Portfolio perspectives

Understanding uncertainty

BlackRock Investment Institute |Apr 29, 2019

Building resilient, investor-specific portfolios requires a shift away from point estimates for returns. That is why we explicitly include uncertainty into our return projections and can create optimal portfolios by considering multiple return pathways.

Overview

The incorporation of uncertainty is an important part of our revamped approach to portfolio construction. By incorporating uncertainty, we recognize that mean expected returns for assets are estimated with error rather than assuming they are known, as is the case with mean variance techniques. We consider the distribution around the mean, effectively reducing the weight placed on our mean (central) estimate. How much uncertainty should we consider? We highlight some criteria used to identify a suitable amount of uncertainty in our process. They include the back-tested predictive power of our asset class return models, the historic volatility of assets and the desire for diverse portfolios when optimizing. Uncertainty in mean returns feeds into our stochastic simulations, that give a range of potential return pathways from five years out to the long term. When constructing portfolios, these simulated pathways and our mean return uncertainty enable us to use robust optimization techniques that generally lead to less concentrated portfolios compared with those portfolios resulting from mean variance optimization. It also gives flexibility to focus on certain upside or downside scenarios when constructing portfolios to fit client needs.

Banding together chart

This information is not intended as a recommendation to invest in any particular asset class or strategy or as a promise -or even estimate -of future performance. Source: BlackRock Investment Institute, April 2019. Data as of 28 February, 2019. Notes: Return assumptions are total nominal returns. US dollar return expectations for all asset classes are shown in unhedged terms, with the exception of global ex-US Treasuries, hedge funds, and global ex-US large cap equities. Our CMAs generate market, or beta, geometric return expectations. Asset return expectations are gross of fees. For a list of indices used, visit our Capital Market Assumptions website at blackrock.com/institutions/en-us/insights/portfolio-design/capital-market-assumptions and click on the information icon in the Asset class return and volatility expectations table. We use BlackRock proxies for selected private markets because of lack of sufficient data. These proxies represent the mix of risk factor exposures that we believe represents the economic sensitivity of the given asset class. There are two sets of bands around our mean return expectation. The darker bands show our estimates of uncertainty in our mean return estimates. The lighter bands are based on the 25th and 75th percentile of expected return outcomes –the interquartile range -of potential return pathways (Garlappi, Wang and Uppal, 2006 ). Indices are unmanaged and used for illustrative purposes only. They are not intended to be indicative of any fund or strategy’s performance. It is not possible to invest directly in an index.

Distinguishing between uncertainty and risk is important. We define uncertainty as the range of outcomes for the mean and risk as the range of outcomes around the mean. For example, instead of saying an asset has a mean return of 6%, we say a mean return in range of 5-7% even if the risk, or volatility, of the asset stays the same. We believe overlooking uncertainty, combined with common mean variance optimization (MVO) techniques, can lead to undesirable results such as unstable or overly concentrated asset allocations without the use of ad-hoc constraints.

Our approach does two important things: First, it acknowledges that we should not place full conviction on a specific value for the mean expected return. Instead, we allow for other potential return pathways where the mean expected return is different. Observing market data over the last 20 years only gives us information on one state of the world, or one regime. We cannot base our expected returns only on historic observation as future regimes can differ from the past, resulting in structural changes to the mean return. Second, our uncertainty varies by asset class. Why is this important? A lower ability to estimate returns for one asset class (for example when an asset’s returns are poorly explained by well-known public market factors) should be reflected with a wider uncertainty range, all else equal. For two assets of the same mean risk and return, we would hold less of the asset where we have greater uncertainty in the mean return assuming investors are averse to uncertainty. See the Banding together chart above.

Philipp Hildebrand
Philipp Hildebrand
Vice Chairman, BlackRock
Jean Boivin
Jean Boivin
Head of BlackRock Investment Institute
Misha Van Beek
Financial Modeling Group
Anthony Chan
Portfolio Research, BlackRock Investment Institute
Paul Henderson
Portfolio Research, BlackRock Investment Institute
Vivek Paul FIA
Vivek Paul FIA
Senior Portfolio Strategist, BlackRock Investment Institute