Do You Know the Risk in Your Portfolio?
Do You Know the Risk in Your Portfolio? A Short Study in Volatility By Craig Brimhall, CFP®, CRPC®, CFS® Vice President – Retirement Wealth Strategies June 6, 2016 Risk is a word that means different things to different people. Businesses take educated risks to get started. Individuals take on risk to develop their careers, move to another state, start over, get married, have children…all are risky propositions. However, people generally take risks in order to reap a reward. Nothing in life is riskless… especially in the investing world. It’s just a question of managing various risks. The purpose of this paper is to help you understand what you mean by risk, how much risk you may be comfortable taking, and how much risk you consider is appropriate for your goals. In other words, not only do you need to define “risk” for yourself, but you should know how much risk you may need to take in order to achieve your financial goals, and then how much you are comfortable taking. What you may need to do and what you are comfortable doing can be two different things.
Abstract All investors need to know what the various types of risks there are in the marketplace, how much risk they are willing to accept, and how much they may need to consider in order to achieve their goals. There are three principles to building a sound retirement portfolio — downside protection; income generation; and growth or inflation protection. These competing priorities need to be balanced to lower risk, pay income, and provide future income needs through growth of principal. In a recent study nearly 70% of retirees said “downside protection” was one of the top priorities for their portfolio in retirement.1 For more information regarding the importance of volatility management and “sequence of returns” risk, read the research paper entitled, “Volatility and Sustainable Withdrawals” also by Craig Brimhall and available from your Ameriprise advisor. Knowing and understanding the risks you may need to take, and what you are comfortable with, is a most important conversation to have with your financial advisor. One of the most common measurements of volatility is standard deviation, and knowing how much your portfolio may fluctuate from the “expected long-term return” is the linchpin of the conversation you may need to have.
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2014 Retiree Insights Study, The Diversified Services Group, Inc.
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Risk... What is it? Risk is the potential of losing something of value. Various dictionaries define it in similar terms. However, they do not necessarily deal with the issue of the probability of a risk happening, just the possibility. For this paper, we will be dealing with probabilities, and discussing risk in terms of the market value of your investments. And, that market value fluctuation can be expressed by another word: volatility. Even though volatility is defined as variance from the mean (or average), it is generally recognized that investors don’t have a problem with returns that are above the average, but they do have issues when returns are below the mean; particularly when returns are negative. Of course, managing to rein in negative returns may also mean lowering the potential returns to some degree as well. There are always tradeoffs. Mitigating volatility From a strategic standpoint, one of the main ways to reduce volatility is with a highly diversified portfolio. Investing in a diverse mix of the traditional asset class of stocks, bonds and cash and possibly adding some non-traditional investments as well (also referred to as "alternatives") may enhance the risk diversification of your portfolio. Remember that the main goal of diversification is not to increase return (although it might in some circumstances) but to try to reduce risk. Once you move past the strategies of diversification by asset type and product selection for your portfolio, you could also discuss with your advisor the tactical ideas around downside protection. Although many who have become wealthy have done so by under diversifying (having a concentrated position in a stock, a business, or other investment for example), it may be wise, at some point, to decide to take some profit and diversify away from what has made them wealthy. After all, if the driver of their wealth decides to take the big fall, wealth can evaporate. “Rags-to-richesand-back-to-rags” stories are plentiful. Measuring risk or volatility All investments that vary in value over time can have that volatility measured. Standard deviation is the statistical measure of the volatility of a portfolio’s returns. The calculation is fairly straightforward, and it is very important for all investors to understand the
volatility in their portfolios. Here is the heart of the matter: how much volatility is appropriate for your portfolio in order to accomplish your goals, and how much volatility are you comfortable with? What your portfolio may need, in terms of return, and how much volatility you are comfortable with are not necessarily going to coincide. For those familiar with statistics, you already know about “the bell curve” picture of a standard deviation example. It is shown below. Additional information regarding calculations of standard deviation can be found in the appendix. However, since standard deviations for investments are published, we’ll spend the time here with a shortcut on how to interpret what is being said and how it may affect you and your portfolio. A typical standard deviation “bell curve”
34%
34%
13.5% -3x
-2x
13.5%
-1x
1x
2x
3x
99.5% Standard deviation is, simply stated, the measurement of variance from a mean (an average). In the graphic shown above, the vertical line in the middle is the average or mean. It indicates that in a “normal distribution” of a series of numbers, there will be observations to the right of that line (returns higher than the average) and an equal number of observations to the left (returns lower than the average). You need this collection of numbers to come up with an average. And, “normal” distributions are not necessarily common (especially in measuring investment returns) and there may be more returns to right or left…in other words, the returns may not be symmetrical. Notice that in a normal distribution, basically two-thirds of observations (34% + 34% = 68% in the graphic) occur in what is called “one standard deviation.”
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Two standard deviations will also include observations to the left and right that account for another 27% (13.5% + 13.5% = 27%). Basically, if you include all observations that fall within two deviations, it accounts for 95% of all possibilities. As you can see from the graphic, if you step out three deviations, we can account for 99.5% of possibilities. But, most of the data points occur much closer to average, or within one standard deviation. Some things that get measured, such as portfolio returns or temperatures, have either significant volatility, very low volatility, or somewhere in between. Let’s look at average temperatures in a couple of cities in the US to clarify the point. The weather station may tell you what the average is for the day, but chances are, it’s not the average where you are right now. It’s warmer or colder than the average for this day on the calendar, most likely.
It is always possible for an observation to occur out past two standard deviations (there is a 5% possibility this will occur), but it is more probable that returns, or observations, will occur much closer to “the average.” 68% of the time it should be within one deviation. And once you average these temperatures over time, you end up with an “average” or a “mean.” But that can be deceptive, since an average tells you nothing about the variance. An interesting example might be San Diego, CA vs. Nashville, TN. These two cities have the same average high temperature and that happens to be just a fraction under 70 degrees Fahrenheit. But the average
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maximum temperatures by month in San Diego run from 65 – 76 degrees, depending on the month…a very small span of 11 degrees.2 Nashville’s average monthly high temps range from 47 – 89 degrees…a very high spread of 42 degrees. And yet both cities have had the same average high temperature for the year. This concept holds true in most cases: the averages of items you compare may seem close, but they may be deceptively dissimilar in that the variances may be wildly different. For the sake of trying to clarify the volatility illustration, and assist you in building your own volatility model, let’s now take the standard deviation bell curve and turn it 90 degrees and stand it on end. Simply put, we’ll create a bar graphic with the average return in the middle horizontal line and more positive returns plotted above that mean, and lower returns listed below the mean (see pg. 5-6). Just like temperatures vary over time, so do investment stock returns. Common measuring periods are one year, 3-year, 5-year 10-year, 20-year, and since records began. You will generally notice that whereas there may be a fair amount of difference in the numbers if you look at just one year versus 10 years, once you get a large number of data points, the differences in the volatility number (or returns if we’re discussing the stock market) has a tendency to compress, and therefore we would say they become more reliable or predictable. However, keep in mind that no one can predict the market’s return, and the numbers are simply a look back at what has happened and not what will happen. There are two main numbers to keep in mind in this discussion: “expected return” and “annual standard deviation.” The “return” number is fairly straightforward: it's the total return (capital appreciation and income) on an average annual return basis, but usually realized only over extended periods of time (multiple years). The “standard deviation” number is the volatility you will most likely see, as an annual measurement, on that portfolio as you seek to achieve the “expected return.”
NOAA’s national climatic data center, dates 1981-2010; data from website www.currentresults.com
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But this is where it gets a bit tricky. The standard deviation number, although usually expressed as an annual number, actually changes as you measure it over a multiple year (rolling) basis. This is sometimes referred to as “time-weighted” volatility. In other words, the positive years tend to somewhat cancel out the negative years, and the “range of returns” begins to compress over time, as bad years counterbalance good years, and vice versa.
It may best be seen in a graphic. The chart below is from JP Morgan Asset Management, and shows the range of returns for stocks, bonds, and a 50/50 mix. You will notice at least one significant thing. The range of possible outcomes for a 1-year hold is wildly unpredictable, but once you step out even five years, the range of outcomes compresses significantly.
Range of stock, bond and blended total returns Annual total returns, 1950 to 2015 50%
Investing principles
40%
47%
43%
30%
33%
20%
28% 23% 21%
19%
10%
16%
16%
1%
2%
12%
14%
7%
0%
-8%
-10%
-3%
-2%
1%
-1%
-15%
-39%
-40%
1%
5%
Annual average total return
Growth of $100,000 over 20 years
Stocks
11.1%
$819,296
Bonds
6.0%
$321,853
50/50 portfolio 8.9%
$555,099
-20% -30%
17%
-50% 1-year
5-year rolling
10-year rolling
20-year rolling
Source: Barclays, FactSet, Federal Reserve, Robert Shiller, Strategas/Ibbotson, J.P. Morgan Asset Management. Returns shown are based on calendar year returns from 1950 to 2015. Stocks represent the S&P 500® Shiller Composite and Bonds represent Strategas/Ibbotson for periods from 1950 to 1980 and Barclays Aggregate after index inception in 1980. Growth of $100,000 is based on annual average total returns from 1950 to 2015. Guide to the Markets — U.S. Data are as of March 31, 2016.
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During the 20 years ending 12/31/2015, the S&P 500®3 Index saw returns that went from +47% in one calendar year, to -39%, or an 86 percentage point swing. But over a 5-year rolling basis, the numbers compressed to an average annual return of +28% to -3%. The point is this: if you’re investing and not speculating, more volatile investments need to be viewed with a long-term lens to allow the unpredictability of the short term swings to work themselves out and eventually smooth out the ride. Using the current data from Morningstar and Ibbotson, the annual standard deviation of the S&P 500 Index is about 15 on a long-period measurement (10 years). This number has moved around some over time, but the long-term average (depending on the time frames studied) is in the vicinity of 13-18%, so we’ll use 15% for this discussion. The long-term return for the S&P 500 can be a bit trickier to pin down, since it obviously depends on the “start” and “stop” dates when you examine data. However, from 1926 thru 12/31/2015, the average annual return of the S&P 500 index has been 10.0%, (Source: Morningstar Direct data). I’d like to emphasize: you will be able to do the same exercise with your own portfolio. In the example below, we will walk through the S&P 500 Index annual (calendar year) returns: Step 1:
Step 2:
Step 3:
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10%
25%
25%
10%
10%
-5%
-5%
Step 1: With the aid of your financial advisor, or your own research, put the “expected return” at the middle line. This “expected return” should be a long-term realistic number. For the S&P 500 Index, that number has been about 10%. The volatility number (standard deviation) for the S&P has been about 15% long term3. One standard deviation is where returns are anticipated to fall two-thirds of the time. Step 2: Add the standard deviation number once to the expected return; and then subtract the standard deviation number from the expected return, as shown. So, in 10 years, the S&P annual return may fall between +25% (10% expected return plus 15% standard deviation) and -5% (10% expected return minus 15% standard deviation). Since this still leaves a lot of returns that fall outside of this range, it may be wise to calculate out TWO standard deviations and that should include returns that have occurred 95% of the time. Step 3: Add another standard deviation number to the top return, and subtract the deviation number from the bottom return, as shown. Therefore, returns are expected to fall between +40% (10% return plus 15%, plus 15%) and -20% (10% return minus 15% minus 15%). So, to repeat, 95% of the time, the S&P 500 Index returns are expected to range between +40% and -20%. If things happen as expected, then 2½% of the time returns may exceed 40%, and 2½% of the time returns may fall below -20%. Incidentally, over the past 20 years, there have been two years when the S&P 500 Total Return has had a calendar year return of less than -20%: -22% in 2002 and -37% in 2008.
