January is here again and market commentators are already telling stories about the so-called January Effect. Some articles (examples here
) are saying the effect is an illusion, while others are claiming the effect can help you make some profits (examples here
). Before we dig into the academic research on the subject, let’s first understand the January Effect. Put simply, the January Effect is a term for the observation by some researchers that certain types of stocks (e.g., value
and/or small size
) earn abnormally high returns in January. A good example of this research is from a 1996 FAJ article by Bob Haugen (rest in peace!) and Philippe Jorion.
Source: FAJ 1996. Note the strong performance of smaller stocks in the month of January (highlighted via the red circle). The results are hypothetical results and are NOT an indicator of future results and do NOT represent returns that any investor actually attained. Indexes are unmanaged, do not reflect management or trading fees, and one cannot invest directly in an index.
But is the January Effect Real?
As we pointed out last year
, researchers are still debating the merits of the January Effect. In this piece , we’ll step back and reflect on the extensive academic research published on the January Effect. I’ll end with a recommendation for investors entertaining the idea of using the January Effect as part of their investment process. The research on stock return seasonality likely extends back to when stock markets were invented. Nonetheless, one early piece by the Harvard Committee on Economic Research (published in 1919
) shows that there are no seasonal effects in stock returns from 1897 to 1914. Sidney B. Wachtel, who published a paper
in 1942, found something different: Professor Wachtel identified that tax considerations can lead to seasonality in stock returns and do
generate a January Effect. Next up in the January Effect debate were Michael S. Rozeff and William R. Kinney, Jr., a group of economists who published
a more comprehensive empirical investigation of Wachtel’s initial ideas in 1976. Rozeff and Kinney examine stock returns from 1904 to 1974 and confirm Wachtel’s finding — the January Effect is real! But the debate raged on. Early skeptics of the January Effect include Richard Roll, Don Keim, and Marc Reinganum, all of whom published papers in 1983 (here
, and here
, respectively). The collective work of these researchers showed that January returns are limited to smaller firms, implying that the January Effect was not as pervasive as previously thought. Of course, more recent studies in 2004, by Honghui Chen and Vijay Singal
, and another by Mark Grinblatt and Tobias J. Moskowitz
, leverage better analytical techniques and 1) confirm the existence of a January Effect and 2) tie it to year-end tax-loss selling.
Is Tax-Loss Selling Driving the January Effect?
But if taxes are driving the January Effect, can we find evidence for this hypothesis? Jay Ritter digs a bit further into this question
and examines the buying and selling of individual investors near the turn of the year. By measuring the ratio of buys and sells of individual investors, he finds that individual investors sell more near the end of the year, and buy more in the beginning of the year—so a seasonal pattern exists for individual investors, who tend to hold smaller stocks. In two different academic papers, James Poterba and Scott Weisbenner
and Richard Sias and Laura Starks
, confirm the findings from Jay Ritter: individual investors engaged in tax-loss selling contribute to the January Effect. But the tax-selling hypothesis isn’t a done deal. Early research by Philip Brown, Donald Keim, Allan Kleidon, and Terry Marsh examine
the tax-induced January Effect hypothesis in the Australian equity markets. At the time, Australia had similar tax laws to the US, but a June-July tax year. In theory, if tax incentives were the cause of the January Effect, the authors should find a “July Effect.” But that wasn’t the case. The evidence shows that Australian equity returns have the same January effect
documented in U.S. markets. The analysis in this paper raises a few possibilities: 1) The January Effect is an artifact of data-mining, or 2) researchers still don’t understand why the January Effect exists.
The Reality of the January Effect: Who Knows
Clearly, there has been a lot of research on the January Effect (and we’ve only touched the wave tops!). On net, the research suggests the January Effect may have some mojo, but there are plenty of questions on the topic. Bottomline:
Most investors are better off not paying attention to the January Effect. Instead, investors should focus on what they can control: 1) Identify their goals, 2) maintain a long-term horizon, and 3) keep things simple.