MT483 Unit 6 January Effect Seminar Reflection Example

A Real January Effect That a Taxable Account Cannot Keep: An MT483 Unit 6 Seminar Reflection

[Student Name]

Purdue University Global

MT483: Investments

Unit 6 Seminar Reflection

[Instructor Name]

[Date]

The strategy's returns, costs and tax rates are composite assumptions; the studies cited are real.

What I Believed Going In

I came to the seminar ready to argue that the market can be beaten by an investor willing to act on well-documented patterns. My example was the January effect in small stocks. Keim (1983) found that nearly half of the extra return small firms earned over large ones from 1963 through 1979 came in January, and that more than half of that January premium arrived in the first week of trading. Reinganum (1983) tied part of the pattern to tax-loss selling: investors dump losing small stocks in December to realize losses for tax purposes, pushing prices down, and the selling pressure lifts in January. My plan was simple. Each December, move part of a portfolio into a basket of small stocks that had fallen during the year, hold them through January, then return to an index fund. I had two published studies and a mechanism, and I thought that was enough.

The Question I Was Asked Instead

Our instructor did not dispute that the pattern existed. The question was what would remain of it after I had paid for each trade and each tax bill. I had no answer, because I had never put a number on either. Another student added a second challenge: if the pattern was so well documented, why had it not been traded away?

That second question led the instructor to Grossman and Stiglitz (1980), who argued that markets cannot be perfectly efficient. If prices already reflected all information, nobody would be paid for gathering it, nobody would gather it, and prices would stop reflecting it. Some inefficiency must therefore survive, but only enough to compensate the people who collect information and trade on it. An anomaly can be real, in other words, and still be no larger than the cost of exploiting it.

Some inefficiency has to survive, but perhaps only as much as it costs to trade on.

McLean and Pontiff (2016) gave the point numbers: across 97 return predictors, portfolio returns were 26 percent lower out of sample and 58 percent lower after the research was published, as investors learned from the studies and traded on them.

What My Calculation Showed

After the seminar I built the comparison on composite inputs. Suppose the strategy earns 12 percent a year gross, three points more than an index fund earning 9 percent with a 1.5 percent dividend yield. The basket consists of small, beaten-down stocks with wide spreads, so each round trip costs about 1.2 percent of the money rotated, and selling and repurchasing the index fund adds a small amount, for total trading costs of [1.25] percent a year. That leaves 10.75 percent before tax.

Taxes were the part I had ignored. Because the index holdings are sold every December, eleven months after they were bought, every gain in the strategy is short-term and taxed at my assumed 22 percent rate, leaving 8.39 percent. The buy-and-hold index investor pays tax only on the dividends, at a 15 percent qualified rate, which costs about 0.23 points and leaves about 8.78 percent, with the rest of the gain deferred until sale.

The strategy that beat the index by three points before costs trailed it by about 0.39 points after them. I then solved for the break-evens. Trading costs would have to fall to about 0.75 percent a year, or the gross premium would have to rise to about 3.5 points, before the strategy matched the index after tax. The comparison flatters the strategy slightly, because the index investor will eventually owe tax on the deferred gains, but deferral over decades is worth a great deal, and adding that tax back would not close the gap at these inputs.

The Position I Hold Now

I leave the seminar with a narrower claim than the one I brought. The January pattern Keim documented was real, and a share of it may survive. Whether it exists is one question; whether one taxable investor paying retail trading costs can capture it is another, and on reasonable inputs the answer to the second is no. In a tax-deferred account the result changes, because the short-term tax penalty disappears, and I would want to test the strategy there before dismissing it completely.

I also learned to put costs into the argument before I make it. The next units on funds and portfolios will ask me to compare choices, and I now expect the after-cost, after-tax figure to decide more of those comparisons than the gross return. The question I still cannot answer is how much of the remaining January premium is a reward for bearing the risk of small, distressed companies rather than an inefficiency at all.

References

Grossman, S. J., & Stiglitz, J. E. (1980). On the impossibility of informationally efficient markets. The American Economic Review, 70(3), 393-408.

Keim, D. B. (1983). Size-related anomalies and stock return seasonality: Further empirical evidence. Journal of Financial Economics, 12(1), 13-32. https://doi.org/10.1016/0304-405X(83)90025-9

McLean, R. D., & Pontiff, J. (2016). Does academic research destroy stock return predictability? The Journal of Finance, 71(1), 5-32. https://doi.org/10.1111/jofi.12365

Reinganum, M. R. (1983). The anomalous stock market behavior of small firms in January: Empirical tests for tax-loss selling effects. Journal of Financial Economics, 12(1), 89-104. https://doi.org/10.1016/0304-405X(83)90029-6