January Effect and 52-Week Highs/Lows: How to Beat the S&P 500

“The January effect is a real and continuing anomaly in stock-market returns, and one that defies easy explanation.”

Financial Analysts Journal (2006)

With December half over, it’s time to start thinking about the “January Effect.” Just to be clear, I’m not talking about the deeply-flawed “First Five Days of January Indicator” which says that how a stock market performs during the first trading week of January determines how it will perform for the entire calendar year. I briefly mentioned the 5-day January Indicator in a 2011 article entitled What’s Wrong with India’s Stock Market?” As it turned out, the 5-day January Indicator accurately predicted that India’s stock market would continue underperforming for the rest of 2011, but I digress.

Unlike the dubious 5-day January Indicator, the January Effect is an academically-proven stock-market phenomenon where small-cap and underperforming stocks near the end of one calendar year suddenly reverse course and outperform the general stock market in the January of the following calendar year. That this well-publicized phenomenon continues to occur despite being well known is interesting – the efficient market hypothesis argues that such abnormal outperformance should quickly dissipate at the hands of arbitrageurs.

Jeffrey Hirsch of The Stock Trader’s Almanac calls the January Effect “Wall Street’s only free lunch.” I would argue that diversification also qualifies as a free lunch, but Hirsch’s point is well taken. Based on 38 years of data between 1974 and 2012, Hirsch has found that a portfolio of small-cap stocks hitting 52-week lows in mid-December outperform the NYSE Composite Index (^NYA) by an average 9.5 percentage points (not annualized!) per year between late December and the January/February period. Just as impressive as the magnitude of outperformance is the frequency of outperformance — these beaten-down stocks have outperformed the NYSE Composite in 33 of the 38 years (87% of the time).

Hirsch is not the only one to find this outperformance. Studies galore have reached the same conclusion, including:

  • Ned Davis Research: Between 1996 and 2009, a portfolio of stocks in the lowest market-cap decile of the S&P 1500 composite index that are also close to a 52-week low  outperforms the S&P 500 by an average of 7.4 percentage points between mid-December and the end of January. The outperformance is much less if you exclude December and look just at January, so investing in the strategy should not wait until January.
  • Professors Eugene Fama and Kenneth French: Between 1927 and 2009, the lowest market-cap decile of stocks (average market cap of $100 million) performed more than eight times better in January than in the average of the 11 other months, whereas large-cap stocks actually underperformed in January compared to the average of the 11 other months.

Why do these December small-cap stock laggards persistently outperform in January? Hirsch attributes it to tax-loss selling by individual investors who want to dump losers before year-end in order to neutralize realized capital gains from their winning trades. But that is only one possibility, which is partially negated by the fact that since the passage of the Tax Reform Act of 1986, the tax year for institutional investors – which account for more than 70% of all stock trading — ends on October 31st, not December 31st.  What tax-loss selling does take place in December is limited to individual investors. Since the average individual investor often focuses his trading on low-priced and higher-volatility small-cap stocks, it makes sense that any tax-loss selling effect in December focuses on small-cap names. According to Columbine Capital, other causes of the January Effect may include:

  • End of the year “window dressing” by institutional investors (e.g., mutual funds) who want to eliminate embarrassing losers from their portfolio prior to their end- of-year annual reports.
  • January investment of end-of-year employment bonuses.
  • The postponing of the sale of winning stocks that experienced capital gains until January in order to defer taxes to the following year. 

Taking advantage of the small-cap January effect can be problematic if the only bargain stocks ready to pop in January are microcaps worth $100 million or less, as the Fama-French data suggests may be the case. Microcaps are often illiquid with wide bid/ask spreads that make trading in-and-out of them exorbitantly expensive. Gains from such microcap stocks can be statistical mirages based on nothing more than one trade being executed at the bid and the next trade being executed at the much-higher ask. Furthermore, as James O’Shaughnessy writes on page 53 of his investment classic — What Works on Wall Street (4th ed.):

Microcap stocks possess virtually no trading liquidity, and a large order would send their prices skyrocketing. Thus, while it is easy to assume that you could purchase and sell these securities at their listed price in the historical dataset, I believe that this is an illusion and unnecessarily gives an upward bias to the results of studies that allow their inclusion.

Simply buying a small-cap ETF like the iShares Russell 2000 (NYSE: IWM) of the iShares Russell Microcap (NYSE: IWC) doesn’t work. Over the past 11 years, the Russell 2000 index (median market  cap of $460 million) has declined in January seven times (64% of the time) and has actually performed worse than the S&P 500 a majority of the time (6 out of 11). The Russell Microcap index (median market cap of $152 million) has only been around for seven Januarys (since 2006) and it has underperformed the S&P 500 in four of those years (a majority of the time). December relative performance has been no better for IWM, which underperformed the S&P 500 a majority of the time over the past 11 years, but IWC has done much better in December, outperforming the S&P 500 in each of its first seven years of existence. Like I said earlier, however, microcap “gains” are suspect.

