöma om mean-variance analysis generellt sett presterar bättre än sitt motsvarande index. Vidare visas det att individuella aktier fortfarande kan påverka den optimerade portföljens rörelser, fastän modellen antas diversifiera företagsspecifik risk. På grund av detta rekommenderar författarna att modifiera modellen genom att begränsa mängden som kan investeras i en individuell aktie, om man önskar att tillämpa mean-variance analysis i verkligheten. För att kunna dra vidare slutsatser så krävs mer praktisk forskning inom området.

Place, publisher, year, edition, pages
2020.
Series
TRITA-SCI-GRU ; 2020:103
Keywords [en]
applied mathematics, mean-variance analysis, modern portfolio theory, Markowitz, Dow Jones Industrial Average, quadratic optimization, portfolio optimization
Keywords [sv]
tillämpad matematik, mean-variance analysis, modern portföljteori, Markowitz, Dow Jones Industrial Average, kvadratisk optimering, portföljoptimering
National Category
Probability Theory and Statistics
Identifiers
URN: urn:nbn:se:kth:diva-275662OAI: oai:DiVA.org:kth-275662DiVA, id: diva2:1450545
Subject / course
Applied Mathematics and Industrial Economics
Educational program
Master of Science in Engineering - Industrial Engineering and Management
Supervisors
Examiners
Available from: 2020-09-09 Created: 2020-07-01 Last updated: 2022-06-26Bibliographically approved

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CiteExportLink to record
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Citation style
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