0%
-20%
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S&P 500 Price Index: The S&P 500® is a basket of 500 stocks that are considered to be widely held. The S&P 500® index is weighted by market value (shares outstanding times share price), and its performance is thought to be representative of the stock market as a whole. The S&P 500® index was created in 1957 although it has been extrapolated backwards to several decades earlier for performance comparison purposes. This index provides a broad snapshot of the overall U.S. equity market. Over 70% of all U.S. equity value is tracked by the S&P 500®. Inclusion in the index is determined by Standard & Poor’s and is based upon their market size, liquidity, and sector. The S&P500 price index reflects only the price return, absent the distribution of dividends.
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Data for 10 years ending 09/30/2015; Source: FactSet and Morningstar.
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Here are the actual returns of the S&P 500 Index total return (dividends included) plotted from the beginning of 1995 through the end of 20155: 40%
25%
10% 0% -5% -20%
Source: Bloomberg as of 12/31/2015. Information provided by third parties is deemed to be reliable but may be derived using methodologies or techniques that are proprietary or specific to the third-party source. Indices shown are unmanaged and do not reflect the impact of fees. It is not possible to invest directly in an index.
Some observations: of the 21 calendar year returns plotted on the graph, fewer than two-thirds of the returns ended up as expected, that is, within one standard deviation. Eleven of the 21 data points ended up between -5% and 25%, or ~50% of the time. Although there were more returns than anticipated in the second standard deviation above the “expected return,” there were also a couple of years where “the bottom fell out” (2002 and 2008) and returns were below the second standard deviation. You may notice that there are 13 data points above the mean of 10%, and only 8 data points below the mean. The median (mid-point of all the data) is not the same as the average (the mean), and returns are “asymmetric” (not evenly distributed on both sides of the average). Knowing this data can help set more realistic expectations about an investment, portfolio, or asset allocation.
For investors to understand their true risk tolerance, they need to ask themselves the question: “Can I endure declines of 20% or more in a year and still stick to my plan?” If the answer is “no” (as I would expect it to be for many investors, especially retirees), then a more highly diversified portfolio and some downside protection strategies and tactics may be in order. Another very important thing to keep in mind is that these numbers, so far, are for annual calendar-year returns. In any given month, or calendar quarter, returns may be quite a bit higher or lower than discussed here. But that brings up a good point…time horizon. When it comes to variable investments, whether it’s real estate, stocks, variable annuities, commodities, etc., shorter-term volatility can be very unnerving. But looked at over longer periods of time, the highs and lows tend to balance each other out and an annual inspection of returns may even be too short a time frame, but it is a very common measuring period. As an example using the S&P 500 TR Index again, since 1/30/1973, the highest return over three months (data from Morningstar) was 26.61% (August of 1982-October of 1982) and the lowest 3-month return was -29.65% (September 2008-November 2008).6 The chart on the next page gives a good visual to the amount of volatility during a year. The dots below the horizontal line indicates maximum market declines during that calendar year. Notice that even in positive return years, there were drawdowns of a significant magnitude sometime during the year.
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Bloomberg: data in appendix.
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s an illustration of the “third and fourth standard deviation from the mean,” the highest and lowest (non-calendar) annual returns A for the S&P 500 TR since 1970 have been: +61.18% (July 1982-June 1983) and -43.32% (March 2008-February 2009).
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S&P 500® price return Index
Annual return of the S&P 500® The largest percentage loss in value within each calendar year
Stock market performance 35%
34% 31%
30%
27%
30% 27%
26%
26%
25%
23%
20% 15%
20%
20%
15%
14%
13% 11%
10%
9% 7%
5%
4% -7%
0%
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3%
2% -2%
-10% -13% -23%
-38%
0%
-1%
-3%
-5% -10%
13%
12%
-6% -6% -5% -8% -8%
-9%
-8%
-9%
-8% -11%
-7%
-6% -8% -10%
-12%
-15%
-7%
-10% -12%
-14% -16%
-17%
-20%
-19%
-20%
-19%
-25% -30%
-28%
-30%
-35%
-34%
-34%
-40% -45% -50%
2015
2 014
2013
201 2
2011
2 010
20 09
20 08
20 07
20 06
20 05
20 04
20 03
20 02
20 01
2000
1999
1998
19 97
199 6
1995
1994
19 93
19 92
19 91
199 0
1989
198 8
19 87
198 6
-49%
The Standard and Poors 500® (S&P 500) Price Return Index is a standard tool to measure stock market performance. The S&P 500® has experienced positive returns in 23 of the past 30 years; during that period, intra-year market downturns averaged -14.2% Sources: Standard and Poors, RiverSource Annuity Product Management. Returns are based on price index only and do not include dividends. Intra-year downturn refers to the largest market drop between two dates within each calendar year. For illustrative purposes only. Data as of 12/31/15. Past performance is not a guarantee of future results.
Notice the “Black Monday” year of 1987. After the initial fall in October of 1987, before the market headed up, the total loss had reached -34%. However, by year end, the market was in positive territory. It may also be worth noting that during the really strong years (1995-1999, 2003-2007, and 2009-2014) that there were fairly significant drawdowns at various points during those years, but the total calendar year returns were rather handsome, in most cases. In short: the stock market will be volatile, sometimes dizzyingly so. And trying to second guess these short-duration “storms” can be a fool’s game, so even though you may decide to have some short-term tactics in place for some of your holdings, your overall strategy should most assuredly be longer-term focused. And, “long term” does not mean one year. Long-term, when it comes to stock market returns, should probably be a full market cycle, which may mean a 5-8 year time horizon, or longer. 7
Applying the math to a realistic portfolio Keep in mind that so far we’ve discussed the very high profile S&P 500 index. Most people will not own just the S&P or equivalent, so let’s examine a more realistic portfolio. For the sake of comparisons, we’ll consider a 50/50 portfolio that rebalances annually, that is: 50% S&P 500 TR (total return, so dividends are included)7 and 50% Barclays Aggregate government bond index.8 22.75%
15.75%
8.75%
1.75% 0% -5.25%
And here is the point: even though the return had been 14% less (at least during the time period chosen), the volatility was also about 30% less. The graphic above is a picture of what a 50/50 mix volatility tower would look like when the standard deviation number is rounded to 7%.
importantly, they don’t correlate to each other very well. This means that when stocks are doing well, this Treasury bond index usually is not, and vice versa. When one zigs, the other zags and that smoothes out the ride. This yin and yang is referred to as “negative correlation.” Some assets behave like each other (an example would be stocks and low-grade bonds). Correlations are measured along a continuum of “negatively correlated” (moves in the opposite direction) of -1 to “positively correlated” (moves in the same direction) of +1. A zero means the two investments being compared seem to bear no relationship to each other in their movements. Over the past 10 years, the correlation of the S&P 500 Index to the US Aggregate Bond Index is -0.2 which means they don’t move the same direction, but somewhat in opposite directions. However, when the S&P is compared to the High Yield Index (low-grade US bonds, or junk bonds), the number is 0.73 which means they generally move in the same direction.9 US Government bonds (Bloomberg Treasury Index10 from 12/21/2005-12/21/2015), when compared to the S&P is -.50. This is important because that means the price movement is quite strongly in the opposite direction. When one is advancing, the other is retreating. This can also reduce volatility of the overall portfolio. (Like most other investing statistics, correlations may change over time.)
Notice that the 50/50 mix of stocks and bonds had a much tighter range of returns. High returns were in the teens and low 20s, but lows were negative single digits (whereas stocks alone cratered to -37%). It is interesting to note that the S&P Total Return Index, which includes dividends, experienced a maximum calendar year return of +38% in 1995, and a -37% in 2008. There is another element at work here to understand why this works. The lower volatility of bonds is one factor. The standard deviation of the Barclay’s Aggregate Bond Treasury index is 4.15% compared to the S&P 500 Index volatility of 15%, and, very
S&P 500 TR (Total Return) Index performance from 12/29/1988 to 11/30/2015 • 10.11% average annual total return • 15% volatility (standard deviation) The 50/50 mix of stocks and bonds rebalanced annually during the same time period performed as follows: • 8.75% average annual total return • 7.19% volatility (standard deviation)
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S&P 500 Total Return Index: The S&P 500® is a basket of 500 stocks that are considered to be widely held. The S&P 500® index is weighted by market value (shares outstanding times share price), and its performance is thought to be representative of the stock market as a whole. The S&P 500® index was created in 1957 although it has been extrapolated backwards to several decades earlier for performance comparison purposes. This index provides a broad snapshot of the overall U.S. equity market. Over 70% of all U.S. equity value is tracked by the S&P 500®. Inclusion in the index is determined by Standard & Poor’s and is based upon their market size, liquidity, and sector. The total return index assumes the on-going reinvestment of dividends in the index.
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Barclays Capital U.S. Aggregate Index: The Barclays Capital U.S. Aggregate Index is an index comprised of approximately 6,000 publicly traded bonds including U.S. government, mortgage-backed, corporate and Yankee bonds with an average maturity of approximately 10 years. The index is weighted by the market value of the bonds included in the index. This index represents asset types which are subject to risk, including loss of principal.
