References (30)


Citations (1)



When Does Idiosyncratic Risk Really Matter?

Tony Ruan

Xiamen University

Qian Sun

Fudan University

Yexiao Xu

University of Texas at Dallas - School of Management

February 28, 2010

In contrast to the current literature, we provide new evidence supporting a positive relation between idiosyncratic risk and the expected future market return. Since a large part of the idiosyncratic risk can be diversified away easily, the conventional aggregate idiosyncratic risk measures can only be noisy proxies for the undiversified idiosyncratic risk, which may be priced according to Merton (1987). We thus propose a simple noise reduction method that includes two different noisy measures (dual-predictor) in the same predictive regression to reexamine the relation. We show that the noise effect tends to cancel out in our framework due to the highly correlated noise components of the two measures. In particular, our dual-predictor alone explains future market returns with an adjusted R^2 of 4%. Such a large predictive power is economically significant and robust to the inclusion of other popular predictors and to the choices of sample periods and additional market indices.

Number of Pages in PDF File: 52

JEL Classification: G12, G14, G17

Open PDF in Browser Download This Paper

Date posted: February 28, 2010 ; Last revised: September 21, 2010

Suggested Citation

Ruan, Tony and Sun, Qian and Xu, Yexiao, When Does Idiosyncratic Risk Really Matter? (February 28, 2010). Available at SSRN: https://ssrn.com/abstract=1561262 or http://dx.doi.org/10.2139/ssrn.1561262

Contact Information

Tony Ruan
Xiamen University ( email )
Xiamen, Fujian 361005
Qian Sun
Fudan University ( email )
No. 670, Guoshun Road
No.670 Guoshun Road
Shanghai, 200433
86 21 25011094 (Phone)
Yexiao Xu (Contact Author)
University of Texas at Dallas - School of Management ( email )
P.O. Box 830688
Richardson, TX 75083-0688
United States
972-883-6703 (Phone)
HOME PAGE: http://www.utdallas.edu/~yexiaoxu
Feedback to SSRN

Paper statistics
Abstract Views: 1,490
Downloads: 242
Download Rank: 95,219
References:  30
Citations:  1
People who downloaded this paper also downloaded:
1. Does Academic Research Destroy Stock Return Predictability?
By R. David Mclean and Jeffrey Pontiff