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Analysis of S&P 500 Returns Above & Below The 200 Day SMA $SPY $SPX

The 200 day SMA is a widely watched indicator of health for the U.S. Stock market.  When price is trading above the 200 day SMA, most market participants can agree that a longer term up-trend is either in place or developing.  When price is trading below the 200 day SMA, most people recognize that the up-trend has stopped or is reversing.  That being said, it’s dangerous to make generalizations about an indicator like the 200 day SMA without understanding the potential risks.

Over the past few weeks we’ve seen some volatility come back into U.S. Equities while they hang around all time highs.  The S&P 500 ($SPY) has bounced around the 50 day SMA and could potentially be coming down to visit the 200 day Simple Moving Average.  The chart below is a weekly chart for the S&P 500 ETF ($SPY) with two simple moving averages that approximate the 50 day (10 weeks) and 200 day (40 weeks or 10 months) moving averages.  A brief glance at the chart shows us that $SPY has only come down to test the 200 day moving average once since 2012.

S&P 500 Weekly Chart

What does it mean?

One of the obvious lessons from a longer term chart is that when price is trading above the 200 day simple moving average, price is likely to advance.  The challenge is quantifying that advance and knowing what to expect.  As a result, we’re going to look at 20 years of total returns in the S&P 500 ($SPY) based on it’s location relative to the 200 day SMA.

The table below summarizes the total monthly returns for the S&P 500 from 11/1/1993 to 12/1/2014.  What we see from looking at the table is that when $SPY is trading above the 200 day simple moving average, it returned around 1.22%.  Additionally, that monthly return was accompanied by a lower volatility in returns as indicated by the 3.44% standard deviation of monthly returns.

On the other hand, it’s surprising to see that the average monthly return wasn’t horrible when $SPY was trading below the 200 day simple moving average.  That return came in at -0.15% on average.  However, the 5.89% standard deviation of monthly returns shows us that there was significantly more volatility in returns.  The minimum and maximum monthly returns both took place while price was trading below the 200 day simple moving average.
SPY Returns above below 10 month
In addition to looking at the table, it’s helpful to look at a distribution of the the returns.  The image below shows the distribution of total monthly percentage returns.  It’s worth noting that over the look-back period, the S&P 500 has spent more months above the 200 day (10 month) simple moving average.  The distribution also shows us that when price is trading below the 200 day simple moving average, negative monthly returns of -5% or less are much more likely to occur.

Distribution of SPY Returns

A word of caution:

All studies of historical data are a product of past performance.  Intuitively, we understand that, but it’s important not to make generalizations without understanding the context of the present relative to the past.  In the case of the S&P 500, we’re looking at a market that is currently trading near an all time high with a 200 day SMA that is also at an all time high.  That observation skews the data and the returns to the upside.

Proponents of buy and hold could potentially use the numbers above to justify holding positions even though price is trading below the 200 day simple moving average.  After all, the average monthly return when price is trading below is just -0.15%.  The danger in that strategy is that maintaining a long position while price is trading below the 200 day SMA comes with larger drawdowns and a greater likelihood of drawdown.  Knowing that, owning stocks when price is below the 200 day SMA is not the most productive use of capital.

For additional investing insights check out this post:  Investing.  Here’s a plan to stop doing it wrong

  • evo34

    What do you mean by “monthly returns?” For every trading day that the close is > 200d SMA, you compare to the price on the same calendar date for the next month? That would be one of the right ways to do it. It looks like you are doing something much different, though. Are you just checking first vs. last day of each month, and whether the first day was above or below the 200d MA? That would be ignoring about 97% of your potential sample.

    • Hi and thanks for the comment. I’m using the 200 day / 10 month value somewhat loosely and interchangeably in this article. What I’m looking at is the monthly return rather than the daily return. Additionally, I’m using a price based moving average, but looking at the total return (including dividends) for holding $SPY. Hope that helps and thanks for reading.

      Best,
      Dan

      • evo34

        Please define “monthly return.” Are you just looking at the first day of every month and comparing to first day of the next month?

        • Hi,

          Yes, you’re correct. I used monthly adjusted close data from Yahoo Finance, which gives us the adjusted close on the first trading day of every month. Thanks.

          Dan

          • evo34

            Then my original comment stands. You’re using arbitrary calendar dates to remove 97% of your potential sample. There is no reason to measure “monthly returns” using only the first days of the months as start dates.

  • Mike

    You sparked some thoughts and I did a similar analysis …. looked at SPY from 1/29/1993 – 1/2/2015 … which is 265 monthly price points and calculated 255 ten month moving averages and one month forward returns.

    For this period it looks like the adjusted close is above the ten month SMA 191 out of 255 (75%) months and the average one month forward return is about 1.2%. Of those 191 one month forward returns, 61 (32%) are negative and average 2.8% loss. 130 (68%) have positive one month forward returns and average 3.1%.

    When the adjusted close was below the SMA the one month forward return was almost equally split … 33 were negative and averaged a 4.9% loss and 31 were positive and averaged a 4.6% gain. The overall average was a .3% loss.

    I’m not quite sure what this tells me though. When the market is in a long-term uptrend … then of course the adjusted price will be above the SMA and the one month forward return will be positive.

    This would be interesting to look at for different parts of the business cycle (up markets, down markets, sideways markets, full business cycles) and for annualized forward returns longer than one month.
    Regards! Mike

    • Hi Mike,

      Thanks for sharing, that’s really interesting. My guess is that we were using essentially the same data set. When I ran the test, I applied the SMA to the standard close and used the adjusted close data for the returns. My reasoning is that we’d normally use the standard close for the SMA, but receive the benefits of dividends if we were long.

      Your idea about different market conditions would be good to see as well. I think the biggest challenge with that study would be coming up with some way to define the different market conditions and the business cycle. Maybe some measure of the change in GDP? At any rate, interesting stuff and thanks again for sharing!

      Best,
      Dan