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Ten year correlations: 12/21/2005 – 12/21/2015. Source: Bloomberg
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Bloomberg US Treasury Bond Index: The Bloomberg US Treasury Bond Index is a rules-based, market-value weighted index engineered to measure the performance and characteristics of fixed rate coupon U.S. Treasuries which have a maturity greater than 12 months. To be 8 included in the index a security must have a minimum par amount of 1,000MM. [BBGID BBG0042YWYD0]
Correlations for various asset classes Security S&P 500 Barclay’s Agg Bloomberg Treasury Bloomberg IG Corp
S&P 500
Barclay’s Aggregate
Bloomberg Treasury
Bloomberg IG Corp11
100% -20% -50% -29%
-20% 100% 96% 95%
-50% 96% 100% 88%
-29% 95% 88% 100%
The table above demonstrates that when compared to the stock market (S&P 500), treasuries are the most negatively correlated (at-50%, or -.5), followed by corporate bonds (-29%, or -.29), and then the Barclay’s Capital Aggregate index. SOURCE: Bloomberg 10-year period correlations from 12/21/2005 - 12/21/2015.
Applying behavioral finance to investment correlation From a portfolio construction standpoint, this makes a lot of sense since it can reduce volatility even more than an asset that is neutral in correlation. However, from an investor behavioral standpoint, this can also be very difficult to manage. Investors, generally speaking, want to rid themselves of assets that are not currently performing well and load up on assets that are. The obvious problem with this is that you end up taking on more volatility. This may result in under diversifying a portfolio, and that can result in greater gains if momentum is upward, but it can also mean bigger losses if the market goes the other way.
Patience is a difficult behavior, especially in light of the two great human emotions that can rock a market: fear and greed. So, here is an issue to discuss when talking about your well-diversified and negatively-correlated portfolio with your financial advisor: it means there will almost undoubtedly be some asset (or assets) in your portfolio you don’t like at the moment. In other words, even though your overall portfolio may be fine and the volatility is under control, there may be something you don’t like at the moment. But that’s OK…and to be expected. The point is, it may actually be what may make the most sense. Think of it like you might think of insurance. It may not be making you money now, but if you need it, you’ll be glad you have it. If everything is making money at the moment, it may be time to re-assess your risk. Rebalancing or re-allocating may be in order. Possibly remove some risk, that is, take some money off the table while profits are to be had. 11
Black swans One final comment about correlations, and returns: Occasionally there may be an event that is so extraordinary that even the normal diversification does not accomplish what is expected. The financial crisis of 2008-2009 was one of those events. Many assets that were not positively correlated all went down together (e.g. stocks, corporate bonds, commodities, real estate). Only the safest assets (US Government bonds, for example) and the common disaster hedge, gold, went up in value. And that is the value of negative correlation. These rare, but very significant, events have taken on the name of “Black Swan” events. The reason for the name, by the way, is that the Western world believed all swans were white (in an investment context: all possible events are taken into consideration) because that is all that was known. There were no black swans that anyone knew of. It couldn’t happen. Then in 1697, a Dutch explorer discovered the first black swans in Australia. This “disruption of what was possible or known” has now become known as a black swan event. In the investment world, it may be a totally unanticipated event that sends markets reeling. The collapse in 2008 is an example, and correlations didn’t hold up as many (but not all) assets moved in the same direction: down. And this issue brings up one other asset type not yet mentioned, and it is not correlated to either stocks or bonds, and that is cash. It has been said, “cash is king.” And other times, it is said that “cash is trash.” The truth may lie in the middle. Cash is probably a very good parking place for a shorter time frame, depending on many factors, and it does lower volatility of the entire portfolio because it’s not correlated. And, it is probably a very smart way to deal with retirement cash flow needs. Although the subject of cash’s place in a portfolio, particularly a retirement portfolio, is a topic for another time, cash definitely does have its place.
Bloomberg US Corporate Bond Index: The Bloomberg US Corporate Bond Index is a rules-based market-value weighted index engineered to measure the investment-grade, fixed-rate, taxable, corporate bond market. It includes USD-denominated securities publicly issued by 9 U.S. and non-U.S. corporate issuers. To be included in the index a security must have a minimum par amount of 250MM.
A good financial advisor will always be checking about the potential volatility and dangers in your portfolio, and especially in retirement when you may not have time to recoup from another “black swan” event, should one occur. And, your tolerance for risk may change with the years as well. That’s why this topic should be discussed frequently. And by the way, we all want to participate in the market on the upside, but avoid it on the downside. Keep in mind that if someone had figured out exactly how to do that, he or she might own the world by now. There are other risk and return measurements (e.g. “alpha,” “ beta,” “ Sharpe ratio,” etc.). While we will not discuss these in any detail here, you may want to know some other terms and why they may be important to your portfolio construction. Brief definitions of some of them can be found in the appendix. How much risk do you need to take? This question can be answered by your financial advisor. You will need to know your financial goals to reach financial independence, and know the rate of return you need on your portfolio while you’re accumulating it, and while you’re distributing it in retirement, in order to become, and stay, financially secure. Once you know the rate of return you need, it can then be determined, at least from an historical perspective, what types of assets, or blend of assets, has been able to accomplish that type of return. Generally speaking, higher returns will demand higher risk taking and less diversification. More moderate return assumptions may make more sense (a less volatile or risky portfolio), but could you still achieve your goals? There will always be tradeoffs between safety and return, risk and reward. And do not assume that the phrase, “high risk means high return” has any semblance of truth. High risk means high risk, that is, a higher possibility of loss of principal, but this may also mean a higher possibility of higher returns, but remember the difference between “possibility” and “probability.” How much risk can you tolerate? The real crux of the matter is your risk tolerance. How much volatility do you need to take, and how much can you tolerate in order to accomplish your goals? To create open and candid communication with your advisor, you will probably want to develop a comprehensive investment policy statement (IPS). According to the Chartered Financial Analyst Institute, there are a couple of elements of an IPS that are germaine to our discussion here: (1) it should produce a common vocabulary for the advisor and client
to discuss risk and return; (2) it should result in a document of understanding that protects both the investor and advisor. In short, it is a written document that establishes a client’s objectives and limitations in the management of a portfolio. It should tell the financial advisor what the client’s risk and return expectations are, and what the advisor can and cannot do in seeking to achieve these objectives. For example, a client may not want a certain asset type in the portfolio for various reasons, and the advisor will need to take that into consideration. With this in mind, the discussion points need to encompass two broad themes: the road map of goal achievement (risk, return, portfolio construction), and the rule book for implementation (time horizon, rebalancing or re-allocating the portfolio, taxes, unique circumstances, legal issues, and liquidity needs). Here are the steps for the development of a successful investment policy statement: STEP 1: Regarding the discussion on risk, or volatility, the first step will be to determine an overall risk tolerance. From there, you will be able to get more specific with your advisor in terms of the actual standard deviation you can deal with in your portfolio. The tolerances are generally described as follows: Conservative: you are stating that you desire very low fluctuation in account values in exchange for a low return potential. Such a portfolio would most likely be mostly fixed investments, bond and certificate investments. Over long periods of time, historically, these very conservative portfolios have had a difficult time keeping pace with inflation. Moderately Conservative: you are willing to accept some fluctuation in account values in exchange for a below-average return potential. A portfolio in this space would most likely be more leaning toward fixed investments and bonds, but also have some lowervolatility equity holdings. Over long periods of time, portfolios in this category may do better than those that stayed very conservative. Moderate: you are willing to accept both an average fluctuation and average return. (A moderate portfolio would have a diversified blend of fixed and equity investments. The proverbial “50/50” portfolio would fit here, that is: 50% of various fixed investments such as bonds, certificates, cash and the like; and 50% of various equity holdings, such as stocks and real estate.) With the development of more non-correlated 10
assets and strategies, generally referred to as "alternative investments," there may be an opportunity to sprinkle in exposure by allocating some assets from either the fixed or equity side of the portfolio, or both, if suitable and appropriate. Alternative investments are not necessarily suitable for all investors. Moderately Aggressive: you are willing to accept relatively high volatility in your account values in exchange for a relatively high return potential. This portfolio would weigh heavily toward equity assets, such as stocks, real estate, commodities, etc. with a lesser allocation to fixed investments or bonds. Aggressive: you are willing to accept very high volatility in exchange for a possibility of high returns. A portfolio considered aggressive would likely be mostly invested in stocks, real estate, and may even employ borrowed money, or leverage, to enhance returns. It’s important to note that in considering your risk tolerance, take into account both your willingness and ability to take risks. As a quick example, you might be willing to take a risk on the stock of a company that has just gone public (your willingness is high), but you may not be able to tolerate the high volatility that comes with it, or too large of such a position may jeopardize your portfolio (your ability is low). There can be a fine line between a prudent investment and speculation. STEP 2: Referring back to page 5, ask your advisor to supply you with your portfolio performance on as long-term a history as possible (remember that short-term data will generally be less reliable than long-term data). You’ll need the long-term average annual total return. And, ask to have what the long-term expected return should be. (The reason this is important is that, as an example, even though the long-term return for the S&P 500 Index is about 10% per year average, there have been times it has been well under that. From 2000 to 2010, (12/31/1999 to 12/31/2009) it was actually negative for that 10-year period (Morningstar data). Your advisor should be able to provide you with an actual or estimate of the annual standard deviation of your portfolio (even if you’ve changed investments). Although past performance is no guarantee of future results, you can build a volatility bar (as seen on page 5) for your own portfolio. Then the questions to think about and discuss with your advisor may be: is this portfolio volatility something you are comfortable with? Can you tolerate the volatility illustrated? Do you need to accept that volatility in order to achieve your goals? Do you need to take more risk, or less?
STEP 3: Assuming you are comfortable with the volatility of your portfolio, there still remains at least one more significant discussion point: how should the portfolio be adjusted on a forward basis? In other words, do you need to “re-balance” between stocks and bonds, and how often? Maybe you need to “re-allocate” instead (take on more or less risk). When do you want to take some money “off the table.” In other words, how do you decide when to take profits or book losses? Maybe your decision to sell some assets will be based on time horizon and goals; maybe it will be based on market valuations (when price ratios may be high); maybe it will be a combination. However, it is a very important discussion point since, for most investors, portfolios eventually are turned into income, so planning out cash flows and how to fund those needs is of utmost importance. Investor Takeaway: Much of investing success has to do with proper diversification and having proper expectations. Many investors get into trouble when markets become volatile, which they will do from time to time. Knowing this ahead of time, and knowing the likely range of returns you may expect to see, can go a long way in helping you remain calm for the long haul so your returns are not jeopardized by making emotionally-based moves that you may regret later. Knowing what return on investment you need to be successful in your financial planning is important, but knowing the volatility, or risk, you need to take on can be critical since investor behavior can have a bigger impact on results than even investment performance. Knowing and understanding the risks you may need to take, and what you are comfortable with, is a most important conversation to have with your financial advisor. One of the most common measurements of volatility is standard deviation, and knowing how much your portfolio may fluctuate from the “expected long-term return” is the linchpin of the conversation. And the capstone of that conversation should be a philosophy or strategy as to how and when to take some gains to convert to income for the cash flow needs you may desire in retirement.
