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

Black-Litterman方法和回歸預測中的主觀判斷：理論和運用

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優投資組合時，它考慮了對預期收益率的主觀判斷。作者利用Bayesian框架下的回歸預測（Predictive Regression），開發了一個推導這種主觀判斷及其不确定性的新方法，發現回歸預測的Bayesian估計結果和Black-Litterman的思想十分吻合。本文引入投資者對回歸方程可預測程度的看法作為主觀判斷的一部分。在這種設定下，主觀判斷的不确定性可以由Bayesian回歸自然而然地得到，而不是使用收益率的協方差。最後，作者揭示了考慮主觀判斷的不确定性是使得該方法優于其他投資策略的主要原因。

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.

原文鍊接：http://www.iijournals.com/doi/abs/10.3905/jpm.2016.42.4.038

翻譯：陳爽