FYI: We are getting a colon irrigation today, a kind of cleansing of an over stuffed portfolio hang over from 2013's big profitable year. But not to fear, we have four more days to go.
When the S&P500 has a net positive gain in the first five trading days of the year, there is about an 86% chance that the stock market will rise for the year, it has worked in 31 out of the last 36 years (as of 2006). The five exceptions to this rule were in 1966, 1973, 1990, 1994, and 2002. Four out of these five years were war related, while 1994 was a flat market. As history suggests, the markets average nearly 14% gains when the January Effect is triggered.
On the flip side of the coin, when the first five days of January are lower, there is no statistical bias of the market, up or down. It is anyone’s game at that point. Not a very reliable indication.
Regards,
Ted
Comments
Thanks for reminding us of the January Effect. It is commonly accepted market wisdom that as January equities go, so goes the equity market for the remainder of the year. A positive January foretells above average annual equity rewards; a negative January portends a neutral market return. Maybe so, maybe not.
That interpretation is not without its critics from academia and from financial journalists. Of course, the perceived wisdom is based totally on empirical data. Like all statistics, it depends on the selected data collection period. Therefore one controversy is the relevant data period.
The original finding was based on a much shorter timeframe than is now currently accessible. Should the assessment include all data since the 1920s or should it be restricted to more recent performance since the end of World War II? This is a valid issue, especially since different timeframes will generate disparate conclusions.
A second issue is the current usage of the original January Effect. It is now interpreted as a market-wide equity effect. The original research only focused on the Small Cap market segment’s excess performance. Mark Hulbert and Jason Zweig have excellent articles on this topic. Here are the Links:
http://www.marketwatch.com/story/how-to-play-the-january-effect-2012-01-04
http://www.jasonzweig.com/uploads/1.07JanEffect.pdf
Liz Ann Sonders is one of many practitioners who morphs the original limited findings to the overall market projections. Here is her short study summary:
http://www.metalsnews.com/Metals+News/BusinessInsider/The+Business+Insider+The+Money+Game/HEADLINE718344/A+Review+Of+The+Stock+Market+January+Effect+Since+1928.htm
Ted, I admit that I risk triggering your penetrating ire, but essentially all this work is completely tied to statistics and a little Probability Theory. No fundamentals or financial models explain this anomaly. Most folks do not recognize that they are solely applying empirical observations organized in a statistical format.
From historic market data, we anticipate a 70 % likelihood that the equity market will grant positive returns in 2014. If the market delivers a positive January, that likelihood must increase above the 70 % baseline estimate. Additional data changes the odds. In the extreme, if the market is strongly positive near the end of December, the probability of a positive reward at the end of the year approaches a 100 % certainty.
We are just applying a principle that a mathematician calls “Conditional Probability”. We are updating our projections as the data stream makes itself available, and the outcome becomes more in focus.
The probability of a thrilling sports comeback diminishes towards zero as time expires. Typically, sports fans abandon the event in favor of a local watering hole as they informally assess the Conditional Probabilities, and conclude that a victory is highly unlikely.
To illustrate how data collection changes probabilities, textbooks often use a classic colored Balls in Urn problem. Two identical urns are present. One (Urn A) has 70 % Red balls with 30 % white balls; Urn B has the opposite ball distribution.
Without any data, the probability of choosing the red ball dominated urn is 50 %.
If 12 balls are experimentally withdrawn from one urn with a distribution of 8 red and 4 white balls, what is the likelihood in percentage units that you drew from the heavily populated red ball Urn A? Give it a try.
Most folks underestimate the probability. That’s because of an anchoring behavioral instinct.
If you were a Probability student you would know that a formal Conditional Probability equation exists to yield a solution. I surely do not recall that equation. But simple combination and permutation analyses that is taught at the High School level can also provide the answer. The calculation is easy.
The likelihood that the 12 ball sample was drawn from Urn A is a startling 96.7 %. Sorry for the three digit answer; probability estimates are never that precise in the real world. If a different set of balls were randomly withdrawn, the revised conditional probabilities would change depending on the specific distribution of the sampled balls.
The general lesson is that collecting just a small sample of additional data can greatly enhance chances of making a more informed and more correct decision. Statistics and Probability Theory are the workhorse tools in any such effort.
If you wish, I will provide the simple details of my calculations that permitted a correct probability estimate.
Change is a constant in the marketplace. As John Maynard Keynes noted “When the facts change I change my mind. What do you do sir?”. Like Keynes, I too change.
The dynamic markets demand flexibility in both thinking and in action. Statistical analyses and Probability Theory are the perfect tools to address and to understand the uncertainties of future market outcomes. Regardless if used formally or informally, if deployed either consciously or subconsciously, this tool set is one of the few reliable techniques for successful investing.
In the end, I will monitor the January data, and I will make minor portfolio adjustments according to the signals produced. I’ll loosely follow the data with some approbation of its insights and some appreciation of its shortcomings.
Best Regards.
Regards,
Ted