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Chinese Journal of Management Science ›› 2017, Vol. 25 ›› Issue (8): 39-45.doi: 10.16381/j.cnki.issn1003-207x.2017.08.005

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Dynamic Portfolio Choice based Bayesian Learning Approach

GUO Wen-ying   

  1. School of Statistics Capital University of Economics and Business, Beijing 1000070, China
  • Received:2015-10-13 Revised:2016-11-21 Online:2017-08-20 Published:2017-10-16

Abstract: In this paper, the optimal dynamic portfolio choice is analyzed under Bayesian learning. Assuming that there are two kinds of risky assets, the returns of each asset are predictable by unobservable predictor, and risks of each asset have both systematic and own risks. The empirical results highlight that the proportion of the investor's wealth invested in every risky asset is decreasing with the degree of risk aversion over short horizon, but it is opposite when the investment horizon is long. When the degree of risk aversion is constant, the Bayesian learning makes different about the long and short-horizon investment strategy. This critical point decreases with the degree of risk aversion of investor. The correlation between risk assets and the unobservable predictor is inversely proportional to the size of the risk of asset.

Key words: Bayesian learning, HJB equation, dynamic portfolio choice

CLC Number: