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Bad beta good beta, state-space news decomposition and the cross-section of stock returns


  • The authors wish to thank John Campbell, Guo Hui, Yongmiao Hong, Huang Hongming, Andrew Ferson, Michael Oneil, Huang Lin and participants for seminars in Cincinnati, WISE, HU Berlin, Nottingham, PKU, SWUFE, and 2010 asset pricing workshop in NUT and 2011 AEA Denver meeting for comments and suggestions. The project is supported by NSF (china) Grant #71101122. All remaining errors are our own.


This study employs an innovative market-based approach, where return on equity (ROE) is employed as a proxy for cash-flow news and a state-space model is used for market news decomposition. We document that the bad beta good beta (BBGB) model of Campbell and Vuolteenaho (2004) explains about 30 per cent of the cross-sectional variations in US stock returns. We also find that the BBGB model adequately explains the size effect leading to its superior performance in this area. Our method controls for the news decomposition method and market news proxies’ bias. We contribute to the literature by providing an alternative easy-to-implement and consistent market-based method for news decomposition.