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Investments and Asset Pricing in a World of Satisficing Agents

Author

Listed:
  • Tony Berrada

    (University of Geneva - Geneva Finance Research Institute (GFRI); Swiss Finance Institute)

  • Peter Bossaerts

    (University of Cambridge)

  • Giuseppe Ugazio

    (University of Geneva - Geneva Finance Research Institute (GFRI))

Abstract

In 1955, Herbert Simon proposed that economic agents do not optimize, but instead satisfice: they optimize up to some point of satisfaction. But Simon did not provide a formal model. Here, we develop a formal theory of a satisficing investor and consequent financial market equilibrium borrowing a technique from robust control in engineering, namely, Model Reference Based Adaptive Control (MRAC). Instead of optimizing a portfolio in terms of, say, a mean-variance trade off, the MRAC agent chooses portfolios that generate return distributions that minimize surprise with respect to a desired reference distribution. Surprisingly, the satisficing agent mostly acts “as if” optimizing, but we discover important – and realistic – deviations, such as willingness to accept risk even in the absence of a risk premium. This also implies that asset pricing may at times differ substantially from traditional theory. We motivate our modeling approach not only by pointing to benefits of robustness (robust control), but also with reference to recent developments in behavioral economics and decision neuroscience.

Suggested Citation

  • Tony Berrada & Peter Bossaerts & Giuseppe Ugazio, 2024. "Investments and Asset Pricing in a World of Satisficing Agents," Swiss Finance Institute Research Paper Series 24-05, Swiss Finance Institute.
  • Handle: RePEc:chf:rpseri:rp2405
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    File URL: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4711883
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    Cited by:

    1. Jiaoying Pei, 2024. "Reference Model Based Learning in Expectation Formation: Experimental Evidence," Papers 2404.08908, arXiv.org, revised May 2024.

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