Black swans & the ‘10 best days’ myth: Can investors prepare for market outliers?
Black swans & the ‘10 best days’ myth: Can investors prepare for market outliers?
How much effect do market outliers have on long-term performance? Can the investor prepare for these anomalies, or are they truly ‘black swans’ that cannot be managed?
Editor’s note: Many thanks to Meb Faber and his associate, Prabhat Dalmia, for permission to publish an abbreviated version of this paper, “Where the Black Swans Hide & The 10 Best Days Myth,” which was first published in August 2011. Thanks also to the Market Technician’s Association (MTA), which published this paper in July 2016. A full version of the paper can be downloaded here.
Mr. Faber’s analysis addresses several assumptions behind the “missing the 10-best-days” argument, which, as he says, is “often proffered by advocates of buy-and-hold investing.” He also examines the issues of how market “outliers tend to cluster and the majority of both good and bad outliers occur once markets have already been declining.” Mr. Faber advocates “that investors attempt to avoid declining markets where most of the volatility lies” and concludes that “market timing and risk management is indeed possible, and beneficial, to the investor.”
Taleb defines a black swan as an outlier outside the realm of regular expectations because nothing in the past can convincingly point to its occurrence. The event carries an extreme impact and is often “explained” after the fact, giving the impression that it is explainable and could have been predicted.
Many market commentators have latched on to this term to describe all financial market events. However, the existence of large outlier events known as “fat-tailed distributions” in financial market returns has been well-documented for more than 40 years (see Benoit Mandelbrot’s “The Variation of Certain Speculative Prices” and Eugene Fama’s “The Behavior of Stock-Market Prices”). While the financial media have only recently revisited the fat-tail concept (due largely to the occurrence of the Internet bust in 2000–2003, as well as the global financial meltdown in 2008 and 2009), it has been a thoroughly studied field in finance over the past several decades.
Investors should realize that normal market returns are extreme. Individuals that continue to believe in the Gaussian (bell-shaped) distribution, or ignore empirical results, will continue to be surprised by future events. Roughly 40% of all yearly returns in U.S. stocks are greater than 10% or less than -10%. Bear markets are common, and markets can and do decline from 50% to 100%.
Financial market return distributions are similar to fractal systems that follow a power-law distribution (which is useful in describing events such as earthquakes and volcanic eruptions). Below is a chart from the book “The Failure of Risk Management” by Douglas Hubbard, which illustrates the inability of the Gaussian models to account for large outlier moves in financial markets. In a normal-distribution world, a 5% decline in the Dow in a single trading day should not have happened in the past 100 years. In reality, it has happened nearly 100 times.
FIGURE 1: FREQUENCY OF SEVERE MARKET DECLINES VS. GAUSSIAN MODEL
Unfortunately, many investors have come to the conclusion that rare events are impossible to predict, and therefore, there is nothing to do other than buy and hold their investments and wait out any negative outliers. However, this explanation simply rids the investor (advisor) of any responsibility. The fatalistic attitude becomes “it was a black swan; it’s not my fault!”
In this article, we examine market outliers, their effects, and, more importantly, when they occur and if the investor can do anything to protect against them.
Market outliers: The ‘10 best days’ myth
We begin our examination by taking a look at market outliers in the U.S. stock market back to 1928.
One of the most common rhetorical bulwarks in the defense of buy-and-hold investing is to demonstrate the effects of missing the best 10 days in the market and how that would affect the compounded return to investors. This is perhaps one of the most misleading statistics in our profession (another being the Brinson asset-allocation study misquote). A number of academic papers have examined the effects of missing both the 10 best and the 10 worst days (two good ones are Paul Gire’s “Missing the Ten Best,” published in the Journal of Financial Planning, and Richard Ahrens’ “Missing the 10 Best Days”).
In Table 1, we examine the S&P 500 (and the broad market predecessor) from 1928 to 2010. We use price history only, as dividends will not have a meaningful impact on the daily return data.
TABLE 1: U.S. STOCKS DAILY RETURNS (9/1928–2010), PRICE ONLY
What about the outlier returns? Table 2 shows the best and worst 1% of all days, which equates to only about two or three days per year.
TABLE 2: U.S. STOCKS 1% BEST AND WORST DAYS (9/1928–2010), PRICE ONLY
One can expect these days to occur a handful of times every year since 1928. Much to the displeasure of the fear-mongering media, -4% and +4% days are fairly regular.
To help us really examine the blackest of swans, Table 3 shows the best and worst 0.1% of all days. They occur, on average, only once every few years.
TABLE 3: U.S. STOCKS 0.1% BEST AND WORST DAYS (9/1928–2010), PRICE ONLY
Days of -8% and +8% are fairly rare, as are the -20% and +16% days. Exactly how big of an impact do these outliers have on performance? Massive. Table 4 shows the annualized returns if the investor missed some of the best and worst days. If you missed the best 1% of all days, your return gets crushed from 4.86% down to -7.08% per annum. However, the converse is also true: if you miss the worst 1% of returns, your returns explode to 19.09% a year. And take special note that if you miss both the best and worst 1% of days, your return is higher than buy and hold.
