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Prospect Theory in the Automated Advisory Process
KTH, School of Industrial Engineering and Management (ITM), Industrial Economics and Management (Dept.), Economics.
KTH, School of Industrial Engineering and Management (ITM), Industrial Economics and Management (Dept.), Economics.
2016 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesisAlternative title
Prospektteori i en automatiseradrådgivningsprocess (Swedish)
Abstract [en]

With robo-advisors and regulation eventually changing the market conditions of thefinancial advisory industry, traditional advisors will have to adapt to a new world of asset management. Thus, it will be of interest to traditional advisors to further explore the topic of how to automatically evaluate soft aspects such as client preferences and behavior, and transform it into portfolio allocations while retaining stringency and high quality in the process. In this thesis, we show how client preferences and behavioral aspects can be translated into quantitative parameters, suitable for an asset allocation model based on prospect theory. A risk profiler, a type of questionnaire, is found to be an appropriate tool to use in this process. Further, we show that the impact of the parameters on the resulting portfolio allocations is consistent with prospect theory and the preferences of the investor. Finally, we conclude that the optimized portfolio allocation generated by the model suit the investor's preferences.

Abstract [sv]

Allteftersom robotrådgivning och regleringar förändrar marknadsvillkoren för finansiellrådgivning kommer traditionella aktörer behöva anpassa sig till helt nya förutsättningar. Därmed är det av intresse för traditionella rådgivare att ytterligare undersöka hur man automatiskt kan utvärdera mjuka faktorer, såsom kunders preferenser och beteende, och omvandla dem till portföljallokeringar samtidigt som man bibehåller stringens och hög kvalitet i processen. I denna avhandling visar vi hur kundpreferenser och beteendemässiga aspekter kan översättas till kvantitativa parametrar för en allokeringsmodell baserad på prospektteori. En riskprofilerare, en typ av frågeformulär, visar sig vara ett bra verktyg att använda i processen. Vidare visas att parametrarnas effekt på de resulterande portföljerna är förenliga med prospektteori och investerarens preferenser. Slutligen drar vi slutsatsen att den optimerade allokeringen passar investerarens preferenser.

Place, publisher, year, edition, pages
2016. , p. 58
Keywords [en]
prospect theory, portfolio allocation, robo-advising, risk profiling, investor
Keywords [sv]
prospektteori, portföljallokering, robotrådgivning, riskprofilering, investerarpreferenser
National Category
Economics and Business
Identifiers
URN: urn:nbn:se:kth:diva-199087OAI: oai:DiVA.org:kth-199087DiVA, id: diva2:1060326
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Available from: 2016-12-28 Created: 2016-12-28 Last updated: 2016-12-28Bibliographically approved

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CiteExportLink to record
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Citation style
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