Financial Geekery

Two investing half-myths

June 16, 2019

"A little learning is a dangerous thing;

drink deep, or taste not the Pierian spring:

there shallow draughts intoxicate the brain,

and drinking largely sobers us again."

-Alexander Pope

 

(Yep, this is going to be one of those posts. Buckle up!)

 

In my experience, when an enginerd first dives into investing, they wind up in one of two places: bogleheads.org or Motley Fool. There's a ton of good information to be had in both places! However, if they stop there, they're liable to fall into one of two investing theses:

 

  1. It's impossible to beat the market net of fees, so your optimal path is to buy two or three broad-market funds with the lowest cost possible.

  2. The market is inefficient, so your optimal path is to purchase a few stocks that are underpriced, sell them when the market corrects, and rinse and repeat.

 

Empirically speaking, I'd say that 90% of the investing conversations I have with non-investment managers revolve around one of these two strategies. (Conversely, this is true for less than 10% of the conversations I have with investment managers. We'll talk about why that is a little later.)  

 

And I was no exception! Back in my pre-advisor days, I started at Motley Fool, and thought myself pretty clever. Then I "graduated" to bogleheads.org, and shook my head at the stock-pickers. Once I began my professional education, however, I was reminded rather painfully of Mr. Pope's quote above. As it turns out, both of these theses contain elements of truth, but neither is optimal, because neither is wholly true. 

 

Surprised? You really shouldn't be. The markets for securities (stocks and bonds) are incredibly complex systems which defy simplistic solutions! If you're an expert in a complex system, you've probably said the phrase, "there's more to it than that" so many times that it's become an automatic reaction. (Try telling a physicist why you think the sky is blue.) Whether you're talking about software engineering or quantum physics, abstractions are useful for gaining a basic understanding, but start to fall apart when you're actually tasked with building something optimal. 

 

The same is, naturally, true with investing.

 

Half-Myth #1: Stock-picking and market timing

 

The Motley Fool is positively festooned with stockpicking advice, like a Jim Cramer in website form. The basic idea is this: by accurately analyzing companies and predicting the future, you can determined which stocks are mispriced, and thus buy low (companies that will do better than the market predicts) and sell high (the other thing).

 

The trouble here is that our cognitive biases (and particularly our overconfidence as Smart People) lead us to find patterns where there are none. Moreover, because securities markets are such complex and noisy systems, it's difficult for us to determine the actual correlation between input and output -- in other words, whether we're (un)skilled or simply (un)lucky

 

The same is true if we look to hire somebody else to pick our stocks, in the form of an active mutual fund manager: how do we accurately assess whether they're smart or fortunate?

 

Investment researchers spend countless hours attempting to untangle this, slicing the data in a myriad of ways to cut through the noise and empirically prove causal relationships. Over and over again, they reach the following conclusions:

 

  • Persistent outperformance net of fees is exceedingly rare, even among professionals. (We'll talk about Buffett in a bit.)

  • Moreover, what outperformance does exist is declining, as markets become ever more efficient.

  • When looking at mutual funds, one correlation consistently stands out: low costs are correlated with outperformance.

 

That last should come as no surprise: in a system as complex as the markets, no strategy is guaranteed to outperform every day of the year. Cost, though, is constant! Which leads us to...

 

Half-Myth #2: Cost-chasing

 

Given the three conclusions above, the optimal strategy seems obvious: just pick two or three broadly-diversified mutual funds with the lowest possible expense ratio and move on. As this approach was spearheaded by Jack Bogle's firm Vanguard, its adherents are often called "Bogleheads". And make no mistake: it's a good approach!

 

But it's not optimal. 

 

Why not? Well, as it turns out, the "stockpickers" aren't entirely wrong: there are securities that will outperform others. The most obvious example is that, over the long term, stocks are likely to outperform bonds. Why? Is it because the market is consistently overpricing bonds and underpricing stocks? Not really -- rather, it's because volatility is priced into securities. Lack of volatility has value, and thus creates a higher price. To put it another way, if I'm going to take on risk, you better give me a discount on the price so that I get higher returns! 

