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Searching for and evaluating outsourced chief investment officers

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  • Daehyeon Park
  • Doojin Ryu

Abstract

This study analyzes the impact of the outsourced chief investment officer (OCIO) index and OCIO search consultant on asset owners' selection of OCIOs. We adopt an agent‐based model with a reinforcement learning method by defining the OCIO search problem as a multi‐armed bandit problem. Our model highlights the significance of the information regarding potential managers provided by the OCIO index and an OCIO search consultant. Our simulation results indicate that the more managers in the market, the harder it is for asset owners to identify the optimal OCIO. If asset owners place greater emphasis on their preferences when evaluating OCIOs, those challenges might be eased. Our results suggest that OCIO search consultants and the OCIO index can support asset owners' decision‐making.

Suggested Citation

  • Daehyeon Park & Doojin Ryu, 2023. "Searching for and evaluating outsourced chief investment officers," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 44(7), pages 3923-3931, October.
    • Handle: RePEc:wly:mgtdec:v:44:y:2023:i:7:p:3923-3931
    DOI: 10.1002/mde.3917
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    References listed on IDEAS

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    1. Thomas A. Weber & Zhiqiang (Eric) Zheng, 2007. "A Model of Search Intermediaries and Paid Referrals," Information Systems Research, INFORMS, vol. 18(4), pages 414-436, December.
    2. Hazhir Rahmandad & John Sterman, 2008. "Heterogeneity and Network Structure in the Dynamics of Diffusion: Comparing Agent-Based and Differential Equation Models," Management Science, INFORMS, vol. 54(5), pages 998-1014, May.
    3. Asa B. Palley & Mirko Kremer, 2014. "Sequential Search and Learning from Rank Feedback: Theory and Experimental Evidence," Management Science, INFORMS, vol. 60(10), pages 2525-2542, October.
    4. Yinger, John, 1981. "A Search Model of Real Estate Broker Behavior," American Economic Review, American Economic Association, vol. 71(4), pages 591-605, September.
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    Cited by:

    1. Yeonchan Kang & Doojin Ryu & Robert I. Webb, 2025. "How well do machine learning models in finance work?," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 11(1), pages 1-30, December.

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