11
Post script: “regression to the mean” One truism that seems to occur, but on an irregular basis, is that returns regress to the mean over time, meaning that returns that are higher than the average are inevitably followed, at some point, by some returns that are below average, and vice versa. Two examples would be what happened to the S&P 500 in the mid-1990s through the turn of the century, and then the recent experience of the stock market since the recession of 2008. The average return for the S&P 500 TR (Total Return Index) is about 10% per year (long term). The annual returns for calendar years 1995-1999 were 38%, 23%, 33%, 29%, and 21% (way above the average)12 and were followed by -9%, -12% and -22% in years 2000-2002. The negative 37% that was experienced in 2008 was followed by +26%, 15%, 2%, 16%, 32% and 14% (all but one of those positive years was above the average). The point being that through the years, your portfolio will experience the ups and downs on the way to an average. And as stated previously, you (most likely) will not have all of your money in stocks so your “range of returns” should be much tighter and less volatile than the S&P 500 Index being discussed here.
Although it applies to all investors, when you are near or in retirement, you may want to have as part of your investment policy statement, a philosophy and strategy as to when to take some profits off the table and turn those gains into cash flow. One possible idea to discuss with your advisor would be to consider taking some profits when the price/earnings (P/E) ratio of the market gets to the high side of its historical range.13 Chances are, those same markets may perform at less than average in the near future to return to closer the historical mean so you may want to book some profits…while they are there. From an income tax perspective, that is taking a “unrealized gain” (not currently taxable) and turning it into a “realized gain” (taxable). However, long-term capital gains do presently get a preferential treatment of 0% (for those in the 10% and 15% brackets), 15% (for those above the 15% bracket), or 20% (for those in the highest tax bracket). In any case, understand that the volatility you set up in your portfolio will probably happen at some point, and you need to have a plan on how to deal with that eventuality. Of course, past performance is no guarantee of future results, but it’s best to have a plan.
12
The returns in this example vary slightly from the chart on page 9 because the TR Index (Total Return) includes dividends, whereas the chart is the “price-only” index, not including dividends.
13
The reason the word “some” is used is prudence. The market can surprise sometimes and stay above the mean P/E ratio for an extended period of time. Consider the taking of profits as “selective pruning” versus wholesale “cutting and running.”
12
Appendix The following three graphics chart the S&P 500 Index, then the Barclay’s Capital Aggregate Index, and then a 50/50 mix of both indexes. This graphic is of annual returns (calendar year) of the S&P 500 Total Return (TR) Index.
—
S&P 500 Stock Market Index
40 30 20 10 0 -10 -20 -30
2015
2 014
2013
201 2
2011
2 010
20 09
20 08
20 07
20 06
20 05
20 04
20 03
20 02
20 01
2000
1999
1998
19 97
199 6
1995
1994
19 93
19 92
19 91
199 0
-40
Source: Chart created by Ameriprise based on data from 2015. Standard and Poor's, Barclay's Capital (formerly Lehman Brothers Aggregate Bond Index). Combined returns based on calculation of 50% of S&P 500 return, 50% of Barclays Capital Aggregate Bond Index return. Past performance does not guarantee future results. It is not possible to invest in an index. These examples do not reflect sales charges, taxes or other costs associated with investing.
13
Looking at the S&P 500 Index (total return) since 1990, it’s easy to spot significant volatility. One year, the calendar year return was +38% (1995), and in another year, the return was -37% (2008). Examining the next chart which shows the Barclay’s Capital Aggregate Bond Index (this index includes both government and corporate bonds), you can see very little volatility compared to the stock index. However, with the low volatility came modest returns in many years. This graphic is of annual returns (calendar year) of the Barclay’s Capital Aggregate (bond) Index.
—
Barclays Capital Aggregate Bond Index
40 30 20 10 0 -10 -20 -30
2015
2 014
2013
201 2
2011
2 010
20 09
20 08
20 07
20 06
20 05
20 04
20 03
20 02
20 01
2000
1999
1998
19 97
199 6
1995
1994
19 93
19 92
19 91
199 0
-40
Source: Chart created by Ameriprise based on data from 2015. Standard and Poor's, Barclay's Capital (formerly Lehman Brothers Aggregate Bond Index). Combined returns based on calculation of 50% of S&P 500 return, 50% of Barclays Capital Aggregate Bond Index return. Past performance does not guarantee future results. It is not possible to invest in an index. These examples do not reflect sales charges, taxes or other costs associated with investing.
14
In contrast to the S&P (TR) Index, bonds have a more reliable return, but there still are years it has dipped into negative territory. This graphic is of annual returns (calendar year) of a 50/50 mix of stocks and bonds, represented by the S&P 500 TR Index and the Barclay’s Capital Aggregate (bond) Index.
—
50/50 Mix
40 30 20 10 0 -10 -20 -30
2015
2 014
2013
201 2
2011
2 010
20 09
20 08
20 07
20 06
20 05
20 04
20 03
20 02
20 01
2000
1999
1998
19 97
199 6
1995
1994
19 93
19 92
19 91
199 0
-40
Source: Chart created by Ameriprise based on data from 2015. Standard and Poor's, Barclay's Capital (formerly Lehman Brothers Aggregate Bond Index). Combined returns based on calculation of 50% of S&P 500 return, 50% of Barclays Capital Aggregate Bond Index return. Past performance does not guarantee future results. It is not possible to invest in an index. These examples do not reflect sales charges, taxes or other costs associated with investing.
15
S&P 500 TR Index (Total Return) annual (calendar year) returns including dividends Yearly S&P 500 Total Return Index
Here is the formula for calculating standard deviation.
Date
Closing level
12/30/1988
288.116
S=
12/29/1989
379.409
32%
12/31/1990
367.6313
-3%
12/31/1991
479.6332
30%
12/31/1992
516.1779
8%
12/31/1993
568.2021
10%
12/30/1994
575.7049
1%
12/29/1995
792.0419
38%
12/31/1996
973.8967
23%
12/31/1997
1298.821
33%
12/31/1998
1670.006
29%
12/31/1999
2021.401
21%
12/29/2000
1837.365
9%
12/31/2001
1618.979
-12%
12/31/2002
1261.176
-22%
12/31/2003
1622.939
29%
12/31/2004
1799.548
11%
12/30/2005
1887.941
5%
12/29/2006
2186.127
16%
12/31/2007
2306.232
5%
12/31/2008
1452.976
-37%
12/31/2009
1837.5
26%
12/31/2010
2114.29
15%
12/30/2011
2158.94
2%
12/31/2012
2504.44
16%
12/31/2013
3315.59
32%
12/31/2014
3769.44
14%
12/31/2015
3821.6
1%
% change
(SOURCE: Bloomberg, Ameriprise Financial Services, Inc. Note: The S&P 500 TR (Total Return) index is a different index than the more common S&P 500 Index)
∑ (X - X)2 N
Where S = the standard deviation of a sample, ∑ means “sum of”, X = each value in the data set X = mean of all values in the data set, N = number of values in the data set.
Other terms you may want to know for discussions with your advisor: Sharpe ratio: attributed to Nobel Prize winner in economics, William Sharpe, this calculation takes the return of an investment (actually it’s the excess return over the “safe” rate of T-bills) and divides it by the standard deviation, or volatility. The result is a number that measures the amount of reward experienced per unit of risk. Its meaning can be seen when you compare two or more investments and see how the ratios compare. The higher the number, the more return was achieved for the risk assumed. Beta: measures the degree of change in value one can expect in a portfolio given a change in value in a benchmark index. A beta value of more than one indicates the portfolio or investment is more volatile than the index, and a number less than one means it is less volatile. The value to the investor will be in understanding how much volatility he or she is taking on with any particular investment. For example, any single stock in the S&P 500 may have a volatility, or beta, that is much higher than the index itself (various performances of different stocks and sectors in the S&P tend to balance each other out to some degree and bring the volatility of the whole index down). We’ve already discussed that the volatility of the S&P is about 15. If an individual stock has a beta of 1.6, that means the volatility range during the measuring period was 60% higher than the index, or the standard deviation of that stock was 24 (15 X 1.6). Alpha: is derived from the actual performance of an investment when compared to its expected performance (its beta). Alpha is often seen as a measurement of value added or subtracted by a portfolio’s manager. As a quick example, if the beta of a mutual fund is 1.1, (in other words, 10% more volatile than the index) it means that the expected performance of the fund would be 10% more volatile than the index it’s being compared to. If the fund is up more than 10% 16
above the index in an up market (or down less than minus 10% in a falling market), the manager earns himself or herself a “positive” alpha number. Although this is what an investor would generally like to see, remember that short-term positive alpha numbers do not mean this can continue. Past performance is no guarantee of future results. It only shows what HAS happened and not what WILL happen. R-squared: reflects the percentage of a portfolio’s movements that can be attributed to movements in its underlying benchmark or index. As an easy example, a large US stock blend mutual fund will most likely be benchmarked to the S&P 500 index. If it is constructed to be very close to the index, the R-squared measurement will most likely be close to the number 100. If the fund does not look like or move like the index, the number will move away from (below) the number 100. It basically is a measurement of correlation in that a high R-squared investment is expected to move like its underlying index. The definitions (above) are derived from Morningstar definitions, with some editing for clarification. VIX: The Chicago Board of Options Exchange (CBOE) introduced the Volatility Index (VIX) in 1993. It shows the market expectation of 30-day volatility. The VIX is a widely-watched measure of shorter-term market risk and is sometimes referred to as “the investor fear gauge.” VIX values greater than 30 are generally associated with high volatility whereas values below 20, volatility is assumed to be fairly low.
“The current value of the standard deviation can be used to estimate the importance of a move or set expectations. This assumes that price changes are normally distributed with a classic bell curve. Even though price changes for securities are not always normally distributed, chartists can still use normal distribution guidelines to gauge the significance of a price movement. In a normal distribution, 68% of the observations fall within one standard deviation. 95% of the observations fall within two standard deviations. 99.7% of the observations fall within three standard deviations.” FROM THE DEFINITION OF STANDARD DEVIATION, SOURCED FROM THE WEBSITE STOCKCHARTS.COM
The VIX is probably best used and viewed in the shorter-term environment, such as the pricing of options strategies but may not be a good gauge for longer-term investors. However, it can help give an explanation to shorter-term market swings. And, if an investor is searching for buying opportunities, a high VIX environment may provide some price swings that he or she may want to take advantage of.
