The Alpha and Beta of Risk Attribution
提出将跟踪误差分解为阿尔法和贝塔成分的方法，适用于证券、行业和因子投资过程，支持任意粒度下的平行归因分析。
1. Ben Davis 1. is a vice president at MSCI in Berkeley, CA. (benjamin.l.davis{at}msci.com) 2. Jose Menchero 1. is an executive director at MSCI in Berkeley, CA. (jose.menchero{at}msci.com) <!-- --> 1. To order reprints of this article, please contact Dewey Palmieri at dpalmieri{at}iijournals.com or 212-224-3675. Davis and Menchero present a methodology for attributing the alpha and beta components of tracking error. They define an intuitive and precise decomposition of tracking error into alpha and beta components. Their approach is completely general and is applicable to security-, sector-, and factor-based investment processes. The authors show that by following this methodology, drilldowns into tracking error at any level of granularity can be neatly decomposed into parallel alpha and beta drilldowns. They also show that factor-based risk attribution represents an important special case of the alpha and beta risk decomposition, and they demonstrate that the residual exposure-based analysis of residual risk is prone to counterintuitive attribution effects. TOPICS: [Factor-based models][1], [volatility measures][2], [statistical methods][3] [1]: https://www.pm-research.com/topic/factor-based-models [2]: https://www.pm-research.com/topic/volatility-measures [3]: https://www.pm-research.com/topic/statistical-methods