New Entropy Restrictions and the Quest for Better-Specified Asset-Pricing Models

2018 ◽  
Vol 54 (6) ◽  
pp. 2517-2541 ◽  
Author(s):  
Gurdip Bakshi ◽  
Fousseni Chabi-Yo

This article proposes the entropy of m2 (m is the stochastic discount factor) as a metric to evaluate asset-pricing models. We develop a bound on the entropy of m2 when m correctly prices a finite number of returns and consider models that pass the lower bound on m, yet fail the lower bound on m2. Interpreting our results, we elaborate on the distinction between the entropy of m2 versus the entropy of m. We further show that the entropy of m2 represents an upper bound on the expected excess (log) return of the security with the payoff of m.

2012 ◽  
Vol 10 (4) ◽  
pp. 425
Author(s):  
Carlos Enrique Carrasco-Gutierrez ◽  
Wagner Piazza Gaglianone

In this paper a methodology to compare the performance of different stochastic discount factor (SDF) models is suggested. The starting point is the estimation of several factor models in which the choice of the fundamental factors comes from different procedures. Then, a Monte Carlo simulation is designed in order to simulate a set of gross returns with the objective of mimicking the temporal dependency and the observed covariance across gross returns. Finally, the artificial returns are used to investigate the performance of the competing asset pricing models through the Hansen and Jagannathan (1997) distance and some goodness-of-fit statistics of the pricing error. An empirical application is provided for the U.S. stock market.


Author(s):  
Carlo A. Favero ◽  
Fulvio Ortu ◽  
Andrea Tamoni ◽  
Haoxi Yang

2013 ◽  
Author(s):  
Vladislav Vacek ◽  
Robert Gottfried Kuklik

Sign in / Sign up

Export Citation Format

Share Document