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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8 thoughts on “Technical Analysis Revisited: Moving Averages = Above Average Returns?”
Are the return figures net of fees?
All returns are stated without transaction costs or fees. Thanks for the clarifying question
A question is whether inevitable “black swan events” simply move averages, or do they trigger significant “crosses” requiring major action. The potential for a “whipsaw”,
similar to that when a stop-loss order is activated, would seem to be there even if slow moving averages are used.
I wonder if the author can tell me what the difference is between the moving average strategy and the crossing over strategy? Don’t both of them call for being long the market every day when it is above the moving average and short the market every day when it is below? I realize there must be a difference between the two, but I would be grateful if the rules could be clarified for me. Thanks!
Great question – the cross over strategy literally just buys in for one day if the S&P crosses over the moving average and then gets out at end of day. The opposite if it crosses over on the downside.
So in this strategy, most of the time you are sitting in a cash position. Hope this clarifies it and thanks for the question
I realize that the crossing over strategy reports the returns one day after crossing, but surely crossings occur infrequently enough render that an ineffective strategy. Is the point simply that in using the Moving Average Strategy it is important to pull the trigger the first day after the cross?
Here is the bad news…
The 50-day moving average is calculated at the end of day closing. It included “today’s” closing.
Let’s say there are no fees for buying, shorting, and selling SPY (as a proxy for the SP500) and you buy the SPY at the end of day if the SPY is above its 50-day moving average, and you short the SPY at the end-of-day if the SPY is below its 50-day moving average. That is, all trading is done at the end of day.
If, following the above rules, gains and losses are only totaled for the end-of-day close to the following end-of-day close. The return becomes very slightly positive for the “long” days and decidedly negative for the “short” days.
In other words, if you attempt to actually trade at the close of market based upon the above rules, you lose 3X money if you short as compared to long. If you just go long, based upon that rule, then you will do better just staying in the market long only.
If instead of following the above rules, you take all daily gains/losses for the SP500 at the end of day and assign those to long or short depending upon whether that day’s CLOSE is above or below the 50-day moving average, then yes, your numbers work out. But, of course, this is “looking ahead” to each day’s end-of-day close. Simply, nearly all the money is made on the turns — if you can predict them a few hours before close…. Wish I could…
One can use the price / moving average cross in a more “unique” and “specific” way, by combining it with: 1) an observation of the price / moving average relationship on “fixed” reference dates during the calendar year and 2) where that fixed reference observation lies within the four year “Presidential term cycle”.
As described in this research study https://tinyurl.com/yyf48e4q , using “June 30th” as a “reference date” for observing the price / moving average relationship, since 1933, positive forward market returns have correlated to periods when the “monthly” basis S&P 500 price has resided “above” it’s moving average value on June 30th of the given year ( chart 1 )
Conversely, since 1933, negative forward market returns have correlated to periods when the S&P 500 price has resided below it’s moving average value on June 30th of the given year, AND those periods have fallen within the first, third, or fourth year of the “Presidential term cycle” ( see chart 1 in Appendix ), and especially within the 1st Presidential year ( Table 2 ).
July – June periods commencing within the 2nd Presidential term year have produced the “highest” average positive market returns, with the July – June periods commencing within the 3rd and 4th Presidential term years producing second and third highest average positive returns ( see Table 1 Appendix ). Therefore, observing the price / moving average relationship on June 30th of the 2nd Presidential term year is “exempt” from the signaling conditions.
Further filtering of the above strategy signaling, using data measuring the spread between the 3 mo. T-bill yield and the 10 year Treasury yield, shows that, since 1960, when a rate “inversion” occurred ( 3 mo T- bill yield residing above the 10 year yield ), it coincided, with varying lead times, with some of the largest July – June declines, as indicated by the “defensive” market trend signaling periods generated https://tinyurl.com/53b7hacn
This illustrates that, in order to extract order amongst the chaos, it is necessary to use an ensemble of “variables”, in specific ways, versus an overly simplistic use of a “single” variable. And it illustrates that a “fixed” reference date eliminates an unnecessary number of false “whipsaw” signals ( signals produced by the conventional price / moving average methodology ), thus keeping capital invested in equity based assets for much “longer” periods.
In 2021, a first Presidential term year, the S&P500 price resided “above” it’s moving average value on June 30th https://imgur.com/a/aOpRvzY .