By LARRY SWEDROE
The January effect is a seasonal anomaly in which small stocks have higher returns than in any other month. This calendar effect could create an opportunity to buy these stocks before January and sell them after their value has risen. The effect was first observed around 1942 by investment banker Sidney Wachtel. The most common explanation for this anomaly is that tax-sensitive individual investors, who disproportionately own small stocks, sell stocks for tax reasons (harvesting losses) at year’s end and reinvest after the first of the year.
As with all anomalies, the January effect suggests that the market is not efficient—as market efficiency would cause the effect to disappear once uncovered. Before digging into the historical evidence, it’s important to note that the costs (such as bid-offer spreads, commissions and market impact costs, which are greater in small stocks) of exploiting an anomaly can be greater than the size of the anomaly itself. Thus, what are referred to as “limits to arbitrage” can create hurdles that are high enough to allow anomalies to persist because the costs of trading against the anomaly exceed the profit opportunity. We turn now to examining the evidence.
Over the 95-year period 1927-2021, in the month of January small stocks outperformed large stocks (the size premium) by a highly significant 2.1 percent (t-stat = 6.1). Over all months, the premium was just 0.2 percent (t-stat = 2.2). The difference of 1.9 percent was highly significant (t-stat = 5.3). However, until 1975 the two-way transaction cost (spread plus commission) averaged about 2 percent, fully offsetting the size premium in the month of January. And that 2 percent figure was the average cost of a trade. Given the lesser liquidity of small stocks, the costs of trading them would have been significantly greater, more than offsetting the size premium during the period. Now let’s look at the January effect over the first 45 years of the period, 1927-71. I chose the end point so that we can then look at data for the last 50, 30 and 20 years.
Over the period 1927-71, in the month of January small stocks outperformed large stocks by a statistically significant 2.8 percent (t-stat = 6.5). Over all months, the premium was 0.3 percent (t-stat = 1.9). The difference was highly significant (t-stat = 5.6). Now let’s turn to examining the January effect over more recent time periods—periods that have witnessed significant reductions in trading costs, which have reduced the limits to arbitrage.
Over the 50-year period 1972-2021, in the month of January small stocks outperformed by more than they did in other months, but the anomaly shrunk. During this period, they outperformed in January by a statistically significant 1.4 percent (t-stat = 2.8). Over all months, the premium was a statistically insignificant 0.1 percent (t-stat = 1.2). The difference was statistically significant at the 5 percent level (t-stat = 2.4). Note that in 1975 the era of fixed commissions ended, reducing trading costs, reducing the limits to arbitrage, allowing the market to become more efficient. Now let’s look at the performance of the anomaly over the last 30 years to see if it continued to shrink.
Over the 30-year period 1992-2021, in the month of January small stocks continued to outperform by more than in the other months. However, we see that the anomaly continued to shrink. During this period, they outperformed in January by a statistically insignificant 0.8 percent (t-stat = 1.3). Over all months, the premium was a statistically insignificant 0.1 percent (t-stat = 0.8). And the difference was no longer statistically significant (t-stat = 1.0). Then another major development reduced trading costs and thus the limits to arbitrage—in January 2001, stocks began trading in single digits instead of in fractions, such as one-quarter or one-half. Once again, that lowered the cost of trading. With that in mind, let’s turn to the performance of the January effect over the last 20 years.
Over the 20-year period 2002-2021, in the month of January small stocks continued to outperform by more than they did in other months, but the degree of outperformance was now smaller. During this period, they outperformed in January by a statistically insignificant 0.4 percent (t-stat = 0.7). Over all months, the premium was a statistically insignificant 0.2 percent (t-stat = 1.1). The difference was statistically insignificant (t-stat = 0.4). During this period, we saw the rise of high-frequency traders who, through their actions, lowered the bid-offer spreads and thus reduced the limits to arbitrage.
The bottom line is that as the transaction costs, and thus limits to arbitrage, have come down dramatically, the anomaly has shrunk dramatically and is no longer of statistical significance. In addition, even with today’s much lower cost of trading, the January effect has shrunk to a level that it is not exploitable after expenses. This is just another example of The Incredible Shrinking Alpha, explaining why it has become persistently more difficult for active investors to generate alpha — the January effect may once have been a source of alpha for active managers (although the evidence on trading costs calls that into question), but that is no longer the case.
For informational and educational purposes only and should not be construed as specific investment, accounting, legal, or tax advice. Certain information is based upon third party data which may become outdated or otherwise superseded without notice. Third party information is deemed to be reliable, however its accuracy and completeness cannot be guaranteed. Information from sources deemed reliable, but its accuracy cannot be guaranteed. By clicking on any of the links above, you acknowledge that they are solely for your convenience, and do not necessarily imply any affiliations, sponsorships, endorsements or representations whatsoever by us regarding third-party websites. We are not responsible for the content, availability or privacy policies of these sites, and shall not be responsible or liable for any information, opinions, advice, products or services available on or through them. The opinions expressed by featured authors are their own and may not accurately reflect those of the Buckingham Strategic Wealth® or Buckingham Strategic Partners®, collectively Buckingham Wealth Partners. Neither the Securities and Exchange Commission (SEC) nor any other federal or state agency have approved, determined the accuracy, or confirmed the accuracy of this article. LSR-22-257
LARRY SWEDROE is Chief Research Officer at Buckingham Strategic Wealth and the author of numerous books on investing.
ALSO BY LARRY SWEDROE
Should value strategies adjust for intangibles?
Is social media making markets more efficient?
Active versus passive all boils down to cost
Do dividend-paying stocks hedge against inflation?
ESG strategies: do risk factors explain returns?
Have you discovered The TEBI Podcast? You’ll find it on SoundCloud, Spotify, Apple Podcasts, Podbean or your preferred podcast provider.
© The Evidence-Based Investor MMXXII