Technical Analysis Revisited: Moving Averages = Above Average Returns?
Technical analysis — trading based on the chart patterns of stocks — has always been a hotly debated investing tactic. While fundamental analysts may decry it as junk science, to this day it still has many proponents in Wall Street proprietary trading shops.
Resistance levels, support levels, triangle patterns, double tops, head and shoulders, moving averages, etc., are among the price patterns technical analysts may study to anticipate and profit from future market movements.
We examined one particular form of technical analysis — moving averages — to assess how it performed over the decades.
We built two portfolios that went long the S&P 500 when it traded above its moving average and shorted it when it traded below. One portfolio was constructed based on a 50-day moving average, the other on a 200-day moving average.
As a strategy, buying the market on days when it eclipsed its 50-day moving average generated daily average returns between 0.11% and 0.18% across the six decades surveyed, with the high mark reached in the 1980s. Buying the market on days when it fell below the moving average resulted in average daily returns between -0.14% and -0.28, with the 1980s also accounting for the largest losses.
To give a sense of the magnitudes here: If an investor were to buy every day the market was over its 50-day moving average in the 1960s and short every day that it was below, this would yield an average yearly return just around 22%, while the S&P 500 generated a geometric average return of 10% over the decade. This means an excess performance of 12 percentage points. This outperformance was significant at the 1% level across all decades studied.
The 50-Day Moving Average Portfolio
|Average Daily Return: Buying Above Moving Average||0.11%||0.14%||0.18%||0.17%||0.17%||0.15%|
|Average Daily Return: Buying Below Moving Average||-0.22%||-0.14%||-0.28%||-0.20%||-0.22%||-0.20%|
The 200-day moving average long–short portfolio yielded similar if more muted results, with daily average returns varying from a low of 0.16% in the 1970s to a high of 0.29% in the 1980s.
The 200-Day Moving Average Portfolio
|Average Daily Return: Buying Above Moving Average||0.06%||0.08%||0.09%||0.09%||0.10%||0.08%|
|Average Daily Return: Buying Below Moving Average||-0.15%||-0.07%||-0.20%||-0.16%||-0.11%||-0.14%|
Of course, moving average traders recommend buying stocks immediately after they break out, or cross the trend line, and shorting them as soon as they fall below the trend line. So, how did such a “cross-over” strategy perform?
Across the decades, the 50-day moving average long–short strategy yielded daily average returns from 0.44% in the 1960s and 2000s, to 0.70% in the 1970s.
50-Day Moving Average: Crossing Over Strategy
|Average Return One Day After Crossing Below||-0.24%||-0.35%||-0.22%||-0.18%||-0.14%||-0.30%|
|Average Return One Day After Crossing Above||0.20%||0.35%||0.31%||0.40%||0.29%||0.22%|
By contrast, the 200-day moving average long–short portfolio generated a daily average as low as 0.20% in the 1960s to as high as 0.71% in the 1990s.
200-Day Moving Average: Crossing Over Strategy
|Average Return One Day After Crossing Below||-0.04%||-0.23%||-0.31%||-0.16%||-0.12%||-0.36%|
|Average Return One Day After Crossing Above||0.16%||0.10%||0.17%||0.55%||0.20%||0.12%|
Although such moving average strategies have yielded excess returns, this performance does not come without risk. Specifically, there is considerable volatility on the crossing below side of the moving average as well as skewness in some cases. Perhaps the higher returns then are the investors’ compensation for taking on the excess risk, or maybe just a form of momentum risk.
All in all, while the returns associated with these moving average strategies may be down from their 1980s and 1990s heyday, there may still be alpha to be gained in our modern markets.
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All posts are the opinion of the author. As such, they should not be construed as investment advice, nor do the opinions expressed necessarily reflect the views of CFA Institute or the author’s employer.
Image credit: ©Getty Images / Torsten Asmus
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