The January Effect: Cooling Investor Returns
We can see from ten years of data that January is not the best-performing month for Alpha Theory fund managers. In fact, it is not event the top half. Read our full investigation here.
The January Effect is the belief that equities tend to perform well in January, possibly because of tax-loss harvesting in December and the subsequent repurchasing of positions in January. In light of the noticeable absence of any desirable January Effect in 2022, we decided to investigate to what extent the January Effect is visible within the All-Manager Alpha Theory dataset, which dates back to January 1st, 2012. Is this most recent January an outlier?
To test, we analyzed average monthly returns for long positions for Alpha Theory (AT) managers against the S&P 500 Index (SPY). For the purpose of this exercise, we put aside the fact that if any excess return existed by sizing up in January, it likely would have long since ceased to be a profitable strategy.
We can see from ten years of data that January is not the best-performing month for AT managers. In fact, it is not even in the top half.
In the table below, January is the 3rd worst-performing month for Alpha Theory managers and the SPY over the past decade.
January performance returns across AT Actual, AT Optimal, and SPY are roughly flat. But we can’t give up yet. Is perhaps this most recent January an outlier?
Indeed, returns for this January, though not completely tallied, are the lowest on record since the beginning of the All-Manager Alpha Theory dataset.
The conclusion? January is one of the worst-performing months for Alpha Theory managers and the SPY over the last ten years, and this year, AT managers are seeing the lowest January returns since 2016. Received wisdom, like the January Effect, must always be taken with a grain of salt.
Do you have any hypotheses you would like us to investigate? Comment below or reach out to us at Support@AlphaTheory.com. Alpha Theory is committed to helping fund managers think more clearly about the challenges associated with forecasting and asset allocation, including analysis of assumed dogma, like the January Effect.