# This Bear Market Is Really Just A Regression To Trend

About the only certainty in the stock market is that, over the long haul, over performance turns into under performance and vice versa. Is there a pattern to this movement? Let’s apply some simple regression analysis (see footnote below) to the question.

Below is a chart of the S&P Composite stretching back to 1871 based on the real (inflation-adjusted) monthly average of daily closes. I’ve using a semi-log scale to equalise vertical distances for the same percentage change regardless of the index price range.

The regression trendline drawn through the data clarifies the secular pattern of variance from the trend — those multi-year periods when the market trades above and below trend. That regression slope, incidentally, represents an annualized growth rate of 1.72 per cent.

The peak in 2000 marked an unprecedented 155 per cent overshooting of the trend — nearly double the overshoot in 1929. The index had been above trend for two decades, with one exception: it dipped about 10 per cent below trend briefly in March of 2009. But at the beginning of June 2012, it is 38 per cent above trend, down from 40 per cent at the end of the previous month. In sharp contrast, the major troughs of the past saw declines in excess of 50 per cent below the trend. If the current S&P 500 were sitting squarely on the regression, it would be around the 954 level. If the index should decline over the next few years to a level comparable to previous major bottoms, it would fall to the mid-400s.

Footnote on Calculating Regression: The regressions on the Excel charts above are exponential regressions to match the logarithmic vertical axis. I used the Excel Growth function to draw the lines. The percentages above and below the regression are the calculated as the real average of daily closes for the month in question divided by the Growth function value for that month minus 1. For example, the monthly average of daily closes for June was 1323.48. The Growth function value for the month was 956.57. Thus, the former divided by the latter minus 1 equals 38.4 per cent, which I rounded to 38 per cent.

Footnote on the S&P Composite: For readers unfamiliar with this index, see this article for some background information.

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