Understanding investment risk through drawdown analysis A more refined method of managing and mitigating loss Risk is a central theme in the investment world a core tenet that underscores every step of our investment process and a counterweight to an investor s desire for return. The irony is that, given the enormous role and usage of the term, the concept of risk is typically not well defined and can even be subjective, making risk arithmetic challenging to understand if not outright misleading. Return, on the other hand, is easily defined by the growth or decline in the market value of a portfolio. As detailed below, standard deviation, the broadly used default risk metric, has significant limitations. This leads us to embrace the concept of drawdown as a more intuitive and therefore useful approach to understanding and tracking investment risk. figure 1 Loss potential This is the prevailing traditional measure of risk in investment analysis. What standard deviation does not tell you: Looking at the downside half of a normal distribution, we can see how much of the downside risk is not accounted for by standard deviation. Standard deviation line 32% of outcomes 68% of outcomes The limitations of standard deviation Standard deviation is a measure that is used to quantify the amount of variation of a set of returns. A low standard deviation indicates that the returns tend to be close to the average (also called the expected value) set of returns, while a high standard deviation indicates that the returns are spread out over a wider range of values. Challenges in using standard deviation as a risk barometer are twofold: It is influenced by both up and down market results, which can obscure the risks of loss from an investment or portfolio position It is measured on the basis of historic results, which can dramatically influence the story being told The actual truth is that risk in the markets might be exactly the opposite of what the standard deviation measure is telling us. While the financial crisis caused catastrophic market upheavals, by 2011, downside risks had been significantly reduced as a result of financial strengthening in the banking industry and the Federal Reserve s diligent efforts to provide safety and liquidity. On the other hand, the 2018 Wilmington Trust Corporation and its affiliates. All rights reserved. page 1 of 7
For institutions with specific spending mandates, or pension funds with target funding ratios, it is imperative that portfolios be designed in a manner that constrains the extent of drawdown. market rallies in 2016 while justified by improving earnings and expected improvements in the tax and regulatory environment were pushing market measures such as price/earnings multiples into stratospheric levels, where downside potential in the market was likely getting larger. Clearly a better means of providing quantitative risk assessments is needed. Drawdown, a better approach Given these inadequacies, what can we look at as an additional and more intuitive risk measure? The measure that we believe provides a better assessment of security and portfolio risk is drawdown, which is defined, most often in the asset management space, as the decline in net asset value from a historic high point. Mathematically, if the net asset value is denoted by Vt, t 0, then the current peak-to-trough drawdown is given by: D t = V t (max 0 u t) V u * For institutions with specific spending mandates, or pension funds with target funding ratios, it is imperative that portfolios be designed in a manner that constrains the extent of drawdown. This seeks to ensure that commitments can be kept, with a greater probability, at the point in time they are needed. The best way to appreciate the benefits of constructing a portfolio using drawdown constraints is to consider two portfolios. Based on drawdown, the first portfolio is optimized, where mathematical analysis of asset class returns over a fixed period is employed to project future returns and inform investment weightings in an effort designed to optimize portfolio performance. The second is a baseline portfolio using Cash, Tax-Exempt Bonds, Domestic, and International Equity shown as follows: Optimized Baseline * Dt = Drawdown at time t Vt = net asset value at time t Vu= the maximum net asset value observed from 0 through t Equity 44.6% 62.8% U.S. Large Cap 25.0% U.S. Small Cap 10.0% 40.0% International Developed 7.0% International Emerging Markets 2.6% 22.8% Fixed Income 40.0% 35.2% U.S. Investment-Grade-Tax Exempt 40.0% 35.2% Real Assets 4.2% 0.0% U.S. REITs 4.2% 4.2% Hedge Fund 11.2% 0.0% Cash 0.0% 2.0% TOTAL 100.0% 100.0% 2018 Wilmington Trust Corporation and its affiliates. All rights reserved. page 2 of 7
figure 2 Growth of $10 million (Performance January 2000 May 2017) $28.4MM $25 $20 Optimized Maximum drawdown: 30.8 $24.0MM $15 $10 $5 Baseline Maximum drawdown: 35.1 2000 2002 2004 2006 2008 2010 2012 2014 2016 Optimized portfolio Baseline portfolio Initial wealth Optimized: Return: 6.34 Sharpe ratio: 0.75 Baseline: Return: 5.45 Sharpe ratio: 0.58 Value added: $4,400,000 Data shown in Figures 2, 3, and 4 are for illustrative purposes only, reflecting the historical application of static allocations to index results, and do not reflect the results of actual investing from clients. The optimized and baseline portfolios were created with the benefit of hindsight and do not reflect the impact of material economic or market factors on investment decisions. The optimized allocation includes asset classes that do not appear in the baseline allocation, reflecting real asset and liquid alternative strategies. Data reflect index returns and are not reduced for the impact of