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All About Outcomes CALLAN INSTITUTE January 2018 Research All About Outcomes New Generation of Multi-Asset Class Strategies Focuses on Cutting Risk In the wake of the Global Financial Crisis, a new generation of multi-asset class (MAC) products emerged that emphasized risk management and expanded their toolkits to include shorting and derivatives. Callan groups these “outcome-oriented” MACs into four broad categories: Risk Parity, Risk Premia, Absolute Return, and Long Biased. The reasons to include MAC strategies in a portfolio can vary widely. An asset owner may need to lower equity risk concentration, mitigate drawdown risk, or seek higher risk-adjusted returns. Callan has seen increased interest in MAC strategies over the last year and expects this trend to continue. Introduction Multi-asset class (MAC) strategies have existed for decades; the first product with an allocation to bal- anced stock and bond strategies was launched more than 80 years ago. In the 1980s, MAC strategies evolved, moving beyond static into tactical asset allocation. In the 1990s, MAC strategies expanded glob- ally, seeking improved diversification and increased alpha. These iterations of MACs largely failed to provide adequate downside protection during the 2000-02 bear equity market and 2008 Global Financial Crisis (GFC). The investment community responded by empha- sizing risk management and expanding the MAC toolkit to include shorting and derivatives, as well as untethering them from a static market benchmark (e.g., a 60/40 portfolio), which could sink a strategy in a bear equity market. Concurrently, interest in risk premia and risk parity was reinvigorated by investors seeking return generation and risk diversification beyond traditional allocations. Knowledge. Experience. Integrity. This paper examines the latest generation of outcome-oriented MAC strategies—most of which were launched after the GFC. These MAC strategies vary widely in investment approach, complexity, and tar- geted outcomes. To assist in evaluating them, Callan has developed four broad categories of MACs: • Callan Absolute Return MAC • Callan Long Biased MAC • Callan Risk Parity MAC • Callan Risk Premia MAC Categorizations are often difficult due to some overlap in product characteristics, but they greatly assist in determining how MACs can be employed in a portfolio, which will largely depend on an investor’s goals and philosophy, sensitivity to fees, and comfort with leverage, shorting, and derivatives. Why the Interest? There are three main drivers of interest in MACs: 1. Diversification Most long-term “well-diversified” portfolios are dominated by equity risk. Diversification into other asset classes such as private real estate, high yield, and hedge funds will help lower equity risk concentration, but perhaps not as much as one would think (Exhibit 1). While equities represent virtually the entire risk budget of a 60% equities/40% fixed income portfolio, adding those three asset classes by funding from equities and fixed income only reduces equity risk by 21 percentage points. MAC strategies try to limit equity risk concentration, eliminate equity risk altogether, or dynamically man- age equity risk with the goal of participating more in bull equity markets (i.e., upside capture) than in bear equity markets (i.e., downside capture). In some strategies, equity risk is low due to going long and short physical securities to express relative value trades or gain exposure to risk premia (e.g., value, carry, Exhibit 1 U.S. Fixed Income 0.15% Less Diversification, U.S. Fixed U.S. Broad Global but More Equity Risk Income Equity ex-U.S. 40% 36% U.S. Broad Equity Equity 42.9% 56.9% Global ex-U.S. Equity 24% Equity Capital Allocation = 60% Equity Risk Concentration = 99.85% Real Estate 10% Real Estate 11% High Yield 3% High Yield 5% Hedge Funds U.S. Broad 7% Hedge Funds Equity 10% 30% U.S. Broad Equity Global 45% U.S. Fixed Global ex-U.S. Income ex-U.S. Equity Equity 25% 34% 20% Equity Capital Allocation = 50% Equity Risk Concentration = 79% Note: Calculation of risk concentration is based on Callan’s 2018-2027 capital market assumptions. Source: Callan 2 momentum). Risk Parity—among other MAC strategies—constrains equity risk as a certain percent of its risk budget. Other techniques may include dynamic risk management (e.g., lowering equity exposure when volatility rises), stop-loss strategies, and using derivatives to mitigate tail risk. The outcome-oriented 2. Drawdown Protection Related to equity risk concentration is the increased demand for downside protection in a portfolio. This goal of most MAC stems from not only the two bear equity markets in the last 20 years but also the need to add some ballast. strategies can be Many asset owners are running at maximum portfolio risk capacity as they strive to meet return hurdles summarized as pursuing that become further out of reach as capital market expectations erode. MAC strategies are seen as a way a long-term