 

Investing factors 

 

These higher returns are called "premiums", and there are several systematic sources of premiums, called "factors", that have been identified by researchers. The most well-known in the investment management world are the Three Factors created by Nobel Prize winners Eugene Fama and Kenneth French: 

 

  • High-"beta" stocks (ones that move more relative to the overall market) outperform low-beta stocks

  • Value (low price relative to earnings) stocks outperform growth stocks

  • Small-cap stocks outperform large-cap stocks

 

Why would this be true? In each case, these factors involve taking on more risk: high-beta stocks by their very definition, value stocks because the market anticipates a likely future decline in the company, and small-company stocks because small companies are less able to withstand the slings and arrows of outrageous fortune than large companies. 

 

Note this important fact: these factors exist even though the market is clearly "aware" of them. This isn't a secret sauce, liable to disappear once the secret is out. Rather, higher long-term returns flow naturally to those who have a larger appetite for short-term risk.

 

Case in point: Warren Buffett. Frazzini, Kabiller, and Pedersen broke Buffett's investments down into factors, analyzed his stock-picking v. his management, and concluded that his returns "appear to be neither luck nor magic, but rather, reward for the use of leverage combined with a focus on cheap [(that is, value)], safe, quality stocks" and "more due to stock selection than to his effect on management."

 

Now, you may have noticed that "quality" isn't one of the Three Factors I mentioned above. And you're right -- the Big Three aren't the only factors floating around! The Buffett paper above uses "Betting-Against-Beta" and "Quality minus Junk" factors, which they identified in their earlier research. Fama and French have added two more to their model: investment and profitability. Hou, Mo, Xue and Zhang suggest a four-factor variant called the "q-factor" model. And Fama's PhD student Cliff Asness presents a "momentum" factor to capture the odd habit of stocks to "trend" up or down.

 

So...which model is right? The jury's not yet in; like all research, it takes time, rigor, and a lot of experimentation to refine the accuracy of a model. The Three-Factor Model won a Nobel Prize, and Dimensional funds have outperformed Vanguard by 1-5% annualized net of fees over the past 20 years (without taking on commensurately more risk), so I'd say it's a good foundation to start from.

 

Market timing...sort of

 

Alright, so by using these "factors", you can in fact predict which stocks are more likely to outperform. But what about market timing? That's not a thing, right?

 

As it turns out, it is a thing -- kinda. First, as you might imagine, the factors that apply to a given stock don't hold constant: value companies become growth, small companies grow larger, etc. Maintaining a certain factor exposure over time means buying and selling stocks as their factors change -- in effect, buying low and selling high -- though that generally happens quite slowly. 

 

Another example of research-backed "buying low and selling high" is opportunistic rebalancing. Daryanani showed that you could improve returns by checking daily to see if the asset class percentages in your portfolio were out of whack, and if so, selling the "winners" to buy more of the "losers". For example, in a recession you might see a "flight to safety" as investors move from stocks to bonds. This drives the price of stocks down and the price of bonds up, decreasing your stock allocation and increasing your bond allocation. An opportunistic rebalancing strategy would therefore see you selling your bonds to buy stocks -- selling high to buy low, in an almost Buffett-like fashion.

 

The Whole Truth: It's Complicated

 

If you've gotten this far: congratulations! I've probably challenged a lot of your assumptions in my attempt to replace a simple mental model with a more complex one (if one proven by research to be more accurate). This is not something humans are wired to do, so I commend you for pushing through.

 

If all you take away from the article is that investing is more complicated than you thought, then I've done my job. However, if you're left with the burning question of how to make the best use of the research I've discussed above, let me make a few suggestions:

 

 

Of course, you can always hire someone to do it for you.  Either way, get it done; it's money on the table. Why not pick it up, rather than lighting it on fire?

 

 

Britton is an engineer-turned-financial-planner in Austin, Texas. As such, he shies away from suits and commissions, and instead tends towards blue jeans, data-driven analysis, and a fee-only approach to financial planning.

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