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Sequential Investment Decisions with Bayesian Learning

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Author Info

  • R. M. Cyert

    (Carnegie-Mellon University)

  • M. H. DeGroot

    (Carnegie-Mellon University)

  • C. A. Holt

    (University of Minnesota)

Abstract

This paper analyzes investment decisions that can be made in a modular form. It is motivated by the empirical observation that managements are particularly worried about "downside" risk. With a sequential approach this risk is minimized. An investment in a module produces information as well as profits or losses. In our model a larger investment produces more information in addition to larger profits or losses. Costs for changing the level of the investment from period to period are introduced. The optimal sequential investment policy is studied for a two-period problem. Conditions are presented under which no investment, a partial investment, or a full investment in the first period is optimal.

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File URL: http://dx.doi.org/10.1287/mnsc.24.7.712
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Bibliographic Info

Article provided by INFORMS in its journal Management Science.

Volume (Year): 24 (1978)
Issue (Month): 7 (March)
Pages: 712-718

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Handle: RePEc:inm:ormnsc:v:24:y:1978:i:7:p:712-718

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Cited by:
  1. Alexander Ludwig and Alexander Zimper, 2013. "Biased Bayesian Learning with an Application to the Risk-Free Rate Puzzle," Working Papers 390, Economic Research Southern Africa.
  2. Yue, Xiaohang & Mukhopadhyay, Samar K. & Zhu, Xiaowei, 2006. "A Bertrand model of pricing of complementary goods under information asymmetry," Journal of Business Research, Elsevier, vol. 59(10-11), pages 1182-1192, October.
  3. Alexander Zimper, 2011. "Do Bayesians learn their way out of ambiguity?," Working Papers 240, Economic Research Southern Africa.

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