Diagnosing Dynamic Asset Pricing Models with Generalized Entropy Bounds

26 Pages Posted: 22 Nov 2013 Last revised: 23 Jan 2018

Date Written: January 22, 2018


I examine moment characteristics and predictability assumptions of dynamic asset pricing models. I propose a new measure --- the generalized entropy --- to summarize moment information of the multi-horizon pricing kernel for a dynamic model. Both static and dynamic strategy returns impose robust restrictions on the generalize entropy, providing a way to test candidate models. Applying this test to leading representative agent models and by creating dynamic strategies that depend on model-implied predictive signals, I find that models featuring growth uncertainty is able to explain market data better.

Keywords: higher order moments, pricing kernel, entropy, conditioning information, horizon dependence, model diagnosis

JEL Classification: C14, G10, G11, G12

Suggested Citation

Liu, Yan, Diagnosing Dynamic Asset Pricing Models with Generalized Entropy Bounds (January 22, 2018). Available at SSRN: https://ssrn.com/abstract=2358148 or http://dx.doi.org/10.2139/ssrn.2358148

Yan Liu (Contact Author)

Purdue University ( email )

West Lafayette, IN 47907-1310
United States

HOME PAGE: http://yliu1.com

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