Option-Implied Volatility Factors and the Cross-Section of Market Risk Premia

2011 ◽  
Author(s):  
Junye Li
2011 ◽  
Vol 47 (1) ◽  
pp. 115-135 ◽  
Author(s):  
Mariano González ◽  
Juan Nave ◽  
Gonzalo Rubio

AbstractThis paper explores the cross-sectional variation of expected returns for a large cross section of industry and size/book-to-market portfolios. We employ mixed data sampling (MIDAS) to estimate a portfolio’s conditional beta with the market and with alternative risk factors and innovations to well-known macroeconomic variables. The market risk premium is positive and significant, and the result is robust to alternative asset pricing specifications and model misspecification. However, the traditional 2-pass ordinary least squares (OLS) cross-sectional regressions produce an estimate of the market risk premium that is negative, and significantly different from 0. Using alternative procedures, we compare both beta estimators. We conclude that beta estimates under MIDAS present lower mean absolute forecasting errors and generate better out-of-sample performance of the optimized portfolios relative to OLS betas.


2018 ◽  
Vol 54 (1) ◽  
pp. 425-447 ◽  
Author(s):  
Nikolaos Karagiannis ◽  
Konstantinos Tolikas

We test for the presence of a tail risk premium in the cross-section of mutual fund returns and find that the top tail risk quintile of funds outperforms the bottom by 4.4% per annum. This premium is not simply a reward for market risk, nor do commonly used risk factors offer an adequate explanation. Our findings hold across double-sorted portfolios formed on tail risk and a number of fund characteristics. We also find that funds susceptible to tail risk tend to be small, young, have high management fees, and have managers who do not risk their own capital.


2002 ◽  
Vol 31 (3) ◽  
pp. 389-416 ◽  
Author(s):  
Andrea Beltratti ◽  
Massimo di Tria

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