Strategic asset allocation with distorted beliefs

San Ling Chung, Mao Wei Hung, Tzu Wen Wei*, Chung Ying Yeh*

*Corresponding author for this work

Research output: Contribution to journalJournal Article peer-review

Abstract

We propose an approximate solution for the asset allocation model in which the dynamics of the investment opportunity set are subject to regime shifts and the regime updating/predicting procedures are contaminated by psychological biases, including optimism, pessimism, conservatism, representativeness, momentum, and reversal. We employ monthly U.S. data to study the model and find that the optimistic investor earns higher returns and outperforms the rational (Bayesian) investor. We find that the outperformance of optimism results from the return predictability and that learning errors of optimism are offset by the information contained in the data sample. Psychological biases that can generate a large variability in beliefs or state uncertainty induce the investor to tilt toward cash and bonds.

Original languageEnglish
Pages (from-to)804-831
Number of pages28
JournalInternational Review of Economics and Finance
Volume89
DOIs
StatePublished - 01 2024

Bibliographical note

Publisher Copyright:
© 2023 Elsevier Inc.

Keywords

  • Distorted beliefs
  • Dynamic asset allocation
  • Investor sentiment
  • Markov-switching vector autoregressive model
  • Return predictability

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