Many years ago, I was a fairly new joiner to my company and a senior colleague offered me a stock tip to beat the market.
This was going to be a dead cert to make money.
I think I bought a couple of thousand dollars of stock and then forgot about it. A month or two later we were catching up and he asked me whether I went in on the trade. I’ll never forgot the look of disdain from him when he realized I had not piled in with a 5 or 6-figure investment and totally failed to go-big.
That was the last time he gave me a tip and probably the last time I purchased an individual stock.
I can’t remember his exact method for identifying these tips, but I think he analyzed company reports and devised a signal based on some company-value parameters along with the current stock price. I don’t even remember whether my stock did well or not.
But the reality is that any “edge” he may have had probably did not last.
I recently came upon some fascinating academic research to support this.
Let’s dig into it!
An Edge - Beating the Market
We all want an edge when investing.
We’re all looking for that free lunch. We want those juicy returns, but none of that tiresome risk.
So gimmee a method!
There is no shortage of methods out there for trying to beat the stock market. Most of them are cheap cons but there are some reputable predictors for excess stock returns. Perhaps the most familiar is the market factor investing methods of the Nobel prize winning Fama. Here the researchers found that small cap stocks and value stocks tended to outperform.
It may surprise you to learn that there are dozens and dozens of similar indicators that appear in high-quality peer-reviewed financial journals every year. These predictors broadly fall into four categories:
- Signals constructed from corporate events, such as a merger or a change in credit rating.
- Signals constructed from the accounting data for a company.
- Signals constructed from the market date. This might involve the stock price, it’s dividend yield, volume of trading etc.
- Valuation signals that look at the ratio of market values to fundamentals.
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Does Academic Research Destroy Money-Making Methods
Two academic researchers, R.David Mclean and Jeffrey Pontiff have published a paper with the snappy title “Does academic research destroy stock return predictability” in the Journal of Finance.
In it they look at 97 money making methods for the stock market. These are peer-reviewed methods published in highbrow academic journals – and I think you’ll agree that 97 is a load of predictors!
They analyzed the returns from these methods over three different time periods.
- Using the data sample period of the original study.
- After the original sample ended, but before the paper got published.
- Post-publication, using data after the paper was published.
The Goals of the Research
The goal in this research was to see whether the effectiveness of these methods dropped off after publication. The reasoning being that after the method becomes very well known then everyone and their uncle piles into the trade and destroys any edge that might have been present. This is the benefit of looking at the effectiveness pre and post publication.
Another goal was to examine how much of the method was due to statistical artifacts, or the researchers simply selecting a favorable time period. It’s possible that the researchers cherry-picked, or data-mined a specific period, and therefore this edge might disappear after the original sample period.
Example - 'Momentum Strategy'
To give you an example; the celebrated ‘momentum’ effect found that market returns for recent high-performing stocks seem to be larger than expected. In other words, if a stock has risen sharply, then it’s likely that it will continue to rise. The converse was also found to be true. A stock that sharply falls, may continue to fall more than is expected.
You can therefore create a ‘momentum’ strategy to capitalize on this effect. Note that this is the opposite of the buy-low, sell-high strategy, replacing it with buy-high and sell-even-higher. The original researchers published their paper in 1993 based on analyzing stock data from 1965-1989. The results are impressive – see below.
This puppy is a money-making machine! Holy smokes, get aboard this train now!
However, that’s the sample period of the study. Let’s see what happened after the original study.
Oh whoops! The strategy regularly falls off a cliff. It’s good until… well, until it crashes. And boy does it crash!
The momentum example neatly captures one of the findings of McLean and Pontiff; after the study period the 97 strategies they analyzed tend to do less well.
They found that returns were around 26% lower using data after the original sample period. At least some of this decrease must be due to researchers mining data and looking for effects that don’t persist and are not “real”.
Next they looked at the impact of publication. Does the publication of the results reduce the effectiveness of the strategies? They found that returns fell a further 32% simply from publication. This makes a total reduction in effectiveness of 58%.
Publication of the results did not totally wipe out the edge, and one possible reason for this is that some of the strategies involve a cost to the investor. For example, if the strategy involves small cap stocks that are relatively illiquid then the trading costs will be inflated and so it’s harder for the market to fully remove any advantage.
I have played a little fast-and-loose with the author’s results in places to simplify the messaging. In fact the paper does not say that you can’t beat the market. Really the paper is concerned with unexplainable return premiums. It may be quite possible to ‘beat’ the market with small-cap stocks over the long-term for example. But that will come with additional risk – such as illiquidity risks. The authors are concerned with returns that cannot be explained by the addition of more risk. In other words can you get a ‘free-lunch’ with extra returns for no extra risks. Their conclusion is ‘no’ – broadly speaking. And even if you can, those methods likely involve additional trading and frictional costs that may erode any perceived benefits. If you want to read more about how successful (or not) actively managed funds are, then check out my post The Cosmic Irony of Stock Picking Funds
Author Bio: I started actuary on FIRE as I did not see any actuaries taking a prominent role in the personal finance area and wanted to remedy a shortage of actuary jokes and write for those that appreciate rigor with fancy charts. In my regular day job I advise corporate US on investment and retirement strategies. I’m a qualified actuary, investment adviser and have a PhD in mathematics and reserve the right to have the occasional math post.