Fortunately, a 2010 academic paper has demonstrated that the January Effect is not limited to stocks that are microcaps or have plummeted in price! Based on the authors’ statistical analysis using regression equations, they were able to screen out un-investable microcaps under $250 million, as well as mortally-wounded penny stocks under $5.00 per share, and still be left with a stock universe that generates a substantial January Effect.

According to their regression analysis, the real determinant of the January Effect is a stock’s current relationship to its 52-week high as of the market close on the last trading day of November (i.e., less than two weeks ago!). The nearer to its 52-week high, the worse the stock performs in January and the closer to its 52-week low, the better it performs. Using this metric, small-cap stocks do not perform better than large-cap stocks, nor do the worst-performing stocks at 52-week lows perform better than stagnant stocks near 52-week lows.

This is GREAT news because it means that average investors can benefit from the January Effect with liquid, large-cap stocks! According to the authors of the paper, this blockbuster conclusion means that tax-loss selling by individual investors is not the primary cause of the January Effect. Rather, window-dressing by institutional investors is the primary cause:

When good news has pushed a stock’s price to, or near, a new 52-week high, then fund holders may perceive it to be a good investment.  On the other hand, when bad news pushes a stock’s price far from its 52-week high, fund holders view it as a poor investment. Using the 52-week high as an “anchor” when assessing the stock’s performance is a bias because fund holders do not rely on the stock’s entire cumulative return history, but rather they base their judgments entirely on the highly visible 52-week high reference price.

Fund managers are aware of this cognitive bias and have incentives to window-dress by selling stocks whose December prices are far from the 52-week high, and buying, or continuing to hold, those with December prices near the 52-week high. In January, after the reporting period has ended, prices reverse.

In fact, the study’s authors found that 52-week stocks with extremely poor price performance actually rebound less in January than 52-week low stocks with stagnant price performance. This makes sense to me since stocks that plunge in price usually have downward momentum that continues. Severe price plunges also suggest serious fundamental problems, whereas stocks that simply stagnant could just be undergoing a pause that refreshes. Interestingly, the authors also found that stocks near their 52-week high underperform in January, especially those that don’t have strong year-to-date price appreciation (i.e., momentum), so one can enhance the January Effect by not only buying stagnant 52-week low stocks but also shorting stagnant 52-week high stocks.

Using my trusty Bloomberg terminal, I screened for stocks that are in the bottom two deciles of their 52-week price range and which also have not declined by more than 20% year-to-date. As of December 23rd, ten promising candidates for January outperformance are listed below:

January Effect Stocks Near 52-Week Lows


Stock Price

Market Cap

52-Week Price Range Hi/Low Percentile

Year-to-Date Performance

Diamond Offshore (NYSE: DO) $55.39 $7.7 billion 3.3 -14.2% Oil Drilling
HCP Inc. (NYSE: HCP) $36.22 $16.5 billion 3.5 -16.0% Healthcare REIT
American Realty Capital Properties (Nasdaq: ARCP) $12.64 $2.4 billion 8.6 1.9% Retail and Office REIT
Southern Co. (NYSE: SO) $40.88 $36.1 billion 9.8 -0.1% Electric Utility
Cooper Tire & Rubber (NYSE: CTB) $22.01 $1.4 billion 10.3 -11.8% Automobile Tires
CenturyLink (NYSE: CTL) $31.36 $18.5 billion 11.8 -14.5% Telecommunications
Quest Diagnostic (NYSE: DGX) $54.05 $7.8 billion 13.4 -5.4% Medical Diagnostic Tests
Kinder Morgan Energy Partners (NYSE: KMP) $79.57 $34.9 billion 15.4 6.0% Energy pipeline MLP
Altera (Nasdaq: ALTR) $31.98 $10.3 billion 15.9 -5.6% Semiconductors
ADT Corp. (NYSE: ADT) $40.01 $8.0 billion 16.8 -12.9% Home Security

Source: Bloomberg

My top-ten list from last year outperformed the S&P 500 by 13.3 percentage points (19.8% vs. 6.5%) between December 21st and February 15th. Furthermore, the outperformance was not caused by only one or two big winners — eight out of the ten screened stocks outperformed the S&P 500. No guarantees, but I’m hopeful the current list will also outperform the S&P 500 this year.