When we are looking for an information edge, we have to be specific about what that means. Here, I am talking about an information asymmetry between what is actually the case and what the market believes. The most famous examples of this revolve around insider information— where the market believes one thing about a company and insiders know another—but there are also many macro examples. The hedge funds that made so much money in The Big Short, for example, were betting on information about the housing and mortgage market that was substantially different than the markets as a whole. They happened to be right and made a lot of money. Areas where that information asymmetry exists are fertile fields for active investors.
This idea fits in well with yesterday’s discussion, where we concluded it was hard to see what an individual could know about a large company that the myriad analysts and reporters hadn’t discovered. The obvious solution is to look at investments that are less covered: smaller companies, companies in foreign markets, fractured markets like real estate or private equity, and so forth. The less information publicly available, the greater the chance an active investor really does have an information edge.
So, how does this apply to my own investments? When I look at active versus passive, I have to be shown evidence that an active manager really does have enough of an information edge to justify its fees and then some. I can certainly see that case in markets that are obscure or inefficient, or at least relatively so. I have a harder time when markets are liquid, widely covered, and (at least at the moment) apparently efficient.
That is not to say, however, there are no opportunities. It just means that you might have to look elsewhere. Even if companies are efficiently priced relative to one another, this does not necessarily mean the market as a whole is priced rationally.
As an example, let’s go back to the dot-com boom. At that time, many companies made no money, so they could not be priced on earnings. Instead, alternative metrics (e.g., price per viewer) were used, and companies traded on that basis. Within that metric, pricing was efficient. The bigger picture, as we soon found out, is that pricing—while efficient—was not rational.
That example, of looking beyond the immediate, takes us to one of my favorite illustrations of information asymmetry: using different time frames to evaluate data and investment opportunities. I have written about this before in the context of economic data, but it is just as applicable to investment decisions.
Most investors have a very short time frame—a year, or even less. Buy and sell decisions are made on what is expected to happen in the next couple of months. The average holding time for a stock on the NYSE is now less than a year, for example. The short time frame gives disproportionate influence to that short-term data, and you can see that in pricing. This, after all, is why investors follow quarterly earnings numbers so closely.
What if, instead, you focused on longer-term metrics? A number of simple but successful strategies do just that. The Dogs of the Dow strategy, for example, simply takes the five stocks from the Dow with the highest dividend yields, buys an equal amount, and then waits a year before doing the same thing. Note that the information used, the dividend yield, is not particularly timely; dividends come out on a quarterly basis, and the trading is annual. By looking at data that is longer term, there appears to be a real and actionable information asymmetry. This strategy is not an anomaly, as there are many strategies like this.
Other, more macro indicators include market valuation levels (which provide useful information about likely future returns) and longer-term market pricing trends (the 200-day moving average). It is not an accident that these are included in our Monthly Market Risk Update. Longer-term data is often more useful in constructing longer-term returns and risk management than is shorter-term data. And this is exactly why we use it.
The missing piece here is how I incorporate all of this information into my own investment management. There is a place for both active and passive. There is also a place for information asymmetry at the macro level. We will take a look at that tomorrow.