Maximum Entropy Analysis of Consumption-based Capital Asset Pricing Model and Volatility

Tae Hwy Lee, Mao Millie Yi () and Aman Ullah
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Mao Millie Yi: Department of Mathematics, Physics and Statistics, Azusa Pacific University, Azusa, CA, 91702, USA

Journal of Econometric Methods, 2021, vol. 10, issue 1, 1-19

Abstract: Based on the maximum entropy (ME) method, we introduce an information theoretic approach to estimating conditional moment functions with incorporating a theoretical constraint implied from the consumption-based capital asset pricing model (CCAPM). Using the ME conditional mean/variance functions obtained from the ME density, we analyze the relationship between asset returns and consumption growth under the theoretical constraint of the CCAPM. We evaluate the predictability of asset return using consumption growth through in-sample estimation and out-of-sample prediction in the ME mean regression function. We also examine the ME variance regression function for the asset return volatility as a function of the consumption growth. Our findings suggest that incorporating the CCAPM constraint can capture the nonlinear predictability of asset returns in mean especially in tails, and that the consumption growth has an effect on reducing stock return volatility, indicating the counter-cyclical variation of stock market volatility.

Keywords: information theory; stock return and consumption growth; CCAPM theoretical constraint; ME mean regression function; ME variance regression function (search for similar items in EconPapers)
JEL-codes: C1 C5 G1 (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (1)

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DOI: 10.1515/jem-2019-0022

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