Abstract
The current literature on behavioral portfolio optimization with reference point updating assumes that the decision maker foresees how the reference point will evolve and thus solves a time-consistent problem formulation. Empirical findings, however, suggest that decision makers often fail to foresee the updating of the reference point and consequently make time-inconsistent decisions. We analyze and compare the optimal investment strategies for a discrete time behavioral portfolio optimization problem with loss-aversion and time-varying reference points under both the time-consistent and time-inconsistent framework and for different updating rules for the reference point. There is only one framework predicting realistic investment behavior: the decision maker fails to foresee the updating of the reference point and thus faces a time-inconsistent problem, solves for a dynamically optimal strategy, and updates the reference point in a nonrecursive manner.
Original language | English |
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Pages (from-to) | 199-213 |
Journal | Operations Research |
Volume | 68 |
Issue number | 1 |
Online published | 18 Nov 2019 |
DOIs | |
Publication status | Published - Jan 2020 |
Research Keywords
- reference-dependent preferences
- reference point updating
- time-inconsistency
- stochastic control
- portfolio selection
- prediction bias
- BEHAVIORAL PORTFOLIO SELECTION
- MYOPIC LOSS AVERSION
- PROJECTION BIAS
- PROSPECT-THEORY
- DYNAMIC INCONSISTENCY
- REALIZATION UTILITY
- CHOICE
- MONEY
- ADAPTATION