fees, trading costs, or any other expenses. Investor returns are reduced by such fees and expenses incurred in the management of an investment account and have a compounded impact over time. Similarly, the returns shown would be lower if the results reflected the deduction of advisory fees. Investing involves risk and you may incur a profit or a loss. Past performance is no guarantee of future results. Back-testing these allocations, and assuming no withdrawals during this period and an initial investment of $10 million over a period of the last 17 years, we find some interesting results (see Figure 2). The optimized portfolio experienced a lower variance and a higher return when compared to the baseline portfolio. What is most striking is that the maximum optimized differs by almost 5%. We note that, the terminal wealth of the optimized portfolio exceeds the baseline by $4.4 million. 2018 Wilmington Trust Corporation and its affiliates. All rights reserved. page 3 of 7
figure 3 Growth of $10 million: Factoring in annual withdrawal of 2% (Performance January 2000 May 2017) $20 $18 $16 $18.9MM $16.8MM $14 $12 $10 $8 $6 $4 $2 $0 2000 2002 2004 2006 2008 2010 2012 2014 2016 Optimized portfolio Baseline portfolio Initial wealth Optimized: Return: 6.34 Sharpe ratio: 0.75 Baseline: Return: 5.45 Sharpe ratio: 0.58 Value added: $2,100,000 Data shown in Figures 2, 3, and 4 are for illustrative purposes only, reflecting the historical application of static allocations to index results, and do not reflect the results of actual investing from clients. The optimized and baseline portfolios were created with the benefit of hindsight and do not reflect the impact of material economic or market factors on investment decisions. The optimized allocation includes asset classes that do not appear in the baseline allocation, reflecting real asset and liquid alternative strategies. Data reflect index returns and are not reduced for the impact of fees, trading costs, or any other expenses. Investor returns are reduced by such fees and expenses incurred in the management of an investment account and have a compounded impact over time. Similarly, the returns shown would be lower if the results reflected the deduction of advisory fees. Investing involves risk and you may incur a profit or a loss. Past performance is no guarantee of future results. Consider the fact that most institutional portfolios typically have a mandatory withdrawal amount that needs to be factored in. In our next example, we assume a 2% annual withdrawal rate (see Figure 3). After the same period, the terminal wealth of the optimized portfolio exceeds that of the baseline portfolio by over $2.1 million. What is even more significant is that the optimized portfolio was underwater (i.e., below its initial investment value) for a period of 36 months while the other portfolio was underwater for 76 months. This is critical if the institution needs to maintain a certain minimum amount of principal, which could cause regulatory or statutory issues. 2018 Wilmington Trust Corporation and its affiliates. All rights reserved. page 4 of 7
figure 4 Growth of $10 million: Factoring in annual withdrawal of 2% and a one-time withdrawal of $3 million (Performance January 2000 May 2017) $16 One-time withdrawal of $3 million $14 $12 $14.2MM $11.7MM $10 $8 $6 $4 $2 $0 2000 2002 2004 2006 2008 2010 2012 2014 2016 Optimized portfolio Baseline portfolio Initial wealth Optimized: Return: 6.34 Sharpe ratio: 0.75 Baseline: Return: 5.45 Sharpe ratio: 0.58 Value added: $2,500,000 Data shown in Figures 2, 3, and 4 are for illustrative purposes only, reflecting the historical application of static allocations to index results, and do not reflect the results of actual investing from clients. The optimized and baseline portfolios were created with the benefit of hindsight and do not reflect the impact of material economic or market factors on investment decisions. The optimized allocation includes asset classes that do not appear in the baseline allocation, reflecting real asset and liquid alternative strategies. Data reflect index returns and are not reduced for the impact of fees, trading costs, or any other expenses. Investor returns are reduced by such fees and expenses incurred in the management of an investment account and have a compounded impact over time. Similarly, the returns shown would be lower if the results reflected the deduction of advisory fees. Investing involves risk and you may incur a profit or a loss. Past performance is no guarantee of future results. Typically, there will be instances where the institution may need adequate reserves to pay off a lump sum obligation, or make a capital expenditure. In such cases, the need for optimization becomes even more compelling. In this example, we assume that the institution makes a one-time withdrawal of $3 million on August of 2009 (see Figure 4). The terminal wealth difference is now $2.5 million as shown above. Note that the optimized portfolio recovers quickly (16 months underwater) and gets back up to its growth trajectory, while the baseline portfolio languishes for a full 52 months after 2018 Wilmington Trust Corporation and its affiliates. All rights reserved. page 5 of 7
