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Bad beta good beta, state‐space news decomposition and the cross‐section of stock returns
Author(s) -
Wang Kent,
Li Jiawei,
Huang Shicheng
Publication year - 2013
Publication title -
accounting and finance
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.645
H-Index - 49
eISSN - 1467-629X
pISSN - 0810-5391
DOI - 10.1111/j.1467-629x.2012.00470.x
Subject(s) - beta (programming language) , econometrics , stock (firearms) , economics , financial economics , proxy (statistics) , cash flow , stock market , equity (law) , computer science , mathematics , statistics , accounting , geography , political science , context (archaeology) , archaeology , law , programming language
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.