Investment products are not federally or FDIC-insured, are not deposits or obligations of, or guaranteed by any financial institution and involve investment risks including possible loss of principal and fluctuation in value. Diversification does not assure a profit or protect against loss. Ameriprise Financial, Inc. and its affiliates do not offer tax or legal advice. Consumers should consult with their tax advisor or attorney regarding their specific situation. Ameriprise Financial Services, Inc. Member FINRA and SIPC. © 2016 Ameriprise Financial, Inc. All rights reserved.
16-001 (6/16)
Abstract All investors need to know what the various types of risks there are in the marketplace, how much risk they are willing to accept, and how much they may need to consider in order to achieve their goals. There are three principles to building a sound retirement portfolio — downside protection; income generation; and growth or inflation protection. These competing priorities need to be balanced to lower risk, pay income, and provide future income needs through growth of principal. In a recent study nearly 70% of retirees said “downside protection” was one of the top priorities for their portfolio in retirement.1 For more information regarding the importance of volatility management and “sequence of returns” risk, read the research paper entitled, “Volatility and Sustainable Withdrawals” also by Craig Brimhall and available from your Ameriprise advisor. Knowing and understanding the risks you may need to take, and what you are comfortable with, is a most important conversation to have with your financial advisor. One of the most common measurements of volatility is standard deviation, and knowing how much your portfolio may fluctuate from the “expected long-term return” is the linchpin of the conversation you may need to have.
1
2014 Retiree Insights Study, The Diversified Services Group, Inc.
1
Risk... What is it? Risk is the potential of losing something of value. Various dictionaries define it in similar terms. However, they do not necessarily deal with the issue of the probability of a risk happening, just the possibility. For this paper, we will be dealing with probabilities, and discussing risk in terms of the market value of your investments. And, that market value fluctuation can be expressed by another word: volatility. Even though volatility is defined as variance from the mean (or average), it is generally recognized that investors don’t have a problem with returns that are above the average, but they do have issues when returns are below the mean; particularly when returns are negative. Of course, managing to rein in negative returns may also mean lowering the potential returns to some degree as well. There are always tradeoffs. Mitigating volatility From a strategic standpoint, one of the main ways to reduce volatility is with a highly diversified portfolio. Investing in a diverse mix of the traditional asset class of stocks, bonds and cash and possibly adding some non-traditional investments as well (also referred to as "alternatives") may enhance the risk diversification of your portfolio. Remember that the main goal of diversification is not to increase return (although it might in some circumstances) but to try to reduce risk. Once you move past the strategies of diversification by asset type and product selection for your portfolio, you could also discuss with your advisor the tactical ideas around downside protection. Although many who have become wealthy have done so by under diversifying (having a concentrated position in a stock, a business, or other investment for example), it may be wise, at some point, to decide to take some profit and diversify away from what has made them wealthy. After all, if the driver of their wealth decides to take the big fall, wealth can evaporate. “Rags-to-richesand-back-to-rags” stories are plentiful. Measuring risk or volatility All investments that vary in value over time can have that volatility measured. Standard deviation is the statistical measure of the volatility of a portfolio’s returns. The calculation is fairly straightforward, and it is very important for all investors to understand the
volatility in their portfolios. Here is the heart of the matter: how much volatility is appropriate for your portfolio in order to accomplish your goals, and how much volatility are you comfortable with? What your portfolio may need, in terms of return, and how much volatility you are comfortable with are not necessarily going to coincide. For those familiar with statistics, you already know about “the bell curve” picture of a standard deviation example. It is shown below. Additional information regarding calculations of standard deviation can be found in the appendix. However, since standard deviations for investments are published, we’ll spend the time here with a shortcut on how to interpret what is being said and how it may affect you and your portfolio. A typical standard deviation “bell curve”
34%
34%
13.5% -3x
-2x
13.5%
-1x
1x
2x
3x
99.5% Standard deviation is, simply stated, the measurement of variance from a mean (an average). In the graphic shown above, the vertical line in the middle is the average or mean. It indicates that in a “normal distribution” of a series of numbers, there will be observations to the right of that line (returns higher than the average) and an equal number of observations to the left (returns lower than the average). You need this collection of numbers to come up with an average. And, “normal” distributions are not necessarily common (especially in measuring investment returns) and there may be more returns to right or left…in other words, the returns may not be symmetrical. Notice that in a normal distribution, basically two-thirds of observations (34% + 34% = 68% in the graphic) occur in what is called “one standard deviation.”
2
Two standard deviations will also include observations to the left and right that account for another 27% (13.5% + 13.5% = 27%). Basically, if you include all observations that fall within two deviations, it accounts for 95% of all possibilities. As you can see from the graphic, if you step out three deviations, we can account for 99.5% of possibilities. But, most of the data points occur much closer to average, or within one standard deviation. Some things that get measured, such as portfolio returns or temperatures, have either significant volatility, very low volatility, or somewhere in between. Let’s look at average temperatures in a couple of cities in the US to clarify the point. The weather station may tell you what the average is for the day, but chances are, it’s not the average where you are right now. It’s warmer or colder than the average for this day on the calendar, most likely.
It is always possible for an observation to occur out past two standard deviations (there is a 5% possibility this will occur), but it is more probable that returns, or observations, will occur much closer to “the average.” 68% of the time it should be within one deviation. And once you average these temperatures over time, you end up with an “average” or a “mean.” But that can be deceptive, since an average tells you nothing about the variance. An interesting example might be San Diego, CA vs. Nashville, TN. These two cities have the same average high temperature and that happens to be just a fraction under 70 degrees Fahrenheit. But the average
2
maximum temperatures by month in San Diego run from 65 – 76 degrees, depending on the month…a very small span of 11 degrees.2 Nashville’s average monthly high temps range from 47 – 89 degrees…a very high spread of 42 degrees. And yet both cities have had the same average high temperature for the year. This concept holds true in most cases: the averages of items you compare may seem close, but they may be deceptively dissimilar in that the variances may be wildly different. For the sake of trying to clarify the volatility illustration, and assist you in building your own volatility model, let’s now take the standard deviation bell curve and turn it 90 degrees and stand it on end. Simply put, we’ll create a bar graphic with the average return in the middle horizontal line and more positive returns plotted above that mean, and lower returns listed below the mean (see pg. 5-6). Just like temperatures vary over time, so do investment stock returns. Common measuring periods are one year, 3-year, 5-year 10-year, 20-year, and since records began. You will generally notice that whereas there may be a fair amount of difference in the numbers if you look at just one year versus 10 years, once you get a large number of data points, the differences in the volatility number (or returns if we’re discussing the stock market) has a tendency to compress, and therefore we would say they become more reliable or predictable. However, keep in mind that no one can predict the market’s return, and the numbers are simply a look back at what has happened and not what will happen. There are two main numbers to keep in mind in this discussion: “expected return” and “annual standard deviation.” The “return” number is fairly straightforward: it's the total return (capital appreciation and income) on an average annual return basis, but usually realized only over extended periods of time (multiple years). The “standard deviation” number is the volatility you will most likely see, as an annual measurement, on that portfolio as you seek to achieve the “expected return.”
NOAA’s national climatic data center, dates 1981-2010; data from website www.currentresults.com
3
But this is where it gets a bit tricky. The standard deviation number, although usually expressed as an annual number, actually changes as you measure it over a multiple year (rolling) basis. This is sometimes referred to as “time-weighted” volatility. In other words, the positive years tend to somewhat cancel out the negative years, and the “range of returns” begins to compress over time, as bad years counterbalance good years, and vice versa.
It may best be seen in a graphic. The chart below is from JP Morgan Asset Management, and shows the range of returns for stocks, bonds, and a 50/50 mix. You will notice at least one significant thing. The range of possible outcomes for a 1-year hold is wildly unpredictable, but once you step out even five years, the range of outcomes compresses significantly.
Range of stock, bond and blended total returns Annual total returns, 1950 to 2015 50%
Investing principles
40%
47%
43%
30%
33%
20%
28% 23% 21%
19%
10%
16%
16%
1%
2%
12%
14%
7%
0%
-8%
-10%
-3%
-2%
1%
-1%
-15%
-39%
-40%
1%
5%
Annual average total return
Growth of $100,000 over 20 years
Stocks
11.1%
$819,296
Bonds
6.0%
$321,853
50/50 portfolio 8.9%
$555,099
-20% -30%
17%
-50% 1-year
5-year rolling
10-year rolling
20-year rolling
Source: Barclays, FactSet, Federal Reserve, Robert Shiller, Strategas/Ibbotson, J.P. Morgan Asset Management. Returns shown are based on calendar year returns from 1950 to 2015. Stocks represent the S&P 500® Shiller Composite and Bonds represent Strategas/Ibbotson for periods from 1950 to 1980 and Barclays Aggregate after index inception in 1980. Growth of $100,000 is based on annual average total returns from 1950 to 2015. Guide to the Markets — U.S. Data are as of March 31, 2016.
4
During the 20 years ending 12/31/2015, the S&P 500®3 Index saw returns that went from +47% in one calendar year, to -39%, or an 86 percentage point swing. But over a 5-year rolling basis, the numbers compressed to an average annual return of +28% to -3%. The point is this: if you’re investing and not speculating, more volatile investments need to be viewed with a long-term lens to allow the unpredictability of the short term swings to work themselves out and eventually smooth out the ride. Using the current data from Morningstar and Ibbotson, the annual standard deviation of the S&P 500 Index is about 15 on a long-period measurement (10 years). This number has moved around some over time, but the long-term average (depending on the time frames studied) is in the vicinity of 13-18%, so we’ll use 15% for this discussion. The long-term return for the S&P 500 can be a bit trickier to pin down, since it obviously depends on the “start” and “stop” dates when you examine data. However, from 1926 thru 12/31/2015, the average annual return of the S&P 500 index has been 10.0%, (Source: Morningstar Direct data). I’d like to emphasize: you will be able to do the same exercise with your own portfolio. In the example below, we will walk through the S&P 500 Index annual (calendar year) returns: Step 1:
Step 2:
Step 3:
40%
10%
25%
25%
10%
10%
-5%
-5%
Step 1: With the aid of your financial advisor, or your own research, put the “expected return” at the middle line. This “expected return” should be a long-term realistic number. For the S&P 500 Index, that number has been about 10%. The volatility number (standard deviation) for the S&P has been about 15% long term3. One standard deviation is where returns are anticipated to fall two-thirds of the time. Step 2: Add the standard deviation number once to the expected return; and then subtract the standard deviation number from the expected return, as shown. So, in 10 years, the S&P annual return may fall between +25% (10% expected return plus 15% standard deviation) and -5% (10% expected return minus 15% standard deviation). Since this still leaves a lot of returns that fall outside of this range, it may be wise to calculate out TWO standard deviations and that should include returns that have occurred 95% of the time. Step 3: Add another standard deviation number to the top return, and subtract the deviation number from the bottom return, as shown. Therefore, returns are expected to fall between +40% (10% return plus 15%, plus 15%) and -20% (10% return minus 15% minus 15%). So, to repeat, 95% of the time, the S&P 500 Index returns are expected to range between +40% and -20%. If things happen as expected, then 2½% of the time returns may exceed 40%, and 2½% of the time returns may fall below -20%. Incidentally, over the past 20 years, there have been two years when the S&P 500 Total Return has had a calendar year return of less than -20%: -22% in 2002 and -37% in 2008.
