time. But the corrections/bear markets that occur along the way raise recurring questions about portfolio construction and what should be done to “protect” against market sell-offs. We believe there is no “magic bullet” available through hedging the portfolio via either options or through trading volatility. Instead, we encourage investors to shift their thinking from “protecting your portfolio against volatility” to “reducing your sensitivity to volatility.” Through proper allocation between risk control assets (investment-grade fixed income) and risk assets (everything else), investors can position themselves to ride out the volatility that is inherent in risk assets. While not a focus of this report, we do believe it is possible to add value by tactically allocating between risk control and risk assets. However, it is hard to do and takes a back seat to strategic asset allocation when looking at managing volatility. We examine in this report two other approaches to reducing volatility in portfolios – shifting to lower volatility assets within the risk asset category and
executing lower volatility strategies within the equity asset class. We think these asset allocation and implementation strategies will become increasingly important in coming years as the low volatility markets of the last several years return to more normal conditions.
EXHIBIT 1: LONG TIME COMING
Source: Ned Davis Research, Inc., Northern Trust. Data through 3/4/2014. Averages date back to 1928.
Exhibit 1 depicts the length of time the S&P 500 has gone without a correction of 5%, 10% or 20% – the higher the triangle, the longer the market has gone without the related decline. The 5% market correction realized in early February 2014 offset an overextended period of calm where the market had gone 150 days without a 5% pull-back (as opposed to the average 50-day duration). We are still extended with respect to larger corrections, having gone over 600 days without a 10% decline. This is roughly double the average duration during bull markets, but nearly four times the average duration of all market cycles.
0 250 500 750 1,000 1,250 1,500 1,750 2,000 2,250 1945 1950 1955 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 T radi ng day s
LENGTHS OF TIME BETWEEN MARKET CORRECTIONS
Trading days before 20% correction Trading days before 10% correction Trading days before 5% correction Avg. days to 20% - (635 days) Avg. days to 10% - (161 days)
3,109 days Northern Trust Asset Management http://www.northerntrust.com/ investmentstrategy James D. McDonald Chief Investment Strategist firstname.lastname@example.org Michael Leon Director, Risk Management Strategies email@example.com
Daniel J. Phillips, CFA
Investment Strategist firstname.lastname@example.org
Sanford B. Carton
Investment Analyst email@example.com
New episodes of market volatility frequently raise the question of how best to manage market turmoil – such as using options strategies. We are skeptical about the merits of managing overall portfolio volatility through hedging strategies and believe that overall asset allocation is a better approach. We would categorize the two main approaches to volatility hedging as strategic hedging and tactical hedging. Strategic hedging includes ongoing risk management strategies such as regularly buying put options on the S&P 500 that will increase in value upon a significant market decline. However, our research indicates that a long-term strategy of buying puts is not cost effective over time when compared with other ways to lower volatility in the portfolio.
In our study shown in Exhibit 2, we modeled three scenarios of an investor with a 100% equity portfolio. They could stay 100% in equities, or they could choose one of two volatility-reducing strategies: either move 40% of the equities into investment-grade fixed income, or implement a derivative (“option”) overlay strategy on their equity exposure by buying 5% out of the money put options on the S&P 500 every three months and rolling that put upon expiration. Our simulation was run using listed exchange contracts from February 2011 forward, which incorporated the nearly 20% decline in the S&P 500 during the 2011 European Debt Crisis.
EXHIBIT 2: STRATEGIC HEDGES ARE VERY EXPENSIVE
Source: Northern Trust, Bloomberg. 60/40 portfolio comprised of S&P 500 Index and Barclays Capital U.S. Aggregate Bond Index, respectively. Assumes put options were 5% out-of-the-money at purchase, 3 months prior to expiration. One benefit of the option overlay strategy is that an investor does not have to sell their stock
holdings and can remain fully invested in bull markets. But Exhibit 2 shows the drag that the cost of buying puts exerts on a portfolio, even in a period of overall upward momentum. While there was considerable benefit from the put buying strategy during the August 2011 period, it was given back over the next six months as the market advanced and the new puts expired worthless. Interestingly, the return experience from the put-buying strategy and the reduced risk portfolio (60%/40%) proved relatively comparable during this study period, which shows that the cost of put protection overcame the ability to remain fully invested. On a longer-term basis, data on 3-month systematic protective put strategies from 1990 through 2011 showed that, over long periods of time and multiple market cycles, an option-based strategy of purchasing out-of-the-money puts underperformed simply reducing exposure to risk assets. The cost of using a derivative overlay (compared to the 50/50 mix of S&P500 and Cash) averaged about 1.5% a year. (Source: Merrill Lynch).
