Earticle

초록

영어

"It is now widely accepted that excess returns are predictable" (Lettau and Lud- vigson, 2001). However, there also have been authors nding otherwise, claiming that most of the predictive models are \unstable or even spurious" (Welch and Goyal, 2008). This paper proposes a model of learning through which we can investigate the behav- ior of an investor under such ambiguous circumstances. The proposed model describes how observations are translated into a set of probability measures that represents the investor's view of the immediate future; and I explicitly characterize the set's evolution up to a system of dierential equations that generalizes the Kalman-Bucy lter in the presence of ambiguity. The model of learning is then applied to the portfolio choice problem of a log investor; and learning under ambiguity is seen to have a signicant eect on hedging demand|under a reasonable calibration, the optimal demand for the risky asset at zero instantaneous equity premium decreases, as the investor loses condence, by half of wealth.

목차

Abstract
 1 Introduction
 2 Overview
  2.1 The Model of Learning
  2.2 Portfolio Choice
  2.3 Related Papers
 3 The Model of Learning under Ambiguity
  3.1 Preferences: Recursive Multiple-Priors
  3.2 The Theories
  3.3 The Preferential Priors
  3.4 Discussion
 4 Portfolio Choice
  4.1 The Setup
  4.2 Optimal Consumption and Portfolio
  4.3 Markovian Characterization
  4.4 Examples
 References
 Supplementary Appendix toLearning under Ambiguous Reversion

저자

• Hongseok Choi [ Republic of Korea Air Force Academy; Cheongju, Chungbuk 360-849, Republic of Korea ]

참고문헌

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간행물

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• 간행물명

  한국재무학회 학술대회

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• 수록기간

  2006~2024

• 십진분류

  KDC 325 DDC 330