December is a generally good month averaging about a 1.5% rise in the S&P, and having declined only 7 out of the last 26 years since 1979.

  • The biggest decline during this stretch came in 2002 with a 7% decline, which had been preceded by a 20% decline over the previous 11 months, and the next biggest decline was of 4% coming in 1980, following a 30% rise over the preceding 11 months. The biggest rise came in 1991 which was 11%, and followed a 10% rise over the preceding 11 months. The second biggest rise of 6% came in 1987, which was preceded by a big decline of 4% in the preceding 11 months. Thus, big declines come after big rises and big declines, and big rises came after big rises and big declines — in aggregate there is certainly not a linear relationship. All one can say about the extent to which this is non-random is that about half the moves were approximately 1% rises, and there were a few outliers that followed enormous rises and declines from the preceding 11 months.
  • An attempt to get proper percentage changes, and proper adjustments for a series like this shows the need for careful work. The S&P Index started out at around 108 in year end 1979 and now is at 1400, but the algebraically adjusted futures (the only way to go), started out at approximately 600. Any calculations that do not take into account the influence of dividends and levels on studies like this are woefully inadequate.
  • A look at adjusted S&P futures shows that, from November 1998 when they stood at 1400 to date, a buy and hold strategy would have broken even. It is no wonder that there is so much potential for people who have missed the boat — for the Abelprechflecfals of the world to join the party and create a big move or to catch one up.
  • Some of the changes this year are somewhat inconsistent with the 10% yearly volatility one would compute from extrapolation of daily variations. There is a nice 30% move in the first 11 months of 1980, a rise of 31% in 1995, and four other changes of approximately 25% for the year during the test period. The problem with selling calls and covered writes is clearly indicated by these moves, as is the reason this is all so popular on Wall Street, causing the public to lose much more than they have to lose.
  • The Astronomer Royale, Dr. Kim Zussman, has performed a nice regression with an r2 of 8%, showing that the first 11 months is positively correlated some 30% with the next month. Unfortunately, with small numbers like this, a non-linear relationship and a few 30 percenters contributing to the sum of squares, this is not overly meaningful and certainly not predictive.
  • I am often asked the proper way to learn to count. A good way to do it is to wrestle with monthly adjusted prices and unadjusted prices and do some calculating … In fact, I propose a method. Start with 1979 year end, as 1969 year end or anything else is much too far back to be relevant to anyone but the chronic bears. Consider four hypotheses as to the predictive powers of December:
    1. Compute a regression prediction of December based on all the data available up to that time. For example, in 1982 you would have two observations, 1980 and 1981. In 1983, you would have 1980, 1981 and 1982 to fit.
    2. Compute the average move in the Decembers up to that time and predict that the next month will be the same.
    3. Compute the average move in the last three Decembers, and predict that the next month will be the same as this.
    4. Take the prediction generated by the first three methods each year and find which one has the best forecasting record in the past, and use that method for the next prediction.

    Now you have four methods of prediction. Does any beat just predicting the average change from month to month based on simulation, by a reasonable amount. If you want to make money, or test seasonality properly you have to use your head.

  • Some of the years are amazing in retrospect. There was 1997 where some people, I am told, lost a lot of money in Thailand and elsewhere from the bull side. Yet the market went up 26% in that year. There were the ‘5 years of 1985 and 1995 where the market pushed up 30% on the year. Also the year 1987, where the market was actually making a comeback in December. There was a run of fantastic rises in 1995 to 1999 pushing 20% or more in each one.
  • As we have seen the market went from 100 to 1400 during the 26 year period that I have reviewed. Were there any negatives in any of these years, and were they more or less than the present? Are they counterbalanced by any positives or has this been discounted, and is this more or less bullish than usual?
  • There would seem to be a tendency for the market to do well in December over the years. Is this due to the generally optimistic spirit that most of us have in December and is there more than one way to make a profit from this?
  • Year Adjusted Futures Move for first 11 Months (%) Adjusted Futures Move in December (%) Start of Year S&P Index
    1980 30 -04 108
    1981 -09 -03 136
    1982 13 01 122
    1983 15 -01 141
    1984 -03 01 165
    1985 20 05 167
    1986 20 -03 211
    1987 -04 06 242
    1988 10 01 247
    1989 25 01 278
    1990 -10 01 354
    1991 08 10 330
    1992 03 01 417
    1993 08 01 435
    1994 -02 01 466
    1995 30 01 459
    1996 25 -02 616
    1997 25 01 741
    1998 15 05 971
    1999 12 04 1229
    2000 -10 03 1469
    2001 -15 01 1320
    2002 -20 -07 1148
    2003 15 04 880
    2004 06 03 1112
    2005 05 -0.5 1211
    2006 09   1248