-20 -15 -10 -5 0 5 10 15 20
May-11 Aug-11 Nov-11 Feb-12 May-12 Aug-12 Nov-12 Feb-13 May-13 Aug-13 Nov-13 Feb-14
T ot al r et ur n (% )
DOWNSIDE RISK PROTECTION WITH PUT OPTIONS
3 month S&P 500 return 3 month return with put overlay strategy Cumulative relative return of put strategy Cumulative relative return of 60/40 strategy
Some investors consider tactical approaches to managing volatility, and put options can work if the investor is able to perfectly time their entrances and exits. As the market sells off and the price of the put option rises, an investor can benefit from trimming their exposure to the puts by selling them in the market before expiration. But investors looking to employ a tactical approach may find this is hard to do. Exhibit 3 shows year-to-date price movements of the S&P 500 and the iPath S&P 500
VIX Short-Term Futures Exchange Traded Note (VXX), the iPath exchange-traded note
designed to track the CBOE volatility index (commonly referred to as the fear index). VXX does exactly what it sets out to do, which is to provide investors a way to hedge against increasing equity volatility. It has very high convexity (meaning it moves a lot when there is stress in the market), has a correlation of -0.87 against the S&P 500, and is highly liquid.
EXHIBIT 3: TACTICAL HEDGES ARE VERY TRICKY
Source: Northern Trust, Bloomberg. Period: 12/31/2013 through 3/6/2014.
While the VXX tracks market volatility and can provide excellent protection when markets sell off, it is also an extremely volatile implementation vehicle (note how the market’s recent 5% correction was dwarfed by the 35% jump in the VXX). Because of this volatility, VXX requires especially good market timing and adept tactical moves in order to benefit from its inclusion in the portfolio. For instance, perfect market timing (buying at “1” and selling at “3”) would have provided the portfolio with a nice 35% gain to offset the 5% loss in the S&P 500 over that same period. However, being late on the initiation of that trade by two days (buying at “2”) reduced the return on the trade to 21% and being late on closing out the trade by two days (selling at “4”) reduced the return to 14%. So, if the investor was two days late on both the entrance and exit of the hedging strategy (effectively buying at “2” and selling at “4”) the 35% gain falls to just 2%. Far worse, buying at the height of market frenzy (“3”) and holding through the end of this study (March 6th) would translate to a 20% loss. Thus, VXX is definitely a short-term trading tool that should be treated with caution. The long-term return profile of VXX doesn’t provide much comfort on this front. Since its launch (1/30/2009), VXX has a cumulative return of -99% (further arguing for its use as a short-term tactical trading vehicle and not a foundational piece of the portfolio). Of course, it doesn’t help that the product was launched at the height of market volatility – a likely manifestation of the Wall Street motto “when the ducks quack, feed them!”
90 95 100 105 110 115 120 125 130 12/31 1/4 1/8 1/12 1/16 1/20 1/24 1/28 2/1 2/5 2/9 2/13 2/17 2/21 2/25 3/1 3/5
S&P 500 & VXX YEAR-TO-DATE PRICE MOVEMENT
iPath S&P 500 VIX exchange-traded note (VXX) S&P 500
Now that we have shared our views on the limitations of hedging strategies to reduce general portfolio volatility, we move to our recommendation: the best strategy to handle volatility is to reduce your sensitivity to the volatility and do not chase volatility targeting products. We think this is best accomplished through exposure to the best diversifier against equity market risk –
investment-grade bonds. While that assertion is unlikely to put us into consideration for next year’s Nobel Prize in Economics, we think the analysis in Exhibit 4 helps illustrate that this approach works in all market environments – not just in bond bull markets. Interestingly, the 60/40 portfolio provided more frequent downside protection in rising interest rate environments than it did in the falling rate cycle. To understand the graphic, let’s examine the years 1974 and 1975. In 1974, the S&P 500 was down 27% but a more diversified 60/40 portfolio fell by 14%. In contrast, in the rally of 1975 the 60/40 portfolio rose 26% but the overall S&P 500 gain was 37%. Another way to think of this is that the return sacrifice of 11% in 1975 is the premium paid for the insurance for years like 1974 where the portfolio decline was reduced by 13% by fixed income. Average downside
protection over these time frames was 7.7%, while the average “premium,” or upside return sacrificed, was 6.3%.
EXHIBIT 4: BONDS HELP IN FALLING, AND RISING, RATE ENVIRONMENTS
Source: Northern Trust, Ibbotson, Bloomberg. 60/40 portfolio represented by 60% S&P 500 and 40% Ibbotson Intermediate Term Bond Index.
