More Thoughts on “Fad Investing”

In a recent post I called factor investing “fad investing” (see here) because it is, at its core, an ex-post view of the world that implies that the markets will perform a certain way in the future because they’ve performed a certain way in the past. That is, many of the investors who rely on “factors” are utilizing a rear view mirror look at the markets based on extrapolative expectations that the future will look like the past (though not all do this and many quant firms use forward looking models).  In a sort of humorous irony, the “passive indexers” who apply these “factors” to their portfolio are the ultimate performance chasers.  This annoyed a lot of people and I got a number of emails and forum comments from unhappy readers.  This is not surprising given that I am stomping on hallowed ground here (passive indexing, active factor pickers, Efficient Market Hypothesis, etc – is there anyone I haven’t annoyed yet on this blog because I assure you I will find you!).  Let me see if I can explain this a bit better.

First, when we look at the markets in the aggregate we should all acknowledge that there is only one truly “passive” portfolio of all outstanding financial assets.  If you were truly passive you would try to replicate the global market cap weighting of these outstanding financial assets.  At present, that portfolio is roughly a 45/55 stock/bond portfolio (with lots of other financial assets obviously, but those are the two dominant asset classes).   When you deviate from this market cap weighted global portfolio you are making an active decision about your asset allocation.  You are essentially an “asset picker” whether you have a home bias (US stocks are your “stock allocation”) or whether you overweight stocks relative to bonds.  As Cliff Asness has stated, you don’t get to deviate from global cap weighting and then go on to disparage what you perceive to be “active” investing from your not so “passive” perch.

Second, the market return of the global market cap weighted portfolio is the market return.  After taxes and fees no one beats this portfolio in the aggregate.   Saying that most people won’t beat the market is not some Earth shattering discovery in finance.  It should be an obvious fact.  Of course, this doesn’t mean that some investors won’t “beat the market” as the relative risks and returns of different asset classes vary.  But when we look at the aggregate market cap portfolio and its inevitably mid-single digit returns it is not even remotely shocking that an asset manager who charges 2 & 20 will have a very difficult time beating the aggregate index over long periods of time.  Again, we don’t need strawman studies on stock pickers to realize this.  We just need to look at the world for what it is and understand some basic math.

Now, when we try to discover why certain investors are able to “beat the market” we often look at various “factors” that account for this.  This thinking is derived from Eugene Fama’s factor modeling in an attempt to explain the Efficient Market Hypothesis.  But we should note that the Efficient Market Hypothesis is really just a political theory to try to argue why the “market” is smarter than everyone else.  It is, in essence, an argument against government intervention based on laissez-faire Chicago School economics, rational expectations and the idea that the market knows better than any interventionist could ever predict.  This is little more than a beautifully packaged marketing campaign.  Of course the market generates the “market return”.  The fact that this return is difficult to beat doesn’t mean the market is “smarter” than everyone.  It’s just an obvious fact that the market generates the market return and the more fees and frictions you incur the more difficult it is to beat that hurdle over time.  This mathematical reality doesn’t mean markets are “rational”, “efficient” or that intervention is never wise.   It is just an obvious statement of fact that the market generates the market return and high fees erode that return.

More importantly, I would argue that this underlying model of the world distorts our reality.  Andrea Malagoli had a nice comment in the forum that summarized how some of this theoretical thinking is flawed:

“Factors are nothing more than the coefficient of a linear regression applied to the returns of an asset. In doing so, all the information about the ‘sequencing’ of the returns is lost – i.e. there is no concept of cycles because it is assumed that the markets are more or less the same at all times (no bubbles, no business cycles, etc ..).

More troubling, it is wrongly assumed that factors ‘explain’ the ‘returns’ of an investment, while all they to is to ‘explain’ the variability. This means that an investment could be highly exposed to a factor (w.g. growth), while most of the returns come from somewhere else entirely.”

Bingo.  When you apply a linear model of the financial system to what is, in reality, a dynamic system, you come up with results that require a good deal of further explanation because there are inevitable issues that don’t account for this natural cyclicality of the financial system.  But this is the underpinning of the thinking here – the assumption that, in the long-run, the markets are linear, highly efficient and the natural conclusion is that you can apply a static explanation for why the market operates in a certain way.  Even worse, you might assume that a static asset allocation is appropriate….

Eugene Fama didn’t care about presenting this reality when he constructed his factor model of the financial system.  He was simply trying to data mine his research well enough that he could convince people that he was really on to something that would rationalize a set of underlying political assumptions.  He had to make his linear model of the world look accurate.  But his model was incomplete because it didn’t account for the natural dynamism of the world and the very real inefficiencies that arise in the short-run due to cyclicality and irrational thinking.  So there were anomalies that “beta”, the market return, couldn’t explain.  In other words, there was evidence that the market was not rational and this left the door open for an excuse to intervene.  Fama promptly shut that door by adding other various “factors” to his model.  So we got the 3 factor model and then the 5 factor model and today we seem to have an endless number of factors that explain market moves.

Of course, “beta” is just another way of explaining the aggregate market return, but since Fama wasn’t looking at “the markets” in terms of the global aggregate he got bogged down in micro explanations for why stocks did certain things.  Had he bothered to focus on the global market cap weighted aggregate of financial assets he wouldn’t have had to bother with all these “factor” explanations.  Of course, he couldn’t do that because, as Paul Samuelson noted, the markets are “micro efficient” and “macro inefficient” so you run into other problems when you look at things in aggregate terms, which is an unfathomably silly irony considering that EMH and factor investing are cornerstones of the same indexing approaches which advocate buying the aggregate market.

But what are these “factors” really?  They are ex-post explanations for why the market performs a certain way.  But they don’t apply to all asset classes of course.  This is mostly just a stock market obsession even though stocks are not even the majority holding in a truly passive portfolio.   Now, these factor explanations could be perfectly relevant and they might even help someone identify some inefficiency in the market, but there is no iron clad law that says these factors will explain future performance.   They are little more than an ex-post view of what caused stocks to perform a certain way during a certain period of time.

Does this mean that factor investing is useless?  Not necessarily.  Looking at why the market has done certain things in the past can be a very useful exercise in understanding why it might do certain things in the future.  In this sense, some of these “fads” could be quite useful.  In fact, understanding the basic math of the beta factor is beyond important.  But I think it’s important to understand certain “factors” and apply a forward looking model of some type in the process of portfolio construction.  There are no iron clad “factors” that will always account for future performance and if you believe there are then you’re likely just extrapolating past performance into future expectations, which is probably a bit of a naive approach.  But more importantly, these “factors” don’t mean that markets are “efficient”, “rational” or smarter than everyone.