It has become conventional wisdom that underperformance is due to the irrational investment behavior of individuals. For the creation and propagation of this conventional wisdom, we have DALBAR to thank. Now that Wade Pfau has shown that DALBAR’s research is likely to be worthless because it calculates its numbers wrong, it is time to question whether the conventional wisdom has even a scintilla of meaning.

That wisdom says, in particular, that investors underperform the very investments that they invest in, because they get into and out of them at the wrong times. Many investment professionals think that this is obviously true, based on their observation of anecdotal evidence. But like the options day-trader who tells people how successful he is, they may remember the observations they are motivated to remember, and forget or fail to notice the rest. Investment advisors have a clear motivation to believe that investors are irrational and need their help.

The hypothesis

The assumption is that investors panic and get out of the market after it drops, then become greedy and get back in after it rises. This is assumed to be the worst possible timing for the investor.

The respected investment research firm Morningstar Inc., building on what was erroneously thought to be DALBAR’s methodology, has done its own calculations to test this. In a recent Advisor Perspectives article, Morningstar’s head of retirement research, David Blanchett, stated his hypothesis clearly: “If mutual fund investors on average made ‘smart’ market-timing trades, there would most likely be inflows into equity funds at market bottoms and outflows at market tops. What we see, though, is effectively the opposite, where net equity mutual fund flows are positive after the market does well and negative after the market does poorly”.

However, timing market tops and bottoms correctly is all but impossible. As I have shown in a previous article, it is quite possible for an investor to exit the market in a panic after a sharp drop, and reenter it again after a sharp rise, and still wind up buying at lower prices than she sold. In fact, if market movements truly followed a mathematical random walk, it would be equally likely that this behavior would result in a buy-low-sell-high scenario as a buy-high-sell-low one. The reason for this is that momentum – a continuation of the downward or upward trend – would be as likely as a reversal.

The evidence advanced in favor of the hypothesis

Building, as I say, on what was thought to be DALBAR’s methodology, Morningstar calculates the time-weighted return on a dollar invested in a mutual fund or funds, and compares it with the dollar-weighted return (i.e. the internal rate of return or IRR) calculated from the cash flow into or out of the fund and its beginning and ending values. The time-weighted return is called the investment return, and the dollar-weighted return is called the investor return. The difference between these two returns, if the investor return is less than the investment return – as it often is – is assumed to be due to investors’ poor timing.

But why? How can we be sure that the difference between investment and investor return is actually a measure of the quality of the investor’s timing?

We can’t be sure of this, at least not without further, and much more careful and thoughtful research. I believe this is yet another example of a practice that is all too prevalent in the finance field, in the peer-reviewed academic literature as much as in the rumor mill: namely, the tendency to leap to a preconceived conclusion based on a mathematical observation that is not actually warranted by the math. We don’t really know that if the investor return, so measured, is less than the investment return that means that the investor timed the market badly.

Normally, one would compare two investment strategies by comparing the ending wealth resulting from applying one strategy as compared with the other. But to do that, the cash flows have to be the same in both cases.

Comparing investor and investment return is comparing results with two very different cash flows. It is not even a comparison of ending wealth in both cases, but of rates of return that are calculated in very different ways and have very different meanings.

I’ll come back to this comparison, and the difficulty of determining what it really means, later. But first, I will describe an effort I made to address the fundamental hypothesis.