Both the Dow Jones Industrial Average and the S&P 500 are just one or two moderately bad trading days from closing below a key threshold that could spur additional selling. As of the market’s close on Friday, Oct. 26, the S&P was 2.5 percent above its 200-day simple moving average, while the Dow was just 1 percent above its 200-day simple moving average.
While it appears that most traders focus on the simple moving average, a number of traders also monitor the exponential moving average, and the news there is only marginally better for that same span of time. Additionally, both indexes already closed decisively below their 50-day moving averages early last week.
Technical analysts use moving averages to monitor the market’s trend. A simple moving average takes the average of the market’s closing values for each trading day over a particular period and divides them by the number of days in that period. But for longer-term periods, that method puts market sessions in the relatively distant past at parity with the most recent sessions. To overcome this perceived shortcoming, analysts use the exponential moving average to assign greater weightings to more recent trading sessions.
Regardless of the approach, both versions of the moving average are an effort to smooth out the market’s short-term fluctuations in order to gain insight into longer-term trends. And some traders even go so far as to use these moving averages to set buy and sell signals for both individual securities as well as the broad market.
Naturally, skeptics might wonder whether such a widely followed market indicator could eventually lose its effectiveness. After all, if everyone attempts to exploit the same indicator, that would presumably lead to a diminution in returns.
Beyond that, there’s always the potential for technical analysis to become self-fulfilling. In other words, if the market closes below the 200-day moving average and numerous investors sell as a result, that could force the market down further.
And even those traders who don’t necessarily employ technical analysis are often aware of these thresholds. Value-oriented investors might wait to pick up bargains once a selloff is triggered, while sizable traders might even attempt to push an individual security below its 200-day moving average in order to pick up shares more cheaply later.
Moving Averages for the Long Run
In the short term, of course, anything is possible. But over the long term, the 200-day moving average has enjoyed great success. In his landmark book “Stocks for the Long Run,” Wharton professor Jeremy Siegel found that a timing system that uses the 200-day moving average to enter and exit the market outperformed a buy and hold by 0.67 percentage points annually over the 115-year period from 1886 through 2001. And it achieved this performance with nearly 23 percent less risk, largely due to the fact that it was invested in the market just 62.8 percent of the time.
Of course, this performance moderately lags the market once transaction costs are taken into account. And even though Siegel included a 1 percent buffer above and below the moving average to eliminate whipsaws and reduce the number of trades, his system still required an average of nearly three trades per year. That means its performance would shrink further once adjusted for taxes.
But these days, investors could conceivably overcome both taxes and transaction costs by trading commission-free exchange-traded funds (ETF) in tax-advantaged accounts such as the IRA and Roth IRA. With various limitations, commission-free ETF trading is available at fund giants Fidelity and Vanguard, as well as brokerages such as Schwab and TD Ameritrade. ETFs still charge annual expense ratios, but those are typically minimal for ETFs that track the broad market.
A Timing Strategy for Tactical Asset Allocation
In addition to Siegel’s study, there’s another investment system that employs the 200-day moving average to an intriguing end. Portfolio manager Mebane Faber published a study of a tactical asset allocation strategy that uses the 200-day moving average to trade a portfolio constructed from five different asset classes. His backtested results demonstrate an equity-like return, but with volatility and drawdowns more characteristic of bonds.
The five asset classes Faber specified for his model are domestic stocks, international stocks, bonds, real estate, and commodities, and the proxies he used for each are the S&P 500, the MSCI EAFE Index, 10-year Treasuries, the NAREIT Index, and the Goldman Sachs Commodity Index, respectively.
The portfolio had an equal allocation to each of the five asset classes, and that allocation was bought or sold at the close of the market session in which the signal was triggered. It’s important to note that signals were only monitored on the last trading day of each month, so if key levels were breached during the month, they were ignored.
Over the period from 1973 through 2008, Faber’s system returned 11.3 percent annualized vs. 9.8 percent for a buy-and-hold portfolio containing the same five asset classes. And it produced this return with 30 percent less volatility. Even more impressive, the maximum rolling 12-month loss was just 9.5 percent.
Although this system can be easily replicated by the average investor, backtested results often seem to come undone once a system is applied in real time. Also, the utility of a market timing system for portfolio construction depends on the period in question. Faber’s use of five different asset classes overcomes the typical “all in or all out” approach that many market timers seem to use. His data show that his portfolio was invested in four of the five asset classes nearly 40 percent of the time, and that it went to 100 percent cash only around 1 percent of the time.
The Caveats of Mechanical Investing
But most market timing strategies tend to perform best during periods punctuated by bear markets with extended downside volatility. For example, some strategies that use market timing, including the 200-day moving average, sidestepped most of the market’s loss in 2008. At the time, that made market timers look like geniuses. But they also missed out on some of the enviable gains at the outset of the subsequent bull market. And that’s where market timing can be truly costly in terms of performance, particularly during secular bull markets.
That’s because market timers are mostly trend followers. They will rarely make the big call to go to cash at the market’s peak or get fully invested at the market’s trough. Instead, trend following means that sell signals tend to come at least a few times a year, even if the market is otherwise on a historic bull run.
So market timers may look brilliant during bear markets, but they miss out on substantial gains during bull markets. That’s evidenced by the fact that both Siegel’s and Faber’s systems lagged the market by a considerable margin during the 1990s, even though both systems were successful over the long term.
Since most investors rarely have the discipline to adhere to a market timing system through thick and thin, that means they may have to settle for market-lagging returns until the market enters the aforementioned phase that tends to favor such systems. But knowing when it’s best to deploy such a system involves knowing what type of market we’re in at present, and that’s often only apparent in retrospect.