BlackRock s methodology for long-term returns

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1 C A P I T A L M A R K E T A S S U M P T I O N S A P R I L 2017 BlackRock s methodology for long-term returns What investment returns can we expect in the long term across asset classes? Such assumptions are a key input of asset allocation decisions for institutions, financial advisors and individual retirees. This document presents the methodology used to calculate the BlackRock Investment Institute s long-term equilibrium capital market assumptions (CMAs), the long-term complement to our five-year CMAs. Alain Kerneis Head of Strategy and Market Views, BlackRock Client Solutions We publish our return assumptions in an interactive graphic. The tool enables clients to visualize expected returns, volatilities and correlations of fixed income, equity and alternative assets from several different currency perspectives. Our long-term equilibrium assumptions reflect equilibrium or valuation-neutral market conditions that we would expect in the long run, and can be used as key inputs for strategic asset allocation. Our five-year assumptions incorporate valuation signals and can help investors adjust their allocations when valuations and macroeconomic conditions substantially deviate from equilibrium levels. We update our assumptions quarterly, with the most significant changes occurring in the five-year numbers. The assumptions are formulated and published by the BlackRock Investment Institute every quarter, guided by a team of BlackRock investment professionals with expertise in portfolio management, economics, asset allocation and risk management. Gabriella Barschdorff Natalie Gill Stuart Jarvis Vivek Paul BlackRock Client Solutions contributors (top left to bottom right) Long-term model Our long-term assumptions are based upon a multi-factor model of asset prices, known as the Arbitrage Pricing Theory (APT) in the finance literature. According to this model, the return expected from an asset is the direct result of the asset s exposure to underlying sources of rewarded risk ( factors ) within investment markets. The exposure of an asset to each underlying factor is the beta to that factor. The expected return of an asset in excess of the risk-free rate is then just the sum of the betas multiplied by the risk premium associated with each rewarded risk factor. Our estimate of the risk-free rate is based upon current market expectations. The key rewarded risk factors in our model are as follows 1. Equities 2. Interest rates 3. Inflation 4. Credit 5. Illiquidity We describe these factors in more detail in the pages that follow.

2 A century of returns Annual real returns: equity, bonds and cash, Sources: BlackRock Investment Institute and Credit Suisse, April Notes: Global equity and bond returns are Credit Suisse 23-country world indexes, with the equity index weighted by market capitalization, and the bond index weighted by GDP. Cash is represented by U.S. Treasury bills. Real returns are measured relative to U.S. inflation. Data are as of end December Past performance is not a reliable indicator of future performance. Equity risk premium The equity risk premium (ERP) represents the long-run expected return advantage of holding equity over cash. The observed annual ERP was 4.3% from 1900 to 2016, in geometric terms (the difference between a historical equity real return of 5.1% and cash returns of 0.8%). See the chart above. The ERP has been a little higher than this over the past five decades (see the bars for ), but has collapsed since 2000 due to historically muted equity returns. We assume an ERP of 4.0% in the future, which is slightly lower than what the average would suggest. Investors are better equipped with tools to construct globally diversified portfolios than they were 100 years ago. Therefore, the compensation for market risk should, in our view, be lower. We extend this analysis to other asset classes by accounting for their beta a measure of how much an asset or security tends to move along with an index or a portfolio. For example, a beta of 0.75 between a stock and an index indicates that for every 1% move in the index, the stock would be expected to move by 0.75%. We employ a multi-factor framework. This means the overall risk premium of an asset depends on its beta to the economic risk factor and its betas to the other risk factors listed on the previous page. We add a cash return of 2% our estimate of the long-term risk free rate. After rounding and adjusting the figures for annualizing, we arrive at a total expected return. Fixed income risk premia We use risk premia relative to cash for longer duration fixed income, inflation-linked bonds and credit. This is because there is additional return associated with investing in longer maturities, and with moving away from government bonds into asset classes with credit risk, historical analysis suggests. The historical term premium (expressed as percentage points of extra return per year of duration) of the sovereign debt of G7 countries varies significantly over time, and has dwindled to near zero in recent years. It has had a median value of around 0.1 percentage points since See the chart below. This is also consistent with the small premium that global bonds delivered relative to cash between 1900 and 2016, as shown in the chart on the left. Using the median value above, we would expect a 10-year government bond to have a 0.5% higher yield than a fiveyear government bond. Our research also suggests a lower term premium for inflation-linked bonds (around 0.05 percentage points per year of duration) and a higher one for corporate credit (around 0.25 percentage points). Note: These numbers also can fluctuate over time and depend on the risks of these different asset classes. Term premium pendulum Term premium for G7 sovereign debt, Sources: BlackRock Investment Institute, April Notes: The chart is based on the Bloomberg Barclays G7 Global Treasury Index. The term premium is defined as the index yield minus the one-month U.S. cash rate divided by the index duration. The median term premium is calculated over the period shown. 2

