It's been a long time since the last 400 SMA test for the S&P. It tried to test the 400 the last time that price dipped well into the 1 standard deviation band (for the 400 SMA), represented by the purple band closest to the dark purple line (400 SMA), but failed to touch it (came damn close, though).
BTW, each colored band represents 1 more standard deviation out from the mean. There are 5 bands in total, representing from 1 to 5 standard deviations away from the mean - 400 period simple moving average.
Historically, price trades between the first and second standard deviation bands for most of an uptrending period, as has happened here. However, with the rounded top and failure to put in a high as close to the second standard deviation level as were previous highs, this is showing all the signs of a market that has lost upward momentum and in need of a major support level.
The short signal happened when price closed below the 1 SD level. The first target is the major dynamic support of the 400 SMA. If that busts, we should at least get another test of it from underneath. If it busts and holds as resistance, then we're in trouble, IMO.
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Now we get tests from the downside of the 400 SMA.
Watch that second standard deviation line below the 400 SMA. Once price enters below that level, we are officially in bear market mode, as there hasn't been a single time since the early 90's that the daily price has hit that level or below without at least a -20% move immediately ensuing.
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JamesBrown
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DId I call it, or did I call it?
JamesBrown
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Chebyshev's inequality (pasted from Wikipedia)
An observation is rarely more than a few standard deviations away from the mean. Chebyshev's inequality ensures that, for all distributions for which the standard deviation is defined, the amount of data within a number of standard deviations of the mean is at least as much as given in the following table.
Minimum population Number of standard deviations from mean
50% √2
75% 2
89% 3
94% 4
96% 5
97% 6
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What does this mean?
No matter whether the sample data is normally distributed, or not, 75% of the data will fall within 2 standard deviations of the mean. In this case, only 100 candles can trade at or above the 2 standard deviation level for a 400 day look-back period. I don't want to count it out, but I'm sure you'll find that less than 100 candles are either touching or traded above the 2 SD level, over the last 400 candles.
Why do I share this?
Statistical knowledge can help us to get more of an edge over the competition (market), if we're adequately intelligent and creative enough to apply that knowledge in a useful way.
This shouldn't be too difficult for you to figure out... good luck :)
JamesBrown
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Hint: square root of 2 comes into play here with the daily S&P 500 chart.