Moving averages have captured the imagination (and increasingly the managed money) of advisors these days, and it’s easy to see why, at least through the lens of history. Consider a simple strategy benchmark with an initial weighting of 60% stocks (represented by the S&P 500) and 40% bonds (by the Barclays Aggregate Bond index). Buying and holding this mix earned you an annualized total return of 7.7% for the 20 years through August 2012 while it gave you an annualized volatility (standard deviation) of roughly 10.7. By contrast, your performance would have considerably improved with a market-timing strategy that adjusted the same initially weighted allocation using signals from a simple 10-month moving average (roughly the equivalent of a 200-day average). You would have seen a return of 9.3% a year and volatility of 7.9 (see Figure 1).
Here’s how the moving average strategy in Figure 1 works: When the equity index falls under its 10-month moving average (based on monthly data) at any month’s end, the entire stock allocation is moved to cash (three-month T-bills). There it stays until the equity index closes above its 10-month average, at which point all the cash is shifted back to stocks. The same rule applies to bonds. In short, the equity portion of the portfolio is either in stocks or cash, and the remaining fixed-income allocation is either in bonds or cash. The result is that this moving average strategy would have sidestepped the worst of the corrections and crashes. If that sounds familiar, it’s because similar results have been documented in numerous studies through the years.
Figure 2 shows the differences in one-year returns for the moving-average strategy minus the returns for the buy-and-hold strategy. The dots above the zero mark indicate that the moving-average strategy outperformed for the trailing-12-month period, and vice versa. For much of the past two decades, annual returns between the two strategies shared relatively similar results. But the differences widened dramatically around and during recessions—overwhelmingly in favor of the moving-average strategy.
For this reason, finance professor Paskalis Glabadanidis calls moving average-based strategies the equivalent of an “at-the-money put option combined with a long position in the underlying risky asset” (a quote from his working paper, Market Timing with Moving Averages.) In other words, the main value of moving averages has kicked in when the market has trended lower for an extended stretch—a bear market.
None of this should be surprising, says Adam Grimes, the chief investment officer of Waverly Advisors and author of the recently published book The Art and Science of Technical Analysis. “The major crashes usually come well after warnings signalled by technical weakness.” The steep sell-off in the stock market in late 2008 and early 2009, for example, started about a year after equities set new highs. Soon after the peak, investors saw a series of warnings in the moving-average signals.
That’s not unusual, notes Grimes. He adds, however, that there’s nothing magical about 50- or 200-day moving averages—or any other rules for calculating average prices. Moving averages, in all their variations, are simply tools that quantify some of the “repeatable patterns that illustrate the psychology of the markets.”
The main advantage of looking at prices through the prism of trailing averages is that it takes a lot of the emotion out of analysing market trends, he counsels. “You’d be much better off with this than making emotional decisions,” Grimes says. Is it foolproof? No, of course not. “We don’t deal in certainties—we deal in probabilities.”
Source: (Re)Discovering Technical Analysis