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Konsekverna av spinoffs: En kvantitativ studie om avkastning och investeringsstrategier
Södertörn University, School of Social Sciences.
Södertörn University, School of Social Sciences.
2022 (Swedish)Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
Abstract [en]

The purpose of the event study is to analyze the returns in Swedish listed companies that have carried out spinoffs between the period 2006 - 2021. This is done by measuring share price development. The method is observation. Secondary data is presented in the average total development in share price over the measurement period for all of the study's parent and subsidiary companies to see if the difference in returns is statistically significant. Then returns per quarter are examined, and if there is a significant difference between spinoffs and OMXSPI. Regression is used to measure Average Abnormal Return, AAR, in both the short and long term for parent and subsidiary companies, as well as for focused and diversified spinoffs. Theories and ideologies that the study uses are Shareholder Value Maximization (SVM), the Efficient Market Hypothesis (EMH), information asymmetry and modern portfolio theory. The survey covers 47 Swedish listed companies, distributed among 26 spinoffs. The result shows that the average total return was 219% and 319% for the parent and subsidiary companies, butt hat the difference is not statistically significant at a 5 percent level. However, there is a statistically significant difference in the average return per quarter in 4 of the companies compared to OMXSPI. Also that the spinoff also leads to a positive AAR of 1% and 3.7% for the parent and the subsidiary, respectively, when measured two and four quarters after the subsidiary's IPO, but that there is a slowdown in returns when measured long-term. The empirical conclusions are that spinoffs generally lead to greater AAR for the subsidiary, and that focused spinoffs generally generate greater positive AAR than diversified ones. There are large deviations in returns between spinoffs. Thus, active management has probably generateda greater return than investors according to passive management. For returns in addition to the benchmark, good analytical skills are required, a conclusion that is in line with recent studies in the subject. The study's theoretical conclusions are that spinoffs are to some extent associated with SVM. Considering the strong deviation in returns and the fact that the parent companies have on average performed worse than OMXSPI, the study is somewhat questioning how compatible spinoffs are with SVM. The fact that AAR has weakened over time supports that the Swedish securities market can be categorized as the semi-strong form of the efficient market hypothesis, EMH. Due to the selected measurement period and measurement points, the study has failed to test information asymmetry in order to arrive at a fair conclusion. For investors without greater analytical skills and deeper knowledge of stocks, the study provides support for modern portfolio theory. That as an investor you should diversify your portfolio to minimizerisk.

Place, publisher, year, edition, pages
2022. , p. 74
Keywords [en]
spinoffs, stocks, diversification
Keywords [sv]
avknoppningar, avkastning, aktier, diversifiering
National Category
Business Administration
Identifiers
URN: urn:nbn:se:sh:diva-50054OAI: oai:DiVA.org:sh-50054DiVA, id: diva2:1702835
Subject / course
Business Studies
Supervisors
Examiners
Available from: 2022-10-12 Created: 2022-10-11 Last updated: 2022-10-12Bibliographically approved

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Spinoffs(1243 kB)143 downloads
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CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • harvard-anglia-ruskin-university
  • apa-old-doi-prefix.csl
  • sodertorns-hogskola-harvard.csl
  • sodertorns-hogskola-oxford.csl
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
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Output format
  • html
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  • asciidoc
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