Equilibrium Information Acquisition, Prediction Abilities and Asset Prices

Wen Chung Guo; Sy Ming Guu; Ting Yun Chang

doi:10.1007/s10614-010-9239-6

Equilibrium Information Acquisition, Prediction Abilities and Asset Prices

Wen Chung Guo^*, Sy Ming Guu, Ting Yun Chang

^*Corresponding author for this work

Research output: Contribution to journal › Journal Article › peer-review

Abstract

The purpose of this study is to explore a model in which asset prices are endogenously determined by information acquisition when investors have different prediction abilities. The authors discuss how equilibrium price and investor's demand for information are affected by investors' risk attitudes and prediction abilities. The results demonstrate the influence of information cost, the volatility of risky asset value, investors' risk aversion, and prediction abilities on the Nash equilibrium of information acquisition.

Original language	English
Pages (from-to)	89-111
Number of pages	23
Journal	Computational Economics
Volume	37
Issue number	1
DOIs	https://doi.org/10.1007/s10614-010-9239-6
State	Published - 01 2011
Externally published	Yes

Keywords

Asset prices
Different prediction abilities
Information acquisition
Nash equilibrium

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10.1007/s10614-010-9239-6

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abstract = "The purpose of this study is to explore a model in which asset prices are endogenously determined by information acquisition when investors have different prediction abilities. The authors discuss how equilibrium price and investor's demand for information are affected by investors' risk attitudes and prediction abilities. The results demonstrate the influence of information cost, the volatility of risky asset value, investors' risk aversion, and prediction abilities on the Nash equilibrium of information acquisition.",

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author = "Guo, {Wen Chung} and Guu, {Sy Ming} and Chang, {Ting Yun}",

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KW - Asset prices

KW - Different prediction abilities

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KW - Nash equilibrium

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Equilibrium Information Acquisition, Prediction Abilities and Asset Prices

Abstract

Keywords

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