The last decade has been an extremely difficult period for stock market investing. Buying and holding the S&P 500 Index over this period has resulted in a loss of 0.95 percent as of the end of 2009, according to iShares.com. Because of these extremely frustrating results, many investors have turned away from buy-and-hold investing, which worked so well in the 1980s and 1990s. They have turned to a variety of strategies, from diversifying into alternative asset classes to fundamental or technical analysis, to improve performance.
One technique widely employed by professional and individual investors alike is the moving average. Moving averages have been embraced for good reason, as investors could have saved themselves substantial losses in the last bear market by using them to determine when to hold and when to sell broad-market indexes. Applying a 50-day or 200-day moving average to the S&P 500 in 2008 would have produced a loss of 3.14 percent and 3.47 percent, respectively. By contrast, a buy-and-hold position in the S&P 500 would have returned a negative 38.49 percent.
These losses will eventually be recouped. However, many do not have the nerves of steel necessary to “hang in there” after watching their hard-earned nest egg decimated. For these investors, a disciplined investment approach is needed to reduce the volatility in their portfolios, while preventing them from bailing out at the bottom. One such method may be the use of moving averages.
In this paper, we will explore three of the more popular moving averages—the 200-day, the 50-day and a 50-day/200-day crossover. We will analyze the risks and returns of each, comparing them with each other and also with buy-and-hold investing. We will study the results of trading these systems on the S&P 500 stock index, starting in 1971, the first year data is readily available. Special emphasis will be given to the three major bear markets occurring in this period.
Moving Averages Defined
What is a moving average? Investopedia defines it as “An indicator frequently used in technical analysis showing the average value of a security’s price over a set period.” For example, to calculate a 10-day simple moving average, one would collect the prices (usually at close) for the security over the past 10 days, add them together and divide by 10. The following day, one would include the price for the most recent day and drop the price for the first day. Hence, the average is dubbed “moving.”
The advantage of using moving averages is that they are great in defining whether an investment is trending up or down. The problem though, is that they are by definition slow to adapt when a trend has changed. As Robert D. Edwards and John Magee wrote in their classic work “Technical Analysis of Stock Trends”:
The trouble with a Moving Average (and which we discovered long since, but keep bumping into from time to time) is that it cannot entirely escape from its past. The smoother the curve (longer cycle) one has, the more “inhibited” it is in responding to recent important changes of trend.
To make a moving average somewhat more responsive to recent data rather than older data, many investors use an exponential moving average, which calculates the moving average geometrically. In this study, we will use exponential averages exclusively.