Consider the simple reality that, if an investor experiences a 20% drop in the value of a portfolio, a return of 25% is necessary simply to get back to the starting point. the withdrawal. The previous three examples are typical scenarios and need to be considered when performing the asset allocation exercise. Traditionally, investors focused on how their results compared to market results to determine if they were satisfied with their investment performance. This methodology was popularized by institutional investors and their investment consultants. While this view continues to have value, institutional investors have become more focused on their specific needs (such as spending rates, pension liabilities, etc.) as they look to their assets to help them achieve the desired outcomes. The investors can seek to control the drawdown exposure of their portfolios through their asset allocation decisions and selection and allocation of investment vehicles. This can help to improve the odds that the investors portfolios will be able to meet their stated needs within the timeframes stipulated. Back to the future? Consider the different ways of looking at potential drawdown outcomes. One method is to go back and look at historic events to see how individual securities or portfolio combinations behaved. For example, comparing one s portfolio today to the Asian financial crisis in 1998 (which wreaked havoc on much of Asia and stirred fears of a global meltdown) can give a good measure of how the portfolio might react to a foreign-generated currency crisis. Other significant events can be similarly modeled so that investors quickly build an understanding of how their portfolios might react to a variety of previously experienced market disruptions. These are typically called stress scenarios. While stress testing your portfolio based on past events is a good way to check how your investments might have performed, we could be looking at other forwardlooking measures, such as valuation metrics that include price/earnings ratios, dividend yields, and price-to-cash flow, etc. In this look-ahead analysis, cheap market conditions from the past are likely to show reduced risks of significant future drawdowns, while higher valuations may very well show the opposite. Investors can tailor their risk appetites based on these conditions and their goals-based objectives to help them stay on track to achieve success. Portfolio optimization involves determining the preferred combination of assets, looking at return expectations, asset class volatilities, and the correlations of results among various asset classes. Optimizing portfolios based on drawdown exposure can be accomplished by substituting drawdown for volatility in developing the preferred combination of assets for given drawdown levels, a result that creates what is usually called the efficient frontier. Optimizing this combination of assets can be an important component of investment success since it strives to enable an investor to manage the degree of downside risk in a portfolio. Consider the simple reality that, if 2018 Wilmington Trust Corporation and its affiliates. All rights reserved. page 6 of 7
an investor experiences a 20% drop in the value of a portfolio, a return of 25% is necessary simply to get back to the starting point. Bigger drops lead to even more lopsided situations. A 50% drop requires a 100% return just to get back to square one. Managing drawdown exposures, therefore, becomes critical. Avoiding unforced errors Market downdrafts are never comfortable situations. Markets will test the resolve of even the steeliest investor. It is at moments like these that managing expectations becomes critical, as investors can let fear and other emotions get the best of them and be driven to make investment mistakes. The investor who has built a plan around manageable drawdown prospects is in far better shape to weather this storm. Having a reasonable awareness of how much potential downside (based on historic events) there is to one s portfolio helps an investor to remain calm during turbulent times and not sell investments at the very time the market may be getting near a bottom. Conclusion: Implementing the drawdown framework Implementing an investment framework that includes drawdown-measuring capabilities is not an easy task. The breadth of uses and computations required stretch from performing simple estimates on individual securities to the far more complex issues involving estimating future drawdown risks and performing optimizations. To make this a reality, Wilmington Trust provides an enhanced portfolio analysis tool that enables clients to visualize model scenarios in an effort to assess which are most likely to help achieve various investment goals. To explore how drawdown analysis may help curb risk in your portfolio, contact a Wilmington Trust Relationship Manager. This article is for informational purposes only and is not intended as an offer or solicitation for the sale of any financial product or service. This article is not designed or intended to provide financial, tax, legal, investment, accounting, or other professional advice since such advice always requires consideration of individual circumstances. If professional advice is needed, the services of a professional advisor should be sought. Wilmington Trust is a registered service mark. Wilmington Trust Corporation is a wholly owned subsidiary of M&T Bank Corporation. Wilmington Trust Company, operating in Delaware only, Wilmington Trust, N.A., M&T Bank, and certain other affiliates, provide various fiduciary and non-fiduciary services, including trustee, custodial, agency, investment management, and other services. International corporate and institutional services are offered through Wilmington Trust Corporation s international affiliates. Loans, credit cards, retail and business deposits, and other business and personal banking services and products are offered by M&T Bank, member FDIC. Investment Products: Are NOT Deposits Are NOT FDIC Insured Are NOT Insured By Any Federal Government Agency 2018 Wilmington Trust Corporation and its affiliates. All rights reserved. page 7 of 7 CS16265 4-2018