Abstract
The prospect theory model developed by Daniel Kahnemann and Amos Tversky in 1979 is now widely recognized as providing more empirically valid explanations of decision-making under uncertainty than the classical von Neumann-Morgenstern paradigm of expected utility maximization. However, despite compelling potential use cases, industry applications of prospect theory remain scarce. Following an outline of the shortcomings of classical expected utility theory and some key tenets of prospect theory, we discuss how prospect theory can be used in practice to obtain meaningful estimates of investor risk preferences. We then conclude with a case study of the digital investment management firm LIQID and its use of prospect theory as a decision support tool for its clients.
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Lisson, C. (2019). Using Prospect Theory to Determine Investor Risk Aversion. In: Liermann, V., Stegmann, C. (eds) The Impact of Digital Transformation and FinTech on the Finance Professional. Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-030-23719-6_6
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DOI: https://doi.org/10.1007/978-3-030-23719-6_6
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