In finance, the Black–Litterman model is a mathematical model for portfolio allocation developed in 1990 at Goldman Sachs by Fischer Black and Robert Litterman, and published in 1992. It seeks to overcome problems that institutional investors have encountered in applying modern portfolio theory in practice. The model starts with the equilibrium assumption that the asset allocation of a representative agent should be proportional to the market values of the available assets, and then modifies that to take into account the 'views' (i.e., the specific opinions about asset returns) of the investor in question to arrive at a bespoke asset allocation.
Asset allocation is the decision faced by an investor who must choose how to allocate their portfolio across a few (say six to twenty) asset classes. For example a globally invested pension fund must choose how much to allocate to each major country or region.
In principle Modern Portfolio Theory (the mean-variance approach of Markowitz) offers a solution to this problem once the expected returns and covariances of the assets are known. While Modern Portfolio Theory is an important theoretical advance, its application has universally encountered a problem: although the covariances of a few assets can be adequately estimated, it is difficult to come up with reasonable estimates of expected returns. In other words, composing a portfolio based only upon statistical measures of risk and returns yields simplistic results; these are known as unconstrained optimizations.
Black–Litterman overcame this problem by not requiring the user to input estimates of expected return; instead it assumes that the initial expected returns are whatever is required so that the equilibrium asset allocation is equal to what we observe in the markets. The user is only required to state how his assumptions about expected returns differ from the market's and to state his degree of confidence in the alternative assumptions. From this, the Black–Litterman method computes the desired (mean-variance efficient) asset allocation.
In general, when there are portfolio constraints - for example, when short sales are not allowed - the easiest way to find the optimal portfolio is to use the Black-Litterman model to generate the expected returns for the assets, and then use a mean-variance optimizer to solve the constrained optimization problem.
- Black F. and Litterman R.: Global Portfolio Optimization, Financial Analysts Journal, September 1992, pp. 28–43 JSTOR 4479577
- Guangliang He and Robert Litterman: The Intuition Behind Black-Litterman Model Portfolios
- A. Meucci: The Black-Litterman Approach: Original Model and Extensions
- Jay Walters: The Black-Litterman Model in Detail
- Thomas M. Idzorek: A Step-By-Step Guide to the Black-Litterman Model - Incorporating user-specified confidence levels
- Blacklitterman.Org an independent web site with a thorough coverage of the Black-Litterman model, maintained by J. Walters
- Spreadsheet implementations:
- J. Walters
- Peter Ponzo
- Implementation VBA for a master project (ECE Paris, Engineer School)
- Implementation in Python and case study analysis
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