    Dr. Kim Zussman adds:

    Looking further at the same monthly data, December moves seem large compared to the prior 11 months. To check this (and eliminate effects of sign), for each year I looked at the ratio of absolute values:

    |Dec ret|/|J-N ret|

    One would expect each month to contribute something like 1/11 of the return of the prior 11 months. But Decembers are larger, as shown by the data:

    Year Jan-Nov Dec |Dec|/|j-n|
    2005 0.031 -0.001 0.031
    2004 0.056 0.032 0.583
    2003 0.203 0.051 0.250
    2002 -0.184 -0.060 0.327
    2001 -0.137 0.008 0.055
    2000 -0.105 0.004 0.039
    1999 0.130 0.058 0.445
    1998 0.199 0.056 0.283
    1997 0.290 0.016 0.054
    1996 0.229 -0.022 0.094
    1995 0.318 0.017 0.055
    1994 -0.027 0.012 0.450
    1993 0.060 0.010 0.169
    1992 0.034 0.010 0.296
    1991 0.136 0.112 0.819
    1990 -0.088 0.025 0.281
    1989 0.246 0.021 0.087
    1988 0.108 0.015 0.136
    1987 -0.049 0.073 1.487
    1986 0.180 -0.028 0.158
    1985 0.209 0.045 0.216
    1984 -0.008 0.022 2.733
    1983 0.183 -0.009 0.048
    1982 0.130 0.015 0.117
    1981 -0.069 -0.030 0.434
    1980 0.035 -0.034 0.966

    The attached plot depicts |Dec|/|J-N| vs. date, and though variability in this fraction has damped out over time, it still seems high. Even discarding two out-lying years of ‘83 and ‘87, the mean ratio is 0.26; almost 3 times 1/11.

    Rick Foust comments:

    I suppose that there are two major factors (amongst other smaller ones) that cause the December effect.

    The first is money flowing into IRAs prior to the end of the year. Someone on the retail side of the business could confirm or refute this.

    The second is large fund rebalancing. Some funds operate on the basis of maintaining a fixed ratio in various asset classes (percent stocks to percent bonds…). Periodic rebalancing of the ratios forces them to buy the asset class that has done poorly and sell the asset class that has done well. It seems that rebalancing predominantly takes place towards the end of the year. Surely there is someone here that could confirm or refute this.

    Scott Brooks offers:

    IRA fund flow is bigger towards the end of March thru about April 20th or so than it is in December (I say April 20th because the envelope the IRA deposit check is mailed in need only be post marked April 15th).

    One can also look at index reconstitution as issues are dropped and others added to the indexes. However, this has the greatest effect on the smaller issues (smaller in terms of cap weighting). Most larger capitalized stocks are going to stay in the index and could be bought in an effort to rebalance a portfolio fund back into the index weighting.

    As a result, the index funds have to go thru a flurry of rebalancing, selling the issues dropped from the index and buying those that are added….and proportionalizing those stocks that stick (again, mainly the largest capitalized issues).

    Something else to consider (for both money managers and individuals) …

    Stocks that have a loss are often sold to realize capital losses to offset the fact that …

    Stocks that managers or individuals feel have run their course and have a gain are sold.

    Another phenomenon that occurs are RMD’s (Required Minimum Distributions) for those with qualified money that are over 70. This is a forced sale for no other reason than realizing taxable income. What’s interesting is that this now becomes money in motion and as a result, opportunity to invest in other areas. As the baby boomers age, this will become more and more of a factor … especially since such a large number of boomers bought into the myth that they will retire in a lower tax bracket than when they were working.

    I’m sure there are are many other reasons that our resident bond mavens and options experts (as well as anyone smarter about the market than I) could add to this discussion

    An Anonymous Contributor says:

    In his post Kim Zussman wrote that:

    Looking further at the same monthly data, December moves seem large compared to the prior 11 months. To check this (and eliminate effects of sign), for each year I looked at the ratio of absolute values:

    |Dec ret|/|J-N ret|

    One would expect each month to contribute something like 1/11 of the return of the prior 11 months.

    No, one wouldn’t. Since you already have all the data, go ahead and look at every month relative to the other eleven months of the same year (or to the preceding eleven months, it won’t make much of a difference). My own back-of-the-envelope calculations with unadjusted data show a mean of about .22 over all months, with December being somewhat below average.

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