TABLE 4: MISSING THE BEST AND WORST DAYS:
ANNUALIZED RETURNS (9/1928–2010), PRICE ONLY
Most analysts, unfortunately, stop here and throw up their hands. They proclaim buy-and-hold investing to be the only way to ensure being in the market for these best days. Because these events are so rare, and because they have such as massive impact, there is an infinitesimally small chance of predicting when they will occur, and therefore the effort is useless. They take the ball all the way down to the five-yard line but stop there.
What are they missing?
The human element
Markets are a collection of humans, and, therefore, a collection of human emotions. Greed, fear, jealousy, pride, and envy all manifest themselves to the fullest in capital markets.
When you are making money, you are thinking about the new car you are going to buy, how smart you are (and how much smarter you are than your neighbor), the vacation you are going to take, and the (second, third, fourth) house you are going to buy. The part of the brain that is firing nonstop here is the same region that gets stimulated by cocaine or morphine.
However, when you are losing money, you are probably not opening your account statements. Instead, you are thinking about how dumb you are (and how stupid you were to listen to your neighbor) and how you are going to pay for that second house. Even thinking about investing is likely to elicit feelings of revulsion. The brain processes portfolio losses in the same region that is stimulated by the flight response. (For more in-depth discussions on behavioral biases, please consult some of the work of the great MIT professor, Andrew Lo.)
Table 5 examines the returns (and, more importantly, the volatility) when the market is appreciating versus declining (defined as above or below the 200-day simple moving average, or SMA). Based on this data, and that of Table 6, it is little wonder that the volatility found in declining markets can have such a profound impact on investors’ emotional responses.
TABLE 5: MISSING THE BEST AND WORST DAYS (9/1928–2010), PRICE ONLY
(To be read: 69.59% of 1% “worst days” occur in a declining market, 78.34% of 1% “best days” also occur in declining markets.)
What about the outliers—where do they occur? As Table 5 shows, the vast majority (roughly 60%–80%) of the best and worst days occur after the market has already started declining. The simple reason is that markets are more volatile when they are declining, and when the really volatile events and days occur, they tend to cluster together.
Our central argument is that returns improve and volatility is reduced when an investor is invested in uptrending markets, thus avoiding the volatility and clustering of best and worst days inherent in declining markets. As you can see in Table 6, in declining markets, returns are much lower and volatility is much higher.
TABLE 6: MISSING THE BEST AND WORST DAYS (9/1928–2010), PRICE ONLY
Benoit Mandelbrot provides an insightful passage on volatility clustering and timing in his book “The Misbehavior of Markets”:
This effect also plays out on the monthly time frame as well. For a look at other markets, including real estate, bonds, and foreign stocks, on the monthly time frame back to 1972, you can view a blog post here titled “Your Irrational Brain.”
For those investors pondering how they can attempt to avoid these highly volatile periods in markets, we invite you to download a few of our other white papers : “A Quantitative Approach To Tactical Asset Allocation” and “Relative Strength Strategies for Investing.”
Astute market analysts must also realize the drawbacks and downsides of any indicator or investment approach. In the case of a trend-following approach, there are two main drawbacks. First, in trendless markets, whipsaws can occur that have negative effects on the portfolio. Second, and perhaps more important, a trend-following approach does not guarantee the investor will miss a black swan event in an uptrend. A very sharp move against the trend will not allow the investor or model time to react and protect against such a move. Investors looking for protection against this sort of event can use derivatives such as options to protect the portfolio when fully invested (so-called tail-risk insurance), or consequently, to gain long exposure when mostly in cash and bonds (risk of missing out). This process could be a net cost (insurance) to the portfolio.
That is the point of risk management: understanding and trying to account for as many risks as you can.
Our broad summary points from this analysis?
- The stock market historically has gone up about two-thirds of the time.
- All of the stock market return occurs when the market is already uptrending.
- The volatility is much higher when the market is declining.
- Most of the best and worst days occur when the market is already declining. Reason: see #3. Markets are much riskier than models that assume normal distributions can be used to predict.
- The reason markets are more volatile when declining is because investors use a different part of their brain when making money than when losing money.
The opinions expressed in this article are those of the author and do not necessarily represent the views of Proactive Advisor Magazine. These opinions are presented for educational purposes only.
Meb Faber is a co-founder and the chief investment officer of Cambria Investment Management. Mr. Faber is the manager of Cambria’s ETFs, separate accounts and private investment funds. Mr. Faber has authored numerous white papers and three books: "Shareholder Yield," "The Ivy Portfolio," and "Global Value." He is a frequent speaker and writer on investment strategies and has been featured in Barron’s, The New York Times, and The New Yorker. Mr. Faber graduated from the University of Virginia with a double major in engineering science and biology. cambriafunds.com, mebfaber.com