return hurdle to offer some stabilization and diversification or to enhance return relative to low-yielding fixed income. between bonds and stocks while carefully Mitigating large drawdowns can significantly bolster long-term performance since higher returns are managing and limiting risk required to offset down years. For example, a portfolio down 20% in year one must return 25% in year two along the way. to break even. An asset pool in negative cash flow mode (i.e., benefits or spending exceed contributions to the fund) would require an even higher return in year two. During the GFC many “diversified portfolios” did not offer much downside protection when most risky assets lost value (Exhibit 2). Global tactical asset allocation (GTAA) products benchmarked to a 60/40 portfolio incurred large drawdowns during the GFC. Unshackling a MAC strategy from a market bench- mark (e.g., a global 60% stocks/40% bonds portfolio) can be advantageous1 as it liberates the manager to significantly reposition a portfolio quickly in anticipation of a transition to a different economic regime. Some MAC strategies depend on macroeconomic forecasting skills to reduce drawdown risk, while others with systematic investment approaches constrain equity risk or maintain a low correlation to equities. The outcome-oriented goal of most MAC strategies can be summarized as pursuing a long-term return hurdle between bonds and stocks while carefully managing and limiting risk along the way. If successful, this will lead to attractive risk-adjusted returns (Sharpe ratios) over the long run. S&P 500 60% Global Equity/40% Global Fixed 60% U.S. Equity/40% U.S. Fixed Exhibit 2 0% Cumulative Drawdown From Peak to Trough -10% ough) Tr -20% -30% -40% -50% Drawdown (Peak to -60% 91 93 95 97 99 01 03 05 07 09 11 13 15 17 Global Equity = MSCI ACWI, Global Fixed = Bloomberg Barclays Global Aggregate, U.S. Equity = S&P 500, U.S. Fixed = Bloomberg Barclays Aggregate Source: Callan 1 An asset owner needs to be comfortable with monitoring MAC strategies in the absence of a market benchmark. A deep under- standing of the investment process, drawdown controls, current positioning of the portfolio, and peer group opportunity set over the next few years will assist with ongoing evaluation. Knowledge. Experience. Integrity. 3 3. Higher Risk-Adjusted Returns In general, the investment industry expects 10-year forward-looking returns to be low, relative to history, across all asset classes. Most asset owners acknowledge that achieving an annualized return of 7%-8% over the next 10 years is going to be challenging given the current economic environment of low yields and elevated prices for U.S. stocks. Furthermore, public defined benefit (DB) plans, endowments and foundations, and Taft-Hartley plans are probably at full risk capacity, while many corporate DB plans are de-risking out of equities and alternative investments. For many asset owners, higher return per unit of risk is more appealing than ever. With cleverly stated goals of “equity-like returns with less risk” and the emphasis on risk-adjusted returns, MAC strategies are garnering interest. Many MAC strategies are targeting long-term returns of T-bills + 4%-6% or more with half the risk of equities. To put that in context, Callan’s 2018-2027 return/risk expectation for large cap U.S. equities is T-bills + 4.5% with 17.4% risk (Sharpe ratio = 0.258 (4.5/17.4)). MAC strategies are striving to deliver on their stated goals in various ways. In the next section we explain how Callan defines and categorizes MAC strategies and then elaborate on the primary sources of return and methods that are being employed to pursue a T-bills + 4%-6% return with half the risk of equities. MAC Categories Callan classifies MAC strategies into four categories based on the manager’s investment process/philosophy and historical-based metrics such as return, risk, correlation to stocks/bonds, and average stock/bond beta.2 Two questions help determine where a MAC strategy belongs in our taxonomy: 1. Where on the continuum from “market neutral” to “directional” does the strategy’s market exposure fall? 2. What is the basis for the strategy’s portfolio construction, on a spectrum from “systematic harvesting” to “macroeconomic forecasting?” The answers may be nuanced, and thus categorizing a MAC strategy into one of the four groups may not be a perfect fit. Hence, the MAC groups do overlap, making classification tricky3 (Exhibit 3). Exhibit 3 The MAC Map Directional Risk Parity Long Biased Absolute Risk Premia Return Market Neutral Systematic Harvesting Macroeconomic Forecasting Source: Callan 2 Callan’s definition of MAC strategies does not include target date portfolios, target risk portfolios, multi-asset income strategies, traditional balanced funds, ETF managed portfolios, managed futures/CTAs, options/volatility strategies, and (global) tactical asset allocation funds that closely track a blended benchmark of stocks and bonds.
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