The objectives of this workshop are to give you an in-depth introduction to the Black-Litterman asset allocation model and a practical, hands-on understanding of how you can implement and use this model to determine optimal portfolio allocations for specific classes of assets in a manner consistent with investors' market views.
We start with a general introduction to the model and explain how this model overcomes some of the severe weaknesses of the traditional, Markowitz mean-variance optimization approach. Further, we introduce the Black-Litterman formula and explain the intuition behind it and discus the advantages and disadvantages of using this model.
We then proceed with a number of workshops, giving step-by-step instructions for the practitioner to combine market equilibrium expected returns with "investor views" to generate new vectors of expected returns.
Following an overview of the investment process, participants will learn how to set the key parameters in the Black-Litterman framework. This involves a discussion of how the model is used to observe the equilibrium returns in global capital markets and then blend the equilibrium returns with "our" own views to provide a set of expected returns. We explain and demonstrate how we determine the weight and confidence levels on our own views relative to the equilibrium.
We next turn to looking at risk control and optimization. We describe the process of assessing and controlling tracking error risk and Market Exposure (a statistical measure of a portfolio's sensitivity to market moves), and we explain and demonstrate how optimal portfolios can be constructed under risk (budget) constraints.
We conclude with a complete, "real life" asset allocation exercise. We assess and discuss how the allocation has performed when applied to historical data and how it will be expected to perform in the current, low-yield, low-returns environment.
