Taring all investors with the same brush? Evidence for heterogeneity in individual preferences from a maximum likelihood approach

  • Microeconomic modeling of investors behavior in financial markets and its results crucially depends on assumptions about the mathematical shape of the underlying preference functions as well as their parameterizations. With the purpose to shed some light on the question, which preferences towards risky financial outcomes prevail in stock markets, we adopted and applied a maximum likelihood approach from the field of experimental economics on a randomly selected dataset of 656 private investors of a large German discount brokerage firm. According to our analysis we find evidence that the majority of these clients follow trading pattern in accordance with Prospect Theory (Kahneman and Tversky (1979)). We also find that observable sociodemographic and personal characteristics such as gender or age don't seem to correlate with specific preference types. With respect to the overall impact of preferences on trading behavior, we find a moderate impact of preferences on trading decisions of individual investors. A classification of investors according to various utility types reveals that the strength of the impact of preferences on an investors' rading behavior is not connected to most personal characteristics, but seems to be related to round-trip length.

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Metadaten
Author:Andreas HackethalORCiDGND, Sven Thorsten Jakusch, Steffen MeyerORCiDGND
URN:urn:nbn:de:hebis:30:3-416995
URL:https://ssrn.com/abstract=2845866
Parent Title (English):SAFE working paper series ; No. 147
Series (Serial Number):SAFE working paper (147)
Publisher:SAFE
Place of publication:Frankfurt am Main
Document Type:Working Paper
Language:English
Year of Completion:2016
Year of first Publication:2016
Publishing Institution:Universitätsbibliothek Johann Christian Senckenberg
Release Date:2016/10/20
Tag:Individual Investors; Maximum Likelihood; Utility Theory
Page Number:61
HeBIS-PPN:390298409
Institutes:Wirtschaftswissenschaften / Wirtschaftswissenschaften
Wissenschaftliche Zentren und koordinierte Programme / House of Finance (HoF)
Wissenschaftliche Zentren und koordinierte Programme / Center for Financial Studies (CFS)
Wissenschaftliche Zentren und koordinierte Programme / Sustainable Architecture for Finance in Europe (SAFE)
Dewey Decimal Classification:3 Sozialwissenschaften / 33 Wirtschaft / 330 Wirtschaft
JEL-Classification:C Mathematical and Quantitative Methods / C3 Multiple or Simultaneous Equation Models / C35 Discrete Regression and Qualitative Choice Models; Discrete Regressors (Updated!)
C Mathematical and Quantitative Methods / C5 Econometric Modeling / C51 Model Construction and Estimation
C Mathematical and Quantitative Methods / C5 Econometric Modeling / C52 Model Evaluation and Selection
Sammlungen:Universitätspublikationen
Licence (German):License LogoDeutsches Urheberrecht