0%
-20%
3
S&P 500 Price Index: The S&P 500® is a basket of 500 stocks that are considered to be widely held. The S&P 500® index is weighted by market value (shares outstanding times share price), and its performance is thought to be representative of the stock market as a whole. The S&P 500® index was created in 1957 although it has been extrapolated backwards to several decades earlier for performance comparison purposes. This index provides a broad snapshot of the overall U.S. equity market. Over 70% of all U.S. equity value is tracked by the S&P 500®. Inclusion in the index is determined by Standard & Poor’s and is based upon their market size, liquidity, and sector. The S&P500 price index reflects only the price return, absent the distribution of dividends.
4
Data for 10 years ending 09/30/2015; Source: FactSet and Morningstar.
5
Here are the actual returns of the S&P 500 Index total return (dividends included) plotted from the beginning of 1995 through the end of 20155: 40%
25%
10% 0% -5% -20%
Source: Bloomberg as of 12/31/2015. Information provided by third parties is deemed to be reliable but may be derived using methodologies or techniques that are proprietary or specific to the third-party source. Indices shown are unmanaged and do not reflect the impact of fees. It is not possible to invest directly in an index.
Some observations: of the 21 calendar year returns plotted on the graph, fewer than two-thirds of the returns ended up as expected, that is, within one standard deviation. Eleven of the 21 data points ended up between -5% and 25%, or ~50% of the time. Although there were more returns than anticipated in the second standard deviation above the “expected return,” there were also a couple of years where “the bottom fell out” (2002 and 2008) and returns were below the second standard deviation. You may notice that there are 13 data points above the mean of 10%, and only 8 data points below the mean. The median (mid-point of all the data) is not the same as the average (the mean), and returns are “asymmetric” (not evenly distributed on both sides of the average). Knowing this data can help set more realistic expectations about an investment, portfolio, or asset allocation.
For investors to understand their true risk tolerance, they need to ask themselves the question: “Can I endure declines of 20% or more in a year and still stick to my plan?” If the answer is “no” (as I would expect it to be for many investors, especially retirees), then a more highly diversified portfolio and some downside protection strategies and tactics may be in order. Another very important thing to keep in mind is that these numbers, so far, are for annual calendar-year returns. In any given month, or calendar quarter, returns may be quite a bit higher or lower than discussed here. But that brings up a good point…time horizon. When it comes to variable investments, whether it’s real estate, stocks, variable annuities, commodities, etc., shorter-term volatility can be very unnerving. But looked at over longer periods of time, the highs and lows tend to balance each other out and an annual inspection of returns may even be too short a time frame, but it is a very common measuring period. As an example using the S&P 500 TR Index again, since 1/30/1973, the highest return over three months (data from Morningstar) was 26.61% (August of 1982-October of 1982) and the lowest 3-month return was -29.65% (September 2008-November 2008).6 The chart on the next page gives a good visual to the amount of volatility during a year. The dots below the horizontal line indicates maximum market declines during that calendar year. Notice that even in positive return years, there were drawdowns of a significant magnitude sometime during the year.
5
Bloomberg: data in appendix.
6
s an illustration of the “third and fourth standard deviation from the mean,” the highest and lowest (non-calendar) annual returns A for the S&P 500 TR since 1970 have been: +61.18% (July 1982-June 1983) and -43.32% (March 2008-February 2009).
6
S&P 500® price return Index
Annual return of the S&P 500® The largest percentage loss in value within each calendar year
Stock market performance 35%
34% 31%
30%
27%
30% 27%
26%
26%
25%
23%
20% 15%
20%
20%
15%
14%
13% 11%
10%
9% 7%
5%
4% -7%
0%
4%
3%
2% -2%
-10% -13% -23%
-38%
0%
-1%
-3%
-5% -10%
13%
12%
-6% -6% -5% -8% -8%
-9%
-8%
-9%
-8% -11%
-7%
-6% -8% -10%
-12%
-15%
-7%
-10% -12%
-14% -16%
-17%
-20%
-19%
-20%
-19%
-25% -30%
-28%
-30%
-35%
-34%
-34%
-40% -45% -50%
2015
2 014
2013
201 2
2011
2 010
20 09
20 08
20 07
20 06
20 05
20 04
20 03
20 02
20 01
2000
1999
1998
19 97
199 6
1995
1994
19 93
19 92
19 91
199 0
1989
198 8
19 87
198 6
-49%
The Standard and Poors 500® (S&P 500) Price Return Index is a standard tool to measure stock market performance. The S&P 500® has experienced positive returns in 23 of the past 30 years; during that period, intra-year market downturns averaged -14.2% Sources: Standard and Poors, RiverSource Annuity Product Management. Returns are based on price index only and do not include dividends. Intra-year downturn refers to the largest market drop between two dates within each calendar year. For illustrative purposes only. Data as of 12/31/15. Past performance is not a guarantee of future results.
Notice the “Black Monday” year of 1987. After the initial fall in October of 1987, before the market headed up, the total loss had reached -34%. However, by year end, the market was in positive territory. It may also be worth noting that during the really strong years (1995-1999, 2003-2007, and 2009-2014) that there were fairly significant drawdowns at various points during those years, but the total calendar year returns were rather handsome, in most cases. In short: the stock market will be volatile, sometimes dizzyingly so. And trying to second guess these short-duration “storms” can be a fool’s game, so even though you may decide to have some short-term tactics in place for some of your holdings, your overall strategy should most assuredly be longer-term focused. And, “long term” does not mean one year. Long-term, when it comes to stock market returns, should probably be a full market cycle, which may mean a 5-8 year time horizon, or longer. 7
Applying the math to a realistic portfolio Keep in mind that so far we’ve discussed the very high profile S&P 500 index. Most people will not own just the S&P or equivalent, so let’s examine a more realistic portfolio. For the sake of comparisons, we’ll consider a 50/50 portfolio that rebalances annually, that is: 50% S&P 500 TR (total return, so dividends are included)7 and 50% Barclays Aggregate government bond index.8 22.75%
15.75%
8.75%
1.75% 0% -5.25%
And here is the point: even though the return had been 14% less (at least during the time period chosen), the volatility was also about 30% less. The graphic above is a picture of what a 50/50 mix volatility tower would look like when the standard deviation number is rounded to 7%.
importantly, they don’t correlate to each other very well. This means that when stocks are doing well, this Treasury bond index usually is not, and vice versa. When one zigs, the other zags and that smoothes out the ride. This yin and yang is referred to as “negative correlation.” Some assets behave like each other (an example would be stocks and low-grade bonds). Correlations are measured along a continuum of “negatively correlated” (moves in the opposite direction) of -1 to “positively correlated” (moves in the same direction) of +1. A zero means the two investments being compared seem to bear no relationship to each other in their movements. Over the past 10 years, the correlation of the S&P 500 Index to the US Aggregate Bond Index is -0.2 which means they don’t move the same direction, but somewhat in opposite directions. However, when the S&P is compared to the High Yield Index (low-grade US bonds, or junk bonds), the number is 0.73 which means they generally move in the same direction.9 US Government bonds (Bloomberg Treasury Index10 from 12/21/2005-12/21/2015), when compared to the S&P is -.50. This is important because that means the price movement is quite strongly in the opposite direction. When one is advancing, the other is retreating. This can also reduce volatility of the overall portfolio. (Like most other investing statistics, correlations may change over time.)
Notice that the 50/50 mix of stocks and bonds had a much tighter range of returns. High returns were in the teens and low 20s, but lows were negative single digits (whereas stocks alone cratered to -37%). It is interesting to note that the S&P Total Return Index, which includes dividends, experienced a maximum calendar year return of +38% in 1995, and a -37% in 2008. There is another element at work here to understand why this works. The lower volatility of bonds is one factor. The standard deviation of the Barclay’s Aggregate Bond Treasury index is 4.15% compared to the S&P 500 Index volatility of 15%, and, very
S&P 500 TR (Total Return) Index performance from 12/29/1988 to 11/30/2015 • 10.11% average annual total return • 15% volatility (standard deviation) The 50/50 mix of stocks and bonds rebalanced annually during the same time period performed as follows: • 8.75% average annual total return • 7.19% volatility (standard deviation)
7
S&P 500 Total Return Index: The S&P 500® is a basket of 500 stocks that are considered to be widely held. The S&P 500® index is weighted by market value (shares outstanding times share price), and its performance is thought to be representative of the stock market as a whole. The S&P 500® index was created in 1957 although it has been extrapolated backwards to several decades earlier for performance comparison purposes. This index provides a broad snapshot of the overall U.S. equity market. Over 70% of all U.S. equity value is tracked by the S&P 500®. Inclusion in the index is determined by Standard & Poor’s and is based upon their market size, liquidity, and sector. The total return index assumes the on-going reinvestment of dividends in the index.
8
Barclays Capital U.S. Aggregate Index: The Barclays Capital U.S. Aggregate Index is an index comprised of approximately 6,000 publicly traded bonds including U.S. government, mortgage-backed, corporate and Yankee bonds with an average maturity of approximately 10 years. The index is weighted by the market value of the bonds included in the index. This index represents asset types which are subject to risk, including loss of principal.
9
Ten year correlations: 12/21/2005 – 12/21/2015. Source: Bloomberg
10
Bloomberg US Treasury Bond Index: The Bloomberg US Treasury Bond Index is a rules-based, market-value weighted index engineered to measure the performance and characteristics of fixed rate coupon U.S. Treasuries which have a maturity greater than 12 months. To be 8 included in the index a security must have a minimum par amount of 1,000MM. [BBGID BBG0042YWYD0]
Correlations for various asset classes Security S&P 500 Barclay’s Agg Bloomberg Treasury Bloomberg IG Corp
S&P 500
Barclay’s Aggregate
Bloomberg Treasury
Bloomberg IG Corp11
100% -20% -50% -29%
-20% 100% 96% 95%
-50% 96% 100% 88%
-29% 95% 88% 100%
The table above demonstrates that when compared to the stock market (S&P 500), treasuries are the most negatively correlated (at-50%, or -.5), followed by corporate bonds (-29%, or -.29), and then the Barclay’s Capital Aggregate index. SOURCE: Bloomberg 10-year period correlations from 12/21/2005 - 12/21/2015.
Applying behavioral finance to investment correlation From a portfolio construction standpoint, this makes a lot of sense since it can reduce volatility even more than an asset that is neutral in correlation. However, from an investor behavioral standpoint, this can also be very difficult to manage. Investors, generally speaking, want to rid themselves of assets that are not currently performing well and load up on assets that are. The obvious problem with this is that you end up taking on more volatility. This may result in under diversifying a portfolio, and that can result in greater gains if momentum is upward, but it can also mean bigger losses if the market goes the other way.
Patience is a difficult behavior, especially in light of the two great human emotions that can rock a market: fear and greed. So, here is an issue to discuss when talking about your well-diversified and negatively-correlated portfolio with your financial advisor: it means there will almost undoubtedly be some asset (or assets) in your portfolio you don’t like at the moment. In other words, even though your overall portfolio may be fine and the volatility is under control, there may be something you don’t like at the moment. But that’s OK…and to be expected. The point is, it may actually be what may make the most sense. Think of it like you might think of insurance. It may not be making you money now, but if you need it, you’ll be glad you have it. If everything is making money at the moment, it may be time to re-assess your risk. Rebalancing or re-allocating may be in order. Possibly remove some risk, that is, take some money off the table while profits are to be had. 11
Black swans One final comment about correlations, and returns: Occasionally there may be an event that is so extraordinary that even the normal diversification does not accomplish what is expected. The financial crisis of 2008-2009 was one of those events. Many assets that were not positively correlated all went down together (e.g. stocks, corporate bonds, commodities, real estate). Only the safest assets (US Government bonds, for example) and the common disaster hedge, gold, went up in value. And that is the value of negative correlation. These rare, but very significant, events have taken on the name of “Black Swan” events. The reason for the name, by the way, is that the Western world believed all swans were white (in an investment context: all possible events are taken into consideration) because that is all that was known. There were no black swans that anyone knew of. It couldn’t happen. Then in 1697, a Dutch explorer discovered the first black swans in Australia. This “disruption of what was possible or known” has now become known as a black swan event. In the investment world, it may be a totally unanticipated event that sends markets reeling. The collapse in 2008 is an example, and correlations didn’t hold up as many (but not all) assets moved in the same direction: down. And this issue brings up one other asset type not yet mentioned, and it is not correlated to either stocks or bonds, and that is cash. It has been said, “cash is king.” And other times, it is said that “cash is trash.” The truth may lie in the middle. Cash is probably a very good parking place for a shorter time frame, depending on many factors, and it does lower volatility of the entire portfolio because it’s not correlated. And, it is probably a very smart way to deal with retirement cash flow needs. Although the subject of cash’s place in a portfolio, particularly a retirement portfolio, is a topic for another time, cash definitely does have its place.
Bloomberg US Corporate Bond Index: The Bloomberg US Corporate Bond Index is a rules-based market-value weighted index engineered to measure the investment-grade, fixed-rate, taxable, corporate bond market. It includes USD-denominated securities publicly issued by 9 U.S. and non-U.S. corporate issuers. To be included in the index a security must have a minimum par amount of 250MM.
A good financial advisor will always be checking about the potential volatility and dangers in your portfolio, and especially in retirement when you may not have time to recoup from another “black swan” event, should one occur. And, your tolerance for risk may change with the years as well. That’s why this topic should be discussed frequently. And by the way, we all want to participate in the market on the upside, but avoid it on the downside. Keep in mind that if someone had figured out exactly how to do that, he or she might own the world by now. There are other risk and return measurements (e.g. “alpha,” “ beta,” “ Sharpe ratio,” etc.). While we will not discuss these in any detail here, you may want to know some other terms and why they may be important to your portfolio construction. Brief definitions of some of them can be found in the appendix. How much risk do you need to take? This question can be answered by your financial advisor. You will need to know your financial goals to reach financial independence, and know the rate of return you need on your portfolio while you’re accumulating it, and while you’re distributing it in retirement, in order to become, and stay, financially secure. Once you know the rate of return you need, it can then be determined, at least from an historical perspective, what types of assets, or blend of assets, has been able to accomplish that type of return. Generally speaking, higher returns will demand higher risk taking and less diversification. More moderate return assumptions may make more sense (a less volatile or risky portfolio), but could you still achieve your goals? There will always be tradeoffs between safety and return, risk and reward. And do not assume that the phrase, “high risk means high return” has any semblance of truth. High risk means high risk, that is, a higher possibility of loss of principal, but this may also mean a higher possibility of higher returns, but remember the difference between “possibility” and “probability.” How much risk can you tolerate? The real crux of the matter is your risk tolerance. How much volatility do you need to take, and how much can you tolerate in order to accomplish your goals? To create open and candid communication with your advisor, you will probably want to develop a comprehensive investment policy statement (IPS). According to the Chartered Financial Analyst Institute, there are a couple of elements of an IPS that are germaine to our discussion here: (1) it should produce a common vocabulary for the advisor and client
to discuss risk and return; (2) it should result in a document of understanding that protects both the investor and advisor. In short, it is a written document that establishes a client’s objectives and limitations in the management of a portfolio. It should tell the financial advisor what the client’s risk and return expectations are, and what the advisor can and cannot do in seeking to achieve these objectives. For example, a client may not want a certain asset type in the portfolio for various reasons, and the advisor will need to take that into consideration. With this in mind, the discussion points need to encompass two broad themes: the road map of goal achievement (risk, return, portfolio construction), and the rule book for implementation (time horizon, rebalancing or re-allocating the portfolio, taxes, unique circumstances, legal issues, and liquidity needs). Here are the steps for the development of a successful investment policy statement: STEP 1: Regarding the discussion on risk, or volatility, the first step will be to determine an overall risk tolerance. From there, you will be able to get more specific with your advisor in terms of the actual standard deviation you can deal with in your portfolio. The tolerances are generally described as follows: Conservative: you are stating that you desire very low fluctuation in account values in exchange for a low return potential. Such a portfolio would most likely be mostly fixed investments, bond and certificate investments. Over long periods of time, historically, these very conservative portfolios have had a difficult time keeping pace with inflation. Moderately Conservative: you are willing to accept some fluctuation in account values in exchange for a below-average return potential. A portfolio in this space would most likely be more leaning toward fixed investments and bonds, but also have some lowervolatility equity holdings. Over long periods of time, portfolios in this category may do better than those that stayed very conservative. Moderate: you are willing to accept both an average fluctuation and average return. (A moderate portfolio would have a diversified blend of fixed and equity investments. The proverbial “50/50” portfolio would fit here, that is: 50% of various fixed investments such as bonds, certificates, cash and the like; and 50% of various equity holdings, such as stocks and real estate.) With the development of more non-correlated 10
assets and strategies, generally referred to as "alternative investments," there may be an opportunity to sprinkle in exposure by allocating some assets from either the fixed or equity side of the portfolio, or both, if suitable and appropriate. Alternative investments are not necessarily suitable for all investors. Moderately Aggressive: you are willing to accept relatively high volatility in your account values in exchange for a relatively high return potential. This portfolio would weigh heavily toward equity assets, such as stocks, real estate, commodities, etc. with a lesser allocation to fixed investments or bonds. Aggressive: you are willing to accept very high volatility in exchange for a possibility of high returns. A portfolio considered aggressive would likely be mostly invested in stocks, real estate, and may even employ borrowed money, or leverage, to enhance returns. It’s important to note that in considering your risk tolerance, take into account both your willingness and ability to take risks. As a quick example, you might be willing to take a risk on the stock of a company that has just gone public (your willingness is high), but you may not be able to tolerate the high volatility that comes with it, or too large of such a position may jeopardize your portfolio (your ability is low). There can be a fine line between a prudent investment and speculation. STEP 2: Referring back to page 5, ask your advisor to supply you with your portfolio performance on as long-term a history as possible (remember that short-term data will generally be less reliable than long-term data). You’ll need the long-term average annual total return. And, ask to have what the long-term expected return should be. (The reason this is important is that, as an example, even though the long-term return for the S&P 500 Index is about 10% per year average, there have been times it has been well under that. From 2000 to 2010, (12/31/1999 to 12/31/2009) it was actually negative for that 10-year period (Morningstar data). Your advisor should be able to provide you with an actual or estimate of the annual standard deviation of your portfolio (even if you’ve changed investments). Although past performance is no guarantee of future results, you can build a volatility bar (as seen on page 5) for your own portfolio. Then the questions to think about and discuss with your advisor may be: is this portfolio volatility something you are comfortable with? Can you tolerate the volatility illustrated? Do you need to accept that volatility in order to achieve your goals? Do you need to take more risk, or less?
STEP 3: Assuming you are comfortable with the volatility of your portfolio, there still remains at least one more significant discussion point: how should the portfolio be adjusted on a forward basis? In other words, do you need to “re-balance” between stocks and bonds, and how often? Maybe you need to “re-allocate” instead (take on more or less risk). When do you want to take some money “off the table.” In other words, how do you decide when to take profits or book losses? Maybe your decision to sell some assets will be based on time horizon and goals; maybe it will be based on market valuations (when price ratios may be high); maybe it will be a combination. However, it is a very important discussion point since, for most investors, portfolios eventually are turned into income, so planning out cash flows and how to fund those needs is of utmost importance. Investor Takeaway: Much of investing success has to do with proper diversification and having proper expectations. Many investors get into trouble when markets become volatile, which they will do from time to time. Knowing this ahead of time, and knowing the likely range of returns you may expect to see, can go a long way in helping you remain calm for the long haul so your returns are not jeopardized by making emotionally-based moves that you may regret later. Knowing what return on investment you need to be successful in your financial planning is important, but knowing the volatility, or risk, you need to take on can be critical since investor behavior can have a bigger impact on results than even investment performance. Knowing and understanding the risks you may need to take, and what you are comfortable with, is a most important conversation to have with your financial advisor. One of the most common measurements of volatility is standard deviation, and knowing how much your portfolio may fluctuate from the “expected long-term return” is the linchpin of the conversation. And the capstone of that conversation should be a philosophy or strategy as to how and when to take some gains to convert to income for the cash flow needs you may desire in retirement.
