There is a great deal of discussion these days regarding the impact of passive investing (or of systematic active investing in risk factors), and what it means for active management, and perhaps for security pricing generally. In many cases – even with an in interesting or intuitive conclusion – the premise is all wrong.
Further below is an excerpt from Bet with the Best: Expert Strategies from America's Leading Handicappers. We recommend reading the section from Chapter 3, by Steven Crist. The read-across to stock-picking is tremendous. I have highlighted my ten favourite passages below, paraphrasing slightly, and substituting stock-related terms for any horse-related terms.
“We have a quality-focused investment philosophy, and own the best companies for the long term.”
Tough to argue with that one, right? Basically, it is the polar opposite of what must be the worst pitch of all time:
“We focus on horrible management teams and low quality businesses, and like to own