Volatility Ambiguity, Portfolio Decisions, and Equilibrium Asset Pricing

This paper develops a new approach to volatility ambiguity and studies its implications for equilibrium consumption, portfolio choice, and asset prices. Our approach does not require equivalence between priors. The measure of ambiguity is based on the statistical confidence in the reference model that can be assessed with sample statistics. The approach is analytically tractable and amenable to empirical/calibration analysis. A stochastic discount pricing formula is given. At sensible levels of volatility ambiguity, the empirical regularity of equity premium and consumption growth in U.S. data can be the equilibrium outcome of our model featuring a relative risk aversion (RRA) coefficient within a reasonable range. This paper was accepted by Will Cong, finance. Funding: H. Wang received financial support from the Tsinghua University Initiative Scientific Research Program [2023THZWJC20]. L. Zhang received financial support from the Tsinghua University Initiative Scientific Research Program [2021THZWJC28] and The National Natural Science Foundation of China [Grant 72473079]. Supplemental Material: The data files are available at https://doi.org/10.1287/mnsc.2022.02902 .

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Publication Details

Journal
Management Science
Published
2024-09-26
DOI
https://doi.org/10.1287/mnsc.2022.02902
Citations
9
Primary Topic
Stochastic processes and financial applications
Type
article
Field-Weighted Citation Impact
4.85
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article

Volatility Ambiguity, Portfolio Decisions, and Equilibrium Asset Pricing

Hao Wang, L. M. Zhang, Wang Tan, Yu Liu
9 citations
Management Science
Stochastic processes and financial applications
4.85
article

Volatility Ambiguity, Portfolio Decisions, and Equilibrium Asset Pricing

Hao Wang, L. M. Zhang, Wang Tan, Yu Liu
article en
9 citations

Abstract

This paper develops a new approach to volatility ambiguity and studies its implications for equilibrium consumption, portfolio choice, and asset prices. Our approach does not require equivalence between priors. The measure of ambiguity is based on the statistical confidence in the reference model that can be assessed with sample statistics. The approach is analytically tractable and amenable to empirical/calibration analysis. A stochastic discount pricing formula is given. At sensible levels of volatility ambiguity, the empirical regularity of equity premium and consumption growth in U.S. data can be the equilibrium outcome of our model featuring a relative risk aversion (RRA) coefficient within a reasonable range. This paper was accepted by Will Cong, finance. Funding: H. Wang received financial support from the Tsinghua University Initiative Scientific Research Program [2023THZWJC20]. L. Zhang received financial support from the Tsinghua University Initiative Scientific Research Program [2021THZWJC28] and The National Natural Science Foundation of China [Grant 72473079]. Supplemental Material: The data files are available at https://doi.org/10.1287/mnsc.2022.02902 .

Management ScienceVol. 71(6)
Jinan University (CN), Shanghai Jiao Tong University (CN), Guangdong University Of Finances and Economics (CN), Shanghai Advanced Research Institute (CN), Guangdong University of Finance (CN), Shandong University of Finance and Economics (CN), Tsinghua University (CN)
Partnerships for the goals
Openalex Percentile: Top 4%
Stochastic processes and financial applications
4.85
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