11
Post script: “regression to the mean” One truism that seems to occur, but on an irregular basis, is that returns regress to the mean over time, meaning that returns that are higher than the average are inevitably followed, at some point, by some returns that are below average, and vice versa. Two examples would be what happened to the S&P 500 in the mid-1990s through the turn of the century, and then the recent experience of the stock market since the recession of 2008. The average return for the S&P 500 TR (Total Return Index) is about 10% per year (long term). The annual returns for calendar years 1995-1999 were 38%, 23%, 33%, 29%, and 21% (way above the average)12 and were followed by -9%, -12% and -22% in years 2000-2002. The negative 37% that was experienced in 2008 was followed by +26%, 15%, 2%, 16%, 32% and 14% (all but one of those positive years was above the average). The point being that through the years, your portfolio will experience the ups and downs on the way to an average. And as stated previously, you (most likely) will not have all of your money in stocks so your “range of returns” should be much tighter and less volatile than the S&P 500 Index being discussed here.
Although it applies to all investors, when you are near or in retirement, you may want to have as part of your investment policy statement, a philosophy and strategy as to when to take some profits off the table and turn those gains into cash flow. One possible idea to discuss with your advisor would be to consider taking some profits when the price/earnings (P/E) ratio of the market gets to the high side of its historical range.13 Chances are, those same markets may perform at less than average in the near future to return to closer the historical mean so you may want to book some profits…while they are there. From an income tax perspective, that is taking a “unrealized gain” (not currently taxable) and turning it into a “realized gain” (taxable). However, long-term capital gains do presently get a preferential treatment of 0% (for those in the 10% and 15% brackets), 15% (for those above the 15% bracket), or 20% (for those in the highest tax bracket). In any case, understand that the volatility you set up in your portfolio will probably happen at some point, and you need to have a plan on how to deal with that eventuality. Of course, past performance is no guarantee of future results, but it’s best to have a plan.
12
The returns in this example vary slightly from the chart on page 9 because the TR Index (Total Return) includes dividends, whereas the chart is the “price-only” index, not including dividends.
13
The reason the word “some” is used is prudence. The market can surprise sometimes and stay above the mean P/E ratio for an extended period of time. Consider the taking of profits as “selective pruning” versus wholesale “cutting and running.”
12
Appendix The following three graphics chart the S&P 500 Index, then the Barclay’s Capital Aggregate Index, and then a 50/50 mix of both indexes. This graphic is of annual returns (calendar year) of the S&P 500 Total Return (TR) Index.
—
S&P 500 Stock Market Index
40 30 20 10 0 -10 -20 -30
2015
2 014
2013
201 2
2011
2 010
20 09
20 08
20 07
20 06
20 05
20 04
20 03
20 02
20 01
2000
1999
1998
19 97
199 6
1995
1994
19 93
19 92
19 91
199 0
-40
Source: Chart created by Ameriprise based on data from 2015. Standard and Poor's, Barclay's Capital (formerly Lehman Brothers Aggregate Bond Index). Combined returns based on calculation of 50% of S&P 500 return, 50% of Barclays Capital Aggregate Bond Index return. Past performance does not guarantee future results. It is not possible to invest in an index. These examples do not reflect sales charges, taxes or other costs associated with investing.
13
Looking at the S&P 500 Index (total return) since 1990, it’s easy to spot significant volatility. One year, the calendar year return was +38% (1995), and in another year, the return was -37% (2008). Examining the next chart which shows the Barclay’s Capital Aggregate Bond Index (this index includes both government and corporate bonds), you can see very little volatility compared to the stock index. However, with the low volatility came modest returns in many years. This graphic is of annual returns (calendar year) of the Barclay’s Capital Aggregate (bond) Index.
—
Barclays Capital Aggregate Bond Index
40 30 20 10 0 -10 -20 -30
2015
2 014
2013
201 2
2011
2 010
20 09
20 08
20 07
20 06
20 05
20 04
20 03
20 02
20 01
2000
1999
1998
19 97
199 6
1995
1994
19 93
19 92
19 91
199 0
-40
Source: Chart created by Ameriprise based on data from 2015. Standard and Poor's, Barclay's Capital (formerly Lehman Brothers Aggregate Bond Index). Combined returns based on calculation of 50% of S&P 500 return, 50% of Barclays Capital Aggregate Bond Index return. Past performance does not guarantee future results. It is not possible to invest in an index. These examples do not reflect sales charges, taxes or other costs associated with investing.
14
In contrast to the S&P (TR) Index, bonds have a more reliable return, but there still are years it has dipped into negative territory. This graphic is of annual returns (calendar year) of a 50/50 mix of stocks and bonds, represented by the S&P 500 TR Index and the Barclay’s Capital Aggregate (bond) Index.
—
50/50 Mix
40 30 20 10 0 -10 -20 -30
2015
2 014
2013
201 2
2011
2 010
20 09
20 08
20 07
20 06
20 05
20 04
20 03
20 02
20 01
2000
1999
1998
19 97
199 6
1995
1994
19 93
19 92
19 91
199 0
-40
Source: Chart created by Ameriprise based on data from 2015. Standard and Poor's, Barclay's Capital (formerly Lehman Brothers Aggregate Bond Index). Combined returns based on calculation of 50% of S&P 500 return, 50% of Barclays Capital Aggregate Bond Index return. Past performance does not guarantee future results. It is not possible to invest in an index. These examples do not reflect sales charges, taxes or other costs associated with investing.
15
S&P 500 TR Index (Total Return) annual (calendar year) returns including dividends Yearly S&P 500 Total Return Index
Here is the formula for calculating standard deviation.
Date
Closing level
12/30/1988
288.116
S=
12/29/1989
379.409
32%
12/31/1990
367.6313
-3%
12/31/1991
479.6332
30%
12/31/1992
516.1779
8%
12/31/1993
568.2021
10%
12/30/1994
575.7049
1%
12/29/1995
792.0419
38%
12/31/1996
973.8967
23%
12/31/1997
1298.821
33%
12/31/1998
1670.006
29%
12/31/1999
2021.401
21%
12/29/2000
1837.365
9%
12/31/2001
1618.979
-12%
12/31/2002
1261.176
-22%
12/31/2003
1622.939
29%
12/31/2004
1799.548
11%
12/30/2005
1887.941
5%
12/29/2006
2186.127
16%
12/31/2007
2306.232
5%
12/31/2008
1452.976
-37%
12/31/2009
1837.5
26%
12/31/2010
2114.29
15%
12/30/2011
2158.94
2%
12/31/2012
2504.44
16%
12/31/2013
3315.59
32%
12/31/2014
3769.44
14%
12/31/2015
3821.6
1%
% change
(SOURCE: Bloomberg, Ameriprise Financial Services, Inc. Note: The S&P 500 TR (Total Return) index is a different index than the more common S&P 500 Index)
∑ (X - X)2 N
Where S = the standard deviation of a sample, ∑ means “sum of”, X = each value in the data set X = mean of all values in the data set, N = number of values in the data set.
Other terms you may want to know for discussions with your advisor: Sharpe ratio: attributed to Nobel Prize winner in economics, William Sharpe, this calculation takes the return of an investment (actually it’s the excess return over the “safe” rate of T-bills) and divides it by the standard deviation, or volatility. The result is a number that measures the amount of reward experienced per unit of risk. Its meaning can be seen when you compare two or more investments and see how the ratios compare. The higher the number, the more return was achieved for the risk assumed. Beta: measures the degree of change in value one can expect in a portfolio given a change in value in a benchmark index. A beta value of more than one indicates the portfolio or investment is more volatile than the index, and a number less than one means it is less volatile. The value to the investor will be in understanding how much volatility he or she is taking on with any particular investment. For example, any single stock in the S&P 500 may have a volatility, or beta, that is much higher than the index itself (various performances of different stocks and sectors in the S&P tend to balance each other out to some degree and bring the volatility of the whole index down). We’ve already discussed that the volatility of the S&P is about 15. If an individual stock has a beta of 1.6, that means the volatility range during the measuring period was 60% higher than the index, or the standard deviation of that stock was 24 (15 X 1.6). Alpha: is derived from the actual performance of an investment when compared to its expected performance (its beta). Alpha is often seen as a measurement of value added or subtracted by a portfolio’s manager. As a quick example, if the beta of a mutual fund is 1.1, (in other words, 10% more volatile than the index) it means that the expected performance of the fund would be 10% more volatile than the index it’s being compared to. If the fund is up more than 10% 16
above the index in an up market (or down less than minus 10% in a falling market), the manager earns himself or herself a “positive” alpha number. Although this is what an investor would generally like to see, remember that short-term positive alpha numbers do not mean this can continue. Past performance is no guarantee of future results. It only shows what HAS happened and not what WILL happen. R-squared: reflects the percentage of a portfolio’s movements that can be attributed to movements in its underlying benchmark or index. As an easy example, a large US stock blend mutual fund will most likely be benchmarked to the S&P 500 index. If it is constructed to be very close to the index, the R-squared measurement will most likely be close to the number 100. If the fund does not look like or move like the index, the number will move away from (below) the number 100. It basically is a measurement of correlation in that a high R-squared investment is expected to move like its underlying index. The definitions (above) are derived from Morningstar definitions, with some editing for clarification. VIX: The Chicago Board of Options Exchange (CBOE) introduced the Volatility Index (VIX) in 1993. It shows the market expectation of 30-day volatility. The VIX is a widely-watched measure of shorter-term market risk and is sometimes referred to as “the investor fear gauge.” VIX values greater than 30 are generally associated with high volatility whereas values below 20, volatility is assumed to be fairly low.
“The current value of the standard deviation can be used to estimate the importance of a move or set expectations. This assumes that price changes are normally distributed with a classic bell curve. Even though price changes for securities are not always normally distributed, chartists can still use normal distribution guidelines to gauge the significance of a price movement. In a normal distribution, 68% of the observations fall within one standard deviation. 95% of the observations fall within two standard deviations. 99.7% of the observations fall within three standard deviations.” FROM THE DEFINITION OF STANDARD DEVIATION, SOURCED FROM THE WEBSITE STOCKCHARTS.COM
The VIX is probably best used and viewed in the shorter-term environment, such as the pricing of options strategies but may not be a good gauge for longer-term investors. However, it can help give an explanation to shorter-term market swings. And, if an investor is searching for buying opportunities, a high VIX environment may provide some price swings that he or she may want to take advantage of.
Investment products are not federally or FDIC-insured, are not deposits or obligations of, or guaranteed by any financial institution and involve investment risks including possible loss of principal and fluctuation in value. Diversification does not assure a profit or protect against loss. Ameriprise Financial, Inc. and its affiliates do not offer tax or legal advice. Consumers should consult with their tax advisor or attorney regarding their specific situation. Ameriprise Financial Services, Inc. Member FINRA and SIPC. © 2016 Ameriprise Financial, Inc. All rights reserved.
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