Despite all the worries about portfolio protection from fixed income in a rising interest rate environment, it is worth noting: during the last bond bear market (1963-1981), rates climbed from 4% to 14% and a diversified portfolio assisted in downside protection on seven occasions. In contrast, during the bond bull market of 1994-2012, where rates went from 8% to 2%, bonds only assisted in downside protection on four occasions. The examples shown in Exhibit 4 demonstrate one of our key portfolio construction tenets: during periods of market stress, the best diversifier is risk-control assets (investment-grade bonds) due to their low- to negative-correlation to equities. In contrast, the various assets within the risk asset category all share sensitivity to global equity prices, including a correlation of 0.56 for U.S. High Yield and 0.95 for the MSCI World ex-U.S index. Our definition of risk assets is those asset classes that have notable exposure to changes in stock prices (the equity risk factor) – an exposure that typically becomes acute during periods of stress in the financial markets. As such, we do not rely on these asset classes for robust diversification
-18 -12 -6 0 6 12 18 -45 -30 -15 0 15 30 45 1994 1997 2000 2003 2006 2009 2012 Int er es t r at e ( % ) T ot al r et ur n (% )
FIXED INCOME PROTECTION IN BEAR & BULL BOND MARKETS BOND BULL MARKET (1994-2012)
-18 -12 -6 0 6 12 18 -45 -30 -15 0 15 30 45 1963 1966 1969 1972 1975 1978 1981 Int er es t r at e ( % ) T ot al r et ur n (% )
BOND BEAR MARKET (1963-1981)
All equity excess return 60/40 return 10-year UST yield
through all economic cycles. However, some risk asset classes can be used to protect on the downside (while still providing upside participation) in times where heightened volatility is
expected. Exhibit 5 provides the full slate of risk asset options alongside two key volatility measures for each. The first risk measure – and the most common one – is standard deviation, which is a measure of how much a particular asset class’s returns can deviate from its average return. Looking at emerging market equities, it would not be surprising to see returns fall within a band of plus or minus 24% – a good deal of risk, and the riskiest asset class for which we dedicate an allocation.
EXHIBIT 5: CAN WE SHUFFLE OUR RISK ASSETS?
Source: Northern Trust Capital Market Assumptions. *Downside risk is the standard deviation of the negative returns. Private equity standard deviation and downside risk are synthetic estimates.
Another measure we look at is downside risk, which measures reasonable expectations around the potential for negative returns. For instance, using the historical record of emerging market equities, a 16% decrease in any given year should not be considered uncommon. The return potential for emerging market equities is such that we are willing to take on this risk resulting in its inclusion in our asset allocation – but, if focusing on mitigating downside, emerging market equities have historically had the greatest downside risk.
Hedge funds offer a great deal of risk mitigation, but simple risk mitigation is not how a hedge fund manager should be evaluated (as a 60/40 portfolio can provide substantial risk mitigation itself). Rather, hedge fund managers seek to show evidence of true alpha generation to support their higher investment thesis. Other asset classes within risk assets that provide better downside protection than global equities include high yielding fixed income (both corporate high yield and emerging market debt), global listed infrastructure, and commodities. Of course the return outlook for any of these options is critical – an asset class with low volatility but a weak return outlook will not earn much allocation in our risk asset portfolio.
Reflecting the opportunity to reduce expected volatility through changing asset class exposures, we made such a change last month in our global tactical asset allocation model. Because of a continued challenging growth and monetary policy outlook in emerging markets, we shifted some of our recommended risk exposure from emerging market equities to global listed infrastructure stocks. We expect global listed infrastructure (such as transportation, telecom, electric utilities and pipelines) to participate in an upward moving market, but provide us greater downside protection than emerging
60/40 HedgeFunds High Yield E.M. Debt Global L.I. Commodi-ties DevelopedEquities Global R.E. ResourcesNatural PrivateEquity EquitiesE.M. Standard deviation (%) 9.7 7.0 9.2 9.7 14.5 15.3 15.5 18.8 18.9 20.4 23.9 Downside risk* (%) -6.5 -3.9 -6.1 -6.2 -9.5 -10.2 -10.8 -12.9 -12.3 -9.5 -16.4 -20 -10 0 10 20 30 R is k m eas ur e v al ue ( %)
RISK MEASURES OF SELECT RISK ASSETS
Standard deviation (%)
Downside risk* (%)
market stocks in a more difficult market. Global listed infrastructure stocks have nearly 40% lower volatility than emerging market equities, and 42% lower downside risk. While our primary driver for the trade was fundamentally driven, the resulting reduction in portfolio volatility (and risk) was also an important consideration.
Another approach to reducing volatility is to construct an equity portfolio specifically designed for that purpose. In Exhibit 6, we show the risk and return of various equity factors for the period of 1997 through early 2014, and compare them to a global portfolio (MSCI World Index). As can be seen from this data, three factor approaches to equities had lower historical volatility than global equities and also generated better returns. Interestingly, low beta stocks (those stocks less likely to move in the same direction, or at the same magnitude, as the broader markets) outperformed the market at much lower volatility. While this directly contradicts academic gospel (the efficient market hypothesis and models based on its tenets – such as the Capital Asset Pricing Model or Arbitrage Pricing Theory – say that stock returns are based on exposure to risk factors), this anomaly has been gaining traction in the investment community in recent years. We also believe that higher quality companies (as measured by factors such as profitability, balance sheet productivity, and management decision making) can outperform the general market with lower volatility.
