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Black–Litterman model

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 an asset allocation based on the equilibrium assumption (assets will perform in the future as they have in the past) and then modifies that allocation by taking into account the opinion of the investor regarding future asset performance.[1]

Background edit

Asset allocation is the decision faced by an investor who must choose how to allocate their portfolio across a number of 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.

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 markets 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.[2]

See also edit

References edit

  1. ^ Team, Wallstreetmojo Editorial (2022-09-14). "Black Litterman Model". WallStreetMojo. Retrieved 2022-11-15.
  2. ^ [1]
  • Black F. and Litterman R.: Asset Allocation Combining Investor Views with Market Equilibrium, Journal of Fixed Income, September 1991, Vol. 1, No. 2: pp. 7-18
  • Black F. and Litterman R.: Global Portfolio Optimization, Financial Analysts Journal, September 1992, pp. 28–43 JSTOR 4479577

External links edit

Discussion

  • 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

Resources

  • Spreadsheet implementations:
    • Peter Ponzo
    • Implementation in Python Notebook and case study analysis
  • Applets:

    black, litterman, model, finance, mathematical, model, portfolio, allocation, developed, 1990, goldman, sachs, fischer, black, robert, litterman, published, 1992, seeks, overcome, problems, that, institutional, investors, have, encountered, applying, modern, p. 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 an asset allocation based on the equilibrium assumption assets will perform in the future as they have in the past and then modifies that allocation by taking into account the opinion of the investor regarding future asset performance 1 Contents 1 Background 2 See also 3 References 4 External linksBackground editAsset allocation is the decision faced by an investor who must choose how to allocate their portfolio across a number of 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 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 markets 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 2 See also editMarkowitz model for portfolio optimizationReferences edit Team Wallstreetmojo Editorial 2022 09 14 Black Litterman Model WallStreetMojo Retrieved 2022 11 15 1 Black F and Litterman R Asset Allocation Combining Investor Views with Market Equilibrium Journal of Fixed Income September 1991 Vol 1 No 2 pp 7 18 Black F and Litterman R Global Portfolio Optimization Financial Analysts Journal September 1992 pp 28 43 JSTOR 4479577External links editDiscussion 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 levelsResources Spreadsheet implementations Peter Ponzo Implementation in Python Notebook and case study analysis Applets Canlin Li Retrieved from https en wikipedia org w index php title Black Litterman model amp oldid 1217926470, wikipedia, wiki, book, books, library,

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