The January effect is a calendar anomaly connected with the stocks with small market capitalization. The anomaly itself is old (Keim,1983); therefore, it has been widely researched and is well-known in the academic world or between practitioners. The anomaly says that returns of the small-cap stocks are particularly strong in January. Although the strategy based on this anomaly is well-documented, the strategy is connected with certain problems. Firstly, there were unusually high January returns during the 1960s and 1970s or the years which formed the sample examined by Keim (1983) in his seminal study and which are frequently used as a benchmark in studies of the temporal behavior of the anomaly. However, this paper has found, the magnitude of the effect quite similar to what it was before the spike.
Moreover, the evidence does not suggest that investors are learning of the effect and are arbitraging it away. Additionally, the effect should be present at all the major stocks exchanges (NYSE, AMEX, and NASDAQ – if we would consider the small stocks). But in the last several years, the returns were very low.
In the recent period, the January effect was so small that the transaction costs make it impossible to trade this anomaly and the anomaly has become unprofitable. This could be quite confusing, because on the one hand (according to some papers), the January effect should be alive and well, and should continue to present a daunting challenge to the Efficient Market Hypothesis. On the other hand, this anomaly is starting to look more like the result of data mining than a real market anomaly and should not be traded at all.
The most common explanation of this phenomenon is connected with the tax-sensitive individual investors (to income taxes). If those investors disproportionately hold small stocks, they tend to sell those stocks for tax reasons at the end of the year (to claim a capital loss) and reinvest during the first month of the next year. This paper overall states that this anomaly should work and is significant; however, if we would also consider another research, the conclusions become mixed. For example, Haug and Hirschey in the “The January Effect” say that: “The January effect in small-cap stock returns is remarkably consistent over time, and does not appear to have been affected by the passage of the Tax Reform Act of 1986. This finding adds a new perspective to the traditional tax-loss selling hypothesis and suggests the potential relevance of behavioral explanations. After a generation of intensive study, the January effect is alive and well, and continues to present a daunting challenge to the Efficient Market Hypothesis.”
But the research of Anthony Yanxiang Gu – “The Declining January Effect: Evidence from the U.S. Equity Markets” says that: “The January effect exhibits a pronounced declining trend for both large and small firm stock indices since 1988 and the effect is disappearing for the Russell indices. The downward trend is more apparent for indices containing small stocks than for indices of large stocks.”. Connecting the aforementioned with the transaction costs leads to a conclusion that in the recent period, the January effect is becoming impossible to trade.
Backtest period from source paper
Confidence in anomaly's validity
Notes to Confidence in Anomaly's Validity
Notes to Indicative Performance
per annum, data from table 1, January alpha from 2,7% for stocks from middle market deciles (average market capitalization 85.5 mil. USD to 141,3 mil. USD) to 6.7% alpha for stocks from lowest market decile (average market capitalization 7,9 mil. USD) plus average ~10% return for large cap stocks
Period of Rebalancing
Notes to Period of Rebalancing
Notes to Estimated Volatility
Number of Traded Instruments
Notes to Number of Traded Instruments
Notes to Maximum drawdown
Notes to Complexity Evaluation
CFDs, ETFs, funds, futures
Simple trading strategy
Invest in small-cap stocks at the beginning of each January. Stay invested in large-cap stocks for the rest of the year.
Hedge for stocks during bear markets
No - The strategy invests long-only into the equity market factor; therefore, it is not suitable as a hedge/diversification during market/economic crises.
Out-of-sample strategy's implementation/validation in QuantConnect's framework