Loading...
Please wait, while we are loading the content...
Similar Documents
Good and Bad Variance Premia and Expected Returns
| Content Provider | Semantic Scholar |
|---|---|
| Author | Kilic, M. |
| Copyright Year | 2015 |
| Abstract | We measure “good” and “bad” variance premia that capture risk compensations for the realized variation in positive and negative market returns, respectively. The two variance premium components jointly predict excess returns over the next 1 and 2 years with statistically significant negative (positive) coefficients on the good (bad) component. The R2s reach about 10% for aggregate equity and portfolio returns and about 20% for corporate bond returns. We show that an asset pricing model that features distinct time variation in positive and negative shocks to fundamentals can explain the good and bad variance premium evidence in the data. ∗Mete Kilic (mkilic@wharton.upenn.edu) and Ivan Shaliastovich (corresponding author, ishal@wharton.upenn.edu) are at Wharton School, University of Pennsylvania, 3620 Locust Walk, Philadelphia, PA 19104, Phone: (215) 746-0005. We are grateful to Torben Andersen, Bjorn Eraker, Nicola Fusari, Jessica Wachter, Amir Yaron, and Hao Zhou and seminar participants at Emory University, Temple University, University of North Carolina at Chapel Hill, the Wharton School, and the 2015 Midwest Finance Association meetings for helpful comments. We thank The Rodney L. White Center for Financial Research for financial support. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | https://editorialexpress.com/cgi-bin/conference/download.cgi?db_name=AFA2016&paper_id=1279 |
| Alternate Webpage(s) | https://wsbfiles.bus.wisc.edu/digital/shaliastovic/intellcont_journal/ks_gb_MS_FINAL-1.pdf |
| Alternate Webpage(s) | https://repository.upenn.edu/cgi/viewcontent.cgi?article=1404&context=fnce_papers |
| Language | English |
| Access Restriction | Open |
| Subject Keyword | Aggregate data Appendix Assumed Booting Bootstrapping (statistics) Chapel Class Coefficient Common Variable Immunodeficiency Computation Disease regression Downside risk Equity crowdfunding Estimated Expanded memory Guadua velutina High-Speed Serial Interface Kerrison Predictor Large Matthews correlation coefficient Meted Offset binary P-Value Puromycin Aminonucleoside Radio frequency Random Sampling Sample Variance Shock Small Specification St. Moritz Library Time series Volatility emotional dependency meeting |
| Content Type | Text |
| Resource Type | Article |
