This thesis aims to investigate different types of optimization methods that can be used when optimizing fund of fund portfolios. Moreover, the thesis investigates which funds that should be included and what their respective portfolio weights should be, in order to outperform the Swedish SIX Portfolio Return Index. The funds considered for the particular fund of funds in this thesis are all managed by a particular company. The optimization frameworks applied include traditional mean variance optimization, min conditional value at risk optimization, as well as optimization methods studying alpha in combination with the risk measures tracking error and maximum drawdown, respectively. All four optimization methods were applied on a ten years data period as well as on a five years data period. It was found that while the funds have different strengths and weaknesses, four of the funds were considered most appropriate for the fund of funds. Geography and sector constraints were also taken into account and it was found that, in this particular case, the healthcare sector constraint affected the allocated portfolio weights the most. / Syftet med detta masterexamensarbete är att undersöka olika typer av optimeringsmetoder som kan användas vid optimering av en fond i fond. Vidare är syftet med optimeringen att utvärdera vilka fonder som bör inkluderas och vilka deras respektive portföljvikter bör vara för att prestera bättre än det svenska SIX Portfolio Return Indexet. Optimeringsmetoderna inkluderar traditionell modern portföljteori, minimering av conditional Value at Risk och optimeringsmetoder som studerar alpha i kombination med riskmåtten tracking error respektive maximum drawdown. Alla fyra optimeringsmetoder applicerades på en tio år lång respektive fem år lång dataperiod. Det visade sig att även om fonderna har olika styrkor och svagheter kunde fyra av fonderna anses vara mest lämpliga att inkluderas i fond i fonden. Geografiska och sektoriella begränsningar beaktades och det konstaterades att sektorbegränsningen för hälsovårdssektorn hade störst påverkan på resultatet.
Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:kth-337198 |
Date | January 2023 |
Creators | Cederberg, Idun, Cui, Ida |
Publisher | KTH, Matematik (Avd.) |
Source Sets | DiVA Archive at Upsalla University |
Language | English |
Detected Language | English |
Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
Format | application/pdf |
Rights | info:eu-repo/semantics/openAccess |
Relation | TRITA-SCI-GRU ; 2023:330 |
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