January Effect: What It Is in the Stock Market, Possible Causes (2024)

The January effect is the name given to the belief in a seasonal increase in stock prices in the first month of each year. People have generally attributed a supposed rally each January to the rise in buying that follows the price drop that typically happens each December. However, data for this phenomenon over the last several decades has proven elusive.

Some argue that at the end of each year, investors tend to sell off securities at a loss to offset their capital gains and lower their tax bills, prompting a sell-off. After the New Year, they repurchase the stocks, creating a greater demand for a range of shares in the market, leading to the January effect. Another explanation for the phenomenon is that investors use year-end cash bonuses to buy investments the following month. While this market anomaly has been identified in the past, the January effect has disappeared in recent years, if it ever existed, and studies of previous eras have shown it correlated less with lower prices in December than with continuing bullishness during the last months of the previous year. In short, the evidence doesn't seem to match the explanations.

Understanding the January Effect

Investment banker Sidney Wachtel is said to have first noticed the January effect in 1942. Like all calendar-related effects, the hypothesis suggests that the markets are inefficient since efficient markets would naturally make this effect disappear.

Our own look back at the SPDR S&P 500 ETF (SPY) since its 1993 inception makes one wonder how the term ever came to be used. Of the 30 years since, there have been 17 winning January months (57%) and 13 losing January months (43%), making the odds of a gain slightly higher than the flip of a coin. Further, from the start of the 2009 market rally through January 2023, January months showed seven positive vs. seven losing months, a 50%-50% split. Given the strong rally since 2009, one might rightly expect a more pronounced number of January winners, but this has not been the case.

The first month of the year turns out not to be a particularly compelling trading month out of the year, with middling performance at best. Historically, according to data cited by Nasdaq, it's been in positive territory but ranks eighth out of the 12 months over the last 20 years.

January Effect Explanations

Besides tax-loss harvesting with post-New Year repurchases and investors putting cash bonuses into the market, another explanation for the January effect has to do with investor psychology. Some investors argue that January is the best month to begin an investment program or that many are following through on a New Year's resolution to begin investing for the future.

Others have posited that mutual fund managers buy the stocks of top performers at the end of the year and get rid of losingassets forthe sake of appearances in their year-end reports, an activity known as "window dressing." This is unlikely, however, since trading would primarily affect large caps, and the effect, when found, has been seen as greater in small caps.

Year-end sell-offs could attract buyers interested in the lower prices, knowing that the dips are not based on company fundamentals. On a wide enough scale, this could drive prices higher in January.

Rebecca Walser, named by Investopedia as a top advisor for 2023, is skeptical that the theory has "statistical validity." But, she adds, if there's anything to it, she would "attribute it much more to human psychology than tax loss harvesting or mutual fund window dressing."

Studies on the January Effect

Studies on the January effect generally back Walser's view. The effect has long been one of the wider-known market anomalies, so it's no surprise that it's given rise to a wealth of studies. A look back should give us some humility when citing truisms about the market—like the dumping of stocks in December leads to a bullish market in January—that have become outdated or might have been misidentified by previous researchers in the first place. For example, as we've seen, it's never been clear that sell-offs in December led to purchases in January since the better-traded January months correlate to better December trading months, not those that had massive sell-offs.

Until the early 2000s, most researchers accepted the January effect as an empirical fact, focusing less on proving its existence and more on understanding its nuances, such as its precise timing and varying degrees of impact over time. Were there parts of the month that packed the biggest punch? Was there more or less of a January effect over time? Given this acceptance, some scholars began to explore whether the market was inherently riskier in January, hypothesizing that the higher returns were a reward for those willing to invest during this period. Others became interested in correlations between the January effect and any positive returns for the rest of the year. Alternatively, some used the "known fact" of the January effect to prove a December effect, which then gave rise to a whole other set of studies. Still more moved beyond tax-harvesting and traditional stock market explanations, bringing the research into controlled laboratory settings to uncover the supposed underlying behavioral drivers at work in the effect. Others responded to some saying the data for the effect was hard to discern by arguing that perhaps a broader January effect lacked evidence. It could be detected in small-caps or specific markets.

Amid all this work and the yearly publication of evergreen articles on the effect in media outlets starved for content during the holidays leading into the New Year, separate groups of researchers raised a critical point. They suggested that what was perceived as the January effect might have been merely statistical noise, the result of "overfitting" and data mining to find effects that were not real market phenomena, thus challenging the foundational assumptions of previous studies.

Criticisms of the January Effect

January effect skeptics have primarily focused on the lack of recent data showing its continuing impact, problems identifying its causes, and how it's become moot given the evolution of financial markets. Let's take these in turn:

• Diminishing significance: Most studies show that the January effect has become less pronounced. Other than suggesting the effect wasn't real to begin with, one idea is that as investors became aware of this trend, they adjusted their strategies accordingly, which decreased its influence over time. This suggests that the January effect may be more of a historical anomaly than a reliable market indicator.
• Impact of market efficiency: The efficient market hypothesis argues that it is impossible to outperform the stock market because the market will "catch up" to reflect all relevant information. Momentary anomalies are just that, and this is more so with the advent of high-frequency trading and sophisticated algorithms that would exploit and correct for the January effect if it existed.
• The effect is related to small-cap stocks: Some have sought to rescue some form of the January effect by pointing to this or that part of the market as having data to back it up. Several studies have observed the effect in small-cap stocks, which are generally more volatile and riskier. This raises questions about the broader applicability of the effect across different market segments and whether one can make any risk-adjusted returns exploiting it.
• Problems with the tax-loss harvesting hypothesis: Some have argued that the January effect results from investors selling securities at a loss in December for tax purposes, then buying them back in January, artificially inflating prices. Critics point out that this behavior is inconsistent each year, though the tax conditions are and would vary for individual traders anyway, given their specific tax situations and broader economic conditions.
• Changing market dynamics: Financial markets continually evolve with new investment instruments, regulations, and investor behavior. These changes can render past patterns like the January effect if they existed, obsolete as new dynamics emerge that were not present during the times when the effect was first observed. For example, while it could be that tax-loss harvesting made sense over previous periods, individual retirement accounts and other tax shelters make pocketing such losses at the end of the year largely a thing of the past for many investors.

The Bottom Line

The January effect is a market theory suggesting that January often has consistent gains, though the evidence for it has been elusive in recent decades. Despite this, market commentators frequently cite it to explain any positive performance in January. They often link January's buying activity to post-year-end tax-loss sales. However, the relevance of this rationale has greatly diminished over time as more investors shift to tax-sheltered plans like 401(k)s.

Traders are advised to approach the January effect skeptically and focus on the prevailing market conditions as the year turns rather than relying on this increasingly questionable market lore.