EXHIBIT 6: CAN WE SHUFFLE OUR EQUITY APPROACH?
Source: Northern Trust, MSCI Barra. Quality factor is Northern Trust’s proprietary quality measure. Data from 1997-2014. That is not to say that the traditional risk factors of Size (small cap stocks) and Value (cheap stocks on the basis of their book-to-price valuations) have not also provided excess returns. As seen in Exhibit 6, our data shows that these risk factors have provided superior returns over time (and, in fact, better than the lower volatility strategies) – but come with additional risk. So while these stocks don’t help reduce the overall volatility within the equity portfolio, they can help serve the purpose of long-term capital appreciation for those portfolios less concerned about volatility. Importantly, both small cap stocks and value stocks have proven their ability to appropriately compensate the investor for the increased risk they are assuming. Conversely, our study shows that Growth has all the extra risk of Value but does not provide the same return premium over longer-term time frames (such as the 17 year period shown in Exhibit 6); while large cap stocks sit fairly close to the overall market profile (not a surprise, given the market is cap-weighted). All risk factors have the ability to
outperform for extended periods of time; and, therefore, including growth and large cap stocks in the Growth Quality Size (small) Size (large) Value Low volatility Low beta
MSCI World Index
0 2 4 6 8 10 12 10 12 14 16 18 20 22 24 R et ur n ( annual iz ed % )
Risk (standard deviation, annualized %)
overall portfolio may make sense to capture these “runs” and provide stability to the portfolio. However, for the investor with a long-term horizon merely looking to invest in those risk factors with the best long-term returns, Size and Value stack up well in that regard.
Different points within a market cycle bring out different investor issues, and concerns, that need to be researched and addressed. With market volatility being suppressed in recent years (significantly due to active market support from global central banks), it only seems likely to increase over the next year or two. We think investors are best served by reducing their sensitivity to the volatility through proper strategic asset allocation, not by chasing the newest volatility reduction tool. We believe long-term put programs are too expensive, while trading short-term volatility is too difficult. We do think there are opportunities to reduce volatility within the risk asset classes, by reallocating to lower risk assets that have attractive outlooks. Finally, we think that investors should be
intentional about their approach to equities and select the approach that will best help them reach their objective – be it lower volatility or higher long-term returns.
Special thanks to Michael DeJuan, Portfolio Construction Desk Head, for input on portfolio construction topics; and to Mark Sodergren, Head of Quantitative Active Management, and Sri Kancharla, Quantitative Equity Portfolio Manager, for input on factor-based equity investing.
APPENDIX: RETURN DATA FROM EXHIBIT 4
Source: Northern Trust, Ibbotson, Bloomberg. 60/40 portfolio represented by 60% S&P 500 and 40% Ibbotson Intermediate Term Bond Index. All data represent annual total returns (%).
S&P 500 60/40 Difference S&P 500 60/40 Difference
1963 22.8 14.3 8.4 1994 1.3 -1.3 2.6 1964 16.4 11.5 5.0 1995 37.5 29.2 8.3 1965 12.5 7.9 4.6 1996 22.9 14.6 8.3 1966 -10.0 -4.1 -5.9 1997 33.3 23.3 10.0 1967 23.9 14.7 9.2 1998 28.5 21.2 7.3 1968 11.0 8.4 2.6 1999 21.0 11.9 9.1 1969 -8.4 -5.3 -3.1 2000 -9.1 -0.4 -8.7 1970 3.9 9.1 -5.2 2001 -11.9 -4.1 -7.8 1971 14.3 12.1 2.2 2002 -22.1 -8.1 -14.0 1972 19.0 13.5 5.5 2003 28.7 18.2 10.5 1973 -14.7 -7.0 -7.7 2004 10.9 7.4 3.4 1974 -26.5 -13.6 -12.9 2005 4.9 3.5 1.4 1975 37.2 25.5 11.8 2006 15.8 10.7 5.1 1976 23.9 19.5 4.4 2007 5.6 7.4 -1.8 1977 -7.2 -3.7 -3.4 2008 -37.0 -16.9 -20.0 1978 6.6 5.3 1.2 2009 26.4 14.9 11.5 1979 18.6 12.8 5.8 2010 15.1 11.9 3.2 1980 32.5 21.1 11.4 2011 2.1 5.0 -2.9 1981 -4.9 0.8 -5.7 2012 16.0 10.4 5.6
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