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A Framework For Analysing Investable Risk Premia Strategies
KTH, School of Industrial Engineering and Management (ITM), Industrial Economics and Management (Dept.).
KTH, School of Industrial Engineering and Management (ITM), Industrial Economics and Management (Dept.).
2014 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesisAlternative title
Ett ramverk för analys av investerbarariskpremiestrategier (Swedish)
Abstract [en]

The focus of this study is to map, classify and analyse how different risk premia strategies that are fully implementable, perform and are affected by different economic environments. The results are of interest for practitioners who currently invest in or are thinking about investing in risk premia strategies. The study also makes a theoretical contribution since there currently is a lack of publicised work on this subject.

A combination of the statistical methods cluster tree, spanning tree and principal component analysis are used to first categorise the investigated risk premia strategies into different clusters based on their correlation characteristics and secondly to find the strategies’ most important return drivers. Lastly, an analysis of how the clusters of strategies perform in different macroeconomic environments, here represented by inflation and growth, is conducted.

The results show that the three most important drivers for the investigated risk premia strategies are a crisis factor, an equity directional factor and an interest rate factor. These three components explained about 18 percent, 14 percent and 10 percent of the variation in the data, respectively.

The results also show that all four clusters, despite containing different types of risk premia strategies, experienced positive total returns during all macroeconomic phases sampled in this study. These results can be seen as indicative of a lower macroeconomic sensitivity among the risk premia strategies and more of an “alpha-like” behaviour. 

Abstract [sv]

Denna studie fokuserar på att kartlägga, klassificera och analysera hur riskpremie-strategier, som

är fullt implementerbara, presterar och påverkas av olika makroekonomiska miljöer. Studiens resultat är av intresse för investerare som antingen redan investerar i riskpremiestrategier eller som funderar på att investera. Studien lämnar även ett teoretiskt bidrag eftersom det i dagsläget finns få publicerade verk som behandlar detta ämne.

För att analysera strategierna har en kombination av de statistiska metoderna cluster tree, spanning  tree  och  principal  component  analysis  använts.  Detta  för  att  dels  kategorisera riskpremie-strategierna i olika kluster, baserat på deras inbördes korrelation, men också för att finna de faktorer som driver riskpremiestrategiernas avkastning. Slutligen har också en analys över hur de olika strategierna presterar under olika makroekonomiska miljöer genomförts där de makroekonomiska miljöerna representeras av inflation- och tillväxtindikatorer.

Resultaten  visar  att  de  tre  viktigaste  faktorerna  som  driver  riskpremiestrategiernas avkastning  är  en  krisfaktor,  en  aktiemarknadsfaktor och  en  räntefaktor.  Dessa  tre  faktorer förklarar ungefär 18 procent, 14 procent och 10 procent av den undersökta datans totala varians.

Resultaten  visar  också  att  alla  fyra  kluster,  trots  att  de  innehåller  olika  typer  av riskpremiestrategier,  genererade  positiv  avkastning  under  alla  makroekonmiska  faser  som studerades. Detta resultat ses som ett tecken på en lägre makroekonomisk känslighet bland riskpremiestrategier och mer av ett alfabeteende.

Place, publisher, year, edition, pages
2014. , 73 p.
Keyword [en]
Risk premia, cluster tree, spanning tree, principal component analysis, macroeconomics
Keyword [sv]
Riskpremier, cluster tree, spanning tree, principal component analysis, makroekonomi
National Category
Economics and Business
URN: urn:nbn:se:kth:diva-147547OAI: diva2:730449
Educational program
Master of Science in Engineering - Industrial Engineering and Management
Available from: 2014-07-01 Created: 2014-06-27 Last updated: 2014-07-01Bibliographically approved

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