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Bad Beta Good Beta, State-space News Decomposition and the Cross-section of Stock Returns

机译:错误的Beta,良好的Beta,状态空间新闻分解和股票收益的横截面

摘要

This study employs an innovative market-based approach, where ROE are employed as proxy for cash-flow news and a state-space model is used for market news decomposition. We document that the explanatory power of the Bad Beta Good Beta (BBGB) model of Campbell and Vuolteenaho (2004) is about 30% for the cross-section of stock returns. We also find the BBGB model adequately explains the size effect leading to its superior performance. The results are obtained controlling for 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.
机译:本研究采用了创新的基于市场的方法,其中ROE被用作现金流量新闻的代理,而状态空间模型被用于市场新闻的分解。我们证明,Campbell和Vuolteenaho(2004)的不良Beta良好Beta(BBGB)模型的解释能力对于股票收益的横截面约为30%。我们还发现BBGB模型可以充分说明尺寸效应,从而带来其卓越的性能。获得了控制新闻分解方法和市场新闻代理偏差的结果。我们通过提供一种易于实施且一致的基于市场的新闻分解方法来为文献做出贡献。

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