Content area
Full text
INTRODUCTION
Active portfolio management is about leveraging forecasts. As a means of forecast, portfolio managers (PM) or analysts collect information, generate views and seek to convert these views into optimal portfolio holdings. These views may not necessarily be explicit security return predictions, but could be views on relative performance or portfolio strategies. 1 On the other hand, portfolio optimisers do not admit views directly as inputs, but rather expect one explicit return forecast for each security. In order to feed an optimiser, PMs need to translate their views into explicit return forecasts for those view-relevant securities, and are forced to come up with a number (often zero) to represent 'no view'. This practice immediately raises two questions:
What is the appropriate way of translating PM views into explicit return forecasts?
Is it legitimate to use zero return to represent 'no view'?
Regarding the second question, zero-mean return forecasts will be treated by the optimiser relentlessly as views. A typical response of the optimiser will be to use this security to leverage others on which the PM expresses optimism. This easily gives rise to 'unexpected' behaviours (that is, unstable, counter-intuitive or corner solutions). Similar 'erratic' behaviours occur in response to estimation errors in the risk model as well. Yet, in these situations, the common use of optimisation constraints does not address the underlying problem, but definitely undermines the mean-variance efficiency.
To the first question, the Black-Litterman Global Portfolio Optimisation Model (BL) (Black and Litterman, 1992) provides an elegant answer. The model sets the forecast in a Bayesian analytic framework. In this framework, the PM needs only produce a flexible number of views and the model smoothly translates the views into explicit security return forecasts together with an updated covariance matrix - exactly what a conventional mean-variance portfolio optimiser expects. If the views arrive in an acceptable form, that is, linear views, this model can fully consume them.
Moreover, the model handles the second question with ease: without view, there are theoretical justifications for taking the market equilibrium returns as the default forecasts. A remarkable feature of this approach is robustness. As the posterior views are a combination of the market and the PM views, PMs have a common layer, the market view, as their starting...