3 Private-public market spreads Forming return assumptions for alternative asset classes is challenging. Reliable benchmarks for underlying asset class returns are not always available in sectors such as infrastructure and private equity. Alternative premia estimates To overcome these hurdles, we start with the same multifactor model as described on page 1 to form our assumptions for a public market proxy. We then adjust our assumptions to incorporate a few differences between private and public markets, such as the higher levels of leverage and fees that tend to be associated with private markets. Investors expectations for being compensated for illiquidity risk and any differences in valuation or supply and demand between markets can also affect future performance. We estimate these factors from the historical performance of private investments relative to public market equivalents, again net of fees and adjusted for differences in leverage. Given data limitations, we do not intend to produce estimates for each of these factors individually and have defined an aggregate measure of what we call the private-public market spread. Following are explanations of how we arrive at this spread for the main alternative asset classes in our model portfolio: Private Equity: The private equity risk estimates are intended to relate to a representative exposure of a globally diversified private equity fund-of-fund. Exposures to broad risk factors (such as geography and sector) are based off our analysis of the universe of private transactions in the private equity market from 2000 to present. The private equity risk estimates are constructed from estimated fund-of-fund exposures, and assume a 25% / 75% allocation between venture capital (VC) and leveraged buyouts (LBO). Infrastructure Equity: For a diverse mix of infrastructure equity assets, we believe a spread of 1% reflects a reasonable extra return above that of an equivalent public equity investment. This reflects the compensation investors can expect to receive in exchange for accepting long lock-up periods and idiosyncratic risks unique to private infrastructure, such as regulation or construction risks. Infrastructure Debt: Spreads on infrastructure debt in recent years have contracted meaningfully, driven by increased interest from institutional investors and a limited supply of assets. Given the supply-demand picture, and the fact that debt sits above equity in the capital structure, investors should expect a smaller spread for infrastructure debt compared to infrastructure equity or private equity. We assume an illiquidity premium of 0.1%, based on our analysis of the spread between private infrastructure debt issues and liquid corporate bonds of equivalent credit quality. Sources: BlackRock Investment Institute, December Notes: Estimates are based on the historical annual performance of private investments relative to public market equivalents, net of asset management fees and adjusted for differences in leverage. Private Real Estate and Mezzanine Debt: We do not assign a spread to private real estate. This is because listed and private (or direct) real estate have had similar returns over the past two decades, according to NCREIF (private) and NAREIT (public) index returns. We also find private and public real estate to be exposed to similar return drivers. This does not mean we believe private real estate is a poorly rewarded asset class it can still be attractive relative to listed real estate for investors looking to shape a diversified real estate portfolio, in our view. By contrast, we assume a 1% spread for real estate mezzanine debt. Increased regulations are encouraging banks to curb lending. This creates opportunities in mezzanine debt financing for investors comfortable with concentrated exposures and long lock-up periods, we believe. Our assumed spread for alternative asset classes are summarized in the table above. Alternatives calculations In our framework, we explicitly focus on the returns and risks associated with broad asset classes, (represented by an index), as opposed to the risks and returns from investing in any particular actively managed strategy. In alternatives, the distinction between active (alpha) and passive (beta) is less relevant, as there is usually no way to access beta on a standalone basis. Indeed, a major motivation for allocating to private markets is to find idiosyncratic sources of return that can only be captured via skillful active management. Given the difficulty of isolating an index return in alternatives markets, the return numbers for alternatives in our capital market assumptions are meant to represent the performance of an average manager in those asset classes, net of fees. Assumed returns for other asset classes are in index terms, and, unless otherwise noted, returns not denominated in US dollars are assumed to be currency unhedged. 3

