A behavioral model for mutual fund dynamics

dc.contributor.advisorAltı, Aydoğanen
dc.contributor.committeeMemberTitman, Sheridanen
dc.contributor.committeeMemberSialm, Clemensen
dc.contributor.committeeMemberLandvoigt, Timen
dc.contributor.committeeMemberTompaidis, Stathisen
dc.creatorKim, Donghyunen
dc.creator.orcid0000-0001-9641-8716en
dc.date.accessioned2015-11-04T20:38:45Zen
dc.date.available2015-11-04T20:38:45Zen
dc.date.issued2015-08en
dc.date.submittedAugust 2015en
dc.date.updated2015-11-04T20:38:45Zen
dc.descriptiontexten
dc.description.abstractBased on Berk and Green (2004), I develop a model that explains the following well-known stylized facts on mutual funds in a unified framework: (i) a negative aggregate return, (ii) a short-term return persistence, and (iii) a convex return-flow relationship. In the model, agents learn about managers' time-varying abilities from fund returns and non-return information signals. Under decreasing returns to scale, investors equilibrate expected fund returns through fund flows, but their expectations are biased due to overconfidence about precision of non-return signals and overextrapolation of past return trends. I employ a Simulated Method of Moments (SMM) to estimate the model parameters. The model matches most of the 15 moments, and is not rejected at the 10% level. I run a horse race between rational equilibrating forces and behavioral inefficiencies by allowing parameters for biases determined by data. As a result, both information processing biases appear to be important to generate a negative aggregate return and short-term return persistence, and to improve a model fit.en
dc.description.departmentFinanceen
dc.format.mimetypeapplication/pdfen
dc.identifierdoi:10.15781/T2D05Pen
dc.identifier.urihttp://hdl.handle.net/2152/32227en
dc.language.isoenen
dc.subjectMutual funden
dc.subjectBehavioral biasen
dc.titleA behavioral model for mutual fund dynamicsen
dc.typeThesisen
thesis.degree.departmentFinanceen
thesis.degree.disciplineFinanceen
thesis.degree.grantorThe University of Texas at Austinen
thesis.degree.levelDoctoralen
thesis.degree.nameDoctor of Philosophyen

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