Download this Paper Open PDF in Browser

Diagnosing Dynamic Asset Pricing Models with Generalized Entropy Bounds

26 Pages Posted: 22 Nov 2013 Last revised: 24 Nov 2013

Yan Liu

Texas A&M University, Department of Finance

Date Written: November 23, 2013

Abstract

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 (November 23, 2013). Available at SSRN: https://ssrn.com/abstract=2358148 or http://dx.doi.org/10.2139/ssrn.2358148

Yan Liu (Contact Author)

Texas A&M University, Department of Finance ( email )

Wehner 401Q, MS 4353
College Station, TX 77843-4218
United States

Paper statistics

Downloads
107
Rank
219,452
Abstract Views
539