4 Final calculations In summary, the CMAs are based on the following: Five rewarded risk factors; the interrelationship between different asset classes; inherent return drivers such as compensation for illiquidity and credit risk. The resulting annualized risk premium assumptions for the asset classes we track are displayed in the chart below. To arrive at our final capital market assumptions, we add our calculated estimates of the risk premium for each asset class to the risk-free rate. We then make adjustments for rounding and annualization. For each asset class, we provide two sets of assumptions, based on geometric and arithmetic calculations. See the appendix for an explanation of arithmetic versus geometric returns, as well as for details on BlackRock proxies for alternatives asset classes, where historical index data are often lacking or of poor quality. About the CMAs The BlackRock Investment Institute (BII) formulates and publishes CMAs every quarter. We cover long-term equilibrium assumptions, which are key inputs for strategic asset allocation, and five-year CMAs that take into account how we think economic and market conditions play out in the medium term. This document assumes a US dollar currency perspective, but our methodology is the same across regions and currencies. Our CMA group is responsible for formulating the assumptions. It is co-chaired by BII s Richard Turnill and BlackRock Client Solutions Alain Kerneis and consists of senior members from BII, BlackRock Client Solutions and BlackRock s Risk and Quantitative Analysis group. Beating cash Expected long-term equilibrium annualized risk premiums over U.S. cash by asset class, December 2016 Sources: BlackRock Investment Institute, April Notes: The assumptions are based on geometric calculations. See our interactive graphic for full details on the return assumptions and a list of the underlying indexes used for each asset class. Past performance is not a reliable indicator of future performance. 4

5 Appendix Arithmetic returns in this document are converted into geometric returns to account for volatility. A simplified version of the formula we are using is: Expected geometric return = Expected arithmetic return 0.5 Expected volatility 2 ALTERNATIVES PROXIES Private equity: We use data (leverage, deal size, geography, sector and type) on historical (venture and buyout) deals for the time period from 2000 to the present. This data is then mapped onto a variety of public market factors, which are adjusted for private equity characteristics including geography, industry, country, and leverage. Infrastructure equity: We construct a proxy consisting of exposures to baskets of publicly listed infrastructure-related companies. We then adjust for unique characteristics of private infrastructure investments, incorporating exposures to construction and idiosyncratic, project-specific risks. Private real estate: We seek to capture the true behavior of global real estate across core, value-add and opportunistic sectors, by analyzing publicly available market indices (FTSE EPRA / NAREIT Global Real Estate Index series and NCREIF Property Index NPI series) looking back several years ( ). We use regression analysis to map these publicly traded risk factors to the characteristics we are seeking as representative of global real estate, including property type, geography, leverage, and sector exposures. Real estate mezzanine debt: This is modeled as a mix of real estate and high yield, plus an adjustment to more closely mirror the volatility and behavior of that asset class. The correlations used in our calculations can be found in the matrix below. Seeking diversification Assumed correlations between asset classes, December 2016 Sources: BlackRock Investment Institute, April Notes: The correlation and volatility forecasts are based on a proprietary BlackRock risk model, using monthly returns since September See our interactive graphic for a list of underlying indexes used for each asset class. 5

6 BlackRock Investment Institute BlackRock's Capital Market Assumptions disclosures: This information is not intended as a recommendation to invest in any particular asset class or strategy or as a promise of future performance. Note that these asset class assumptions are passive, and do not consider the impact of active management. All estimates in this document are in U.S. dollar terms unless noted otherwise. Given the complex risk-reward trade-offs involved, we advise clients to rely on judgment as well as quantitative optimization approaches in setting strategic allocations to all the asset classes and strategies. References to future returns are not promises or even estimates of actual returns a client portfolio may achieve. Assumptions, opinions and estimates are provided for illustrative purposes only. They should not be relied upon as recommendations to buy or sell securities. Forecasts of financial market trends that are based on current market conditions constitute our judgment and are subject to change without notice. We believe the information provided here is reliable, but do not warrant its accuracy or completeness. This material has been prepared for information purposes only and is not intended to provide, and should not be relied on for, accounting, legal, or tax advice. The outputs of the assumptions are provided for illustration purposes only and are subject to significant limitations. Expected return estimates are subject to uncertainty and error. Expected returns for each asset class can be conditional on economic scenarios; in the event a particular scenario comes to pass, actual returns could be significantly higher or lower than forecasted. Because of the inherent limitations of all models, potential investors should not rely exclusively on the model when making an investment decision. 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