What Is the Black-Litterman Model?

The Black-Litterman (BL) Model is an analytical tool used by portfolio managers to optimize asset allocation within an investor’s risk tolerance and market views. Global investors, such as pension funds and insurance companies, need to decide how to allocate their investments across different asset classes and countries. The BL model helps them do this by generating expected returns of hypothetical portfolios, taking into account the investor’s view.ging the issue of model estimation error, which is problematic when generating expected return outcomes.

The Basics of the Model

The BL model was designed to rely on observed market data and remove investor bias (the investors’ views) based on the notion that investors can’t beat the market with any regularity. In that sense, it is a market-neutral asset allocation model. However, investors can, and often do, have strong market views. Here, the BL Model can show them how far astray they may be going from an essentially market-neutral view.

An Example of the Black-Litterman Model

Let’s say the portfolio management team at a certain insurance company is extremely bullish on global markets in the year ahead. They’re inclined to overweight large cap stocks in the major economies, especially the US. However, after consulting with the BL Model through their investment advisors, they see BL Model is less optimistic. Consequently, they decide to tone back the degree to which they’ll be overweight global large cap stocks. The BL model has been around since 1992 and it receives a great deal of respect from the institutional investment community. 

Key Takeaways

  • The BL Model takes historical market data and then generates potential outcomes.
  • It relies on historical data to generate potential outcomes.
  • The investor then applies their own risk views (e.g. some are long-only), and the BL Model then generates an appropriate asset allocation.
  • The BL Model only uses actual historical data, as opposed to expected outcomes, eliminating the investor’s bias.