The Journal of Portfolio Management, Summer 2016, Vol. 42, No. 4: pp. 38-48

Black-Litterman方法和回归预测中的主观判断：理论和运用

作者：Alois Geyer (Vienna University of Economics and Business; Vienna Graduate School of Finance), Katarína Lucivjanská (VU Amsterdam in Amsterdam)

摘要：Black-Litterman方法的一大吸引力就是在配置最优投资组合时，它考虑了对预期收益率的主观判断。作者利用Bayesian框架下的回归预测（Predictive Regression），开发了一个推导这种主观判断及其不确定性的新方法，发现回归预测的Bayesian估计结果和Black-Litterman的思想十分吻合。本文引入投资者对回归方程可预测程度的看法作为主观判断的一部分。在这种设定下，主观判断的不确定性可以由Bayesian回归自然而然地得到，而不是使用收益率的协方差。最后，作者揭示了考虑主观判断的不确定性是使得该方法优于其他投资策略的主要原因。

The Black–Litterman Approach and Views from Predictive Regressions: Theory and Implementation

Alois Geyer (Vienna University of Economics and Business; Vienna Graduate School of Finance), Katarína Lucivjanská (VU Amsterdam in Amsterdam)

ABSTRACT

A major attraction of the Black–Litterman approach for portfolio optimization is the potential for integrating subjective views on expected returns. In this article, the authors provide a new approach for deriving the views and their uncertainty using predictive regressions estimated in a Bayesian framework. The authors show that the Bayesian estimation of predictive regressions fits perfectly with the idea of Black–Litterman. The subjective element is introduced in terms of the investors’ belief about the degree of predictability of the regression. In this setup, the uncertainty of views is derived naturally from the Bayesian regression, rather than by using the covariance of returns. Finally, the authors show that this approach of integrating uncertainty about views is the main reason this method outperforms other strategies.

原文链接：http://www.iijournals.com/doi/abs/10.3905/jpm.2016.42.4.038

翻译：陈爽