My colleague, Jared Kizer, who serves as chief investment officer at Buckingham Strategic Wealth and The BAM Alliance, recently examined the performance of the S&P 500 Index from March 2009 (the bear market ended on March 9, 2009) through October 2018, a period ending shortly before a spate of market volatility in December that saw the index record some dramatic declines.
Using a common statistical analysis referred to as “bootstrapping,” he shows how “otherworldly” the returns to that asset class were over the past decade. Importantly, he also shows that other “alternative universes” might have shown up.
The message for investors is that they should not make the all-too-common error of recency bias and become performance chasers. The outstanding returns provided by the S&P 500 also led to much higher valuations. While that doesn't forecast a bear market, it does mean investors should not expect a repeat performance, and that return expectations should now be well below historical levels. Following is his analysis.
The S&P 500 was up 352% from March 2009 through October 2018, while international developed stocks, emerging market stocks and bonds were up 140%, 142% and 39%, respectively.
What you might be surprised to know, though, is that it’s almost impossible to simulate another same-length period where the S&P 500 had better risk-adjusted returns. In other words, saying the S&P 500 has done well during this period is a gargantuan understatement. As we will see, it’s done so well that it’s reasonable to ask whether anyone alive will ever experience a better performance period for U.S. large-cap stocks.
The last sentence may sound extreme, but returns data for the S&P 500 illustrate just how mind-blowingly astounding the post-global financial crisis (GFC) returns experience has been. Using a bootstrapping technique (also referred to as “resampling”), you can take the entire historical returns history for any asset class and build out an extremely large number of alternate histories of any length.
For example, you can use the entire monthly returns history of U.S. small-cap stocks to build out 100,000 unique 10-year-length histories to get a sense of what’s theoretically possible, performancewise, over a 10-year period.
Widely Used Method
As you might guess, bootstrapping is very similar to Monte Carlo simulation; the key difference is that bootstrapping directly uses historical data as opposed to simulating returns according to a particular distribution (e.g., the normal distribution).
Bootstrapping is widely used in a variety of other fields outside of finance (and was recently used in a paper by professors Gene Fama and Ken French), and there are a multitude of online resources you can check out if you want to more deeply understand the procedure.
For most, though, all you need to know is that it’s a great way to get a sense of the possible range of outcomes you can then use to compare to specific, actual historical periods of returns data, as we’ll do here.
From a financial market point of view, it’s been about 116 months since the official end of the GFC. This period covers March 2009 through October 2018. In years, this is just shy of a decade. Over this period, the S&P 500’s excess return, i.e., the return in excess of the Treasury bill return, has been 16.5% per year (or 1.35% per month). In terms of the growth of a dollar, $1 invested in the S&P 500 had grown to $4.52 by the end of October.
Most impressively, however, the S&P 500’s excess return achieved a Sharpe ratio of almost 1.30. While Sharpe ratios are generally a bit harder to interpret than the growth of $1 or annualized returns, this Sharpe ratio is about three times higher than its long-run historical value. In other words, not only have raw returns been astounding in the post-GFC period, but the risk-adjusted returns (i.e., Sharpe ratio) have been otherworldly.
Using bootstrapping, we created 100,000 other 116-month returns histories for the S&P 500’s excess return and analyze them below. The excess returns history we used for this bootstrapping procedure encompasses the complete history of January 1926 through October 2018.
Let’s first look at a histogram of the average monthly excess return across each of these histories. Data are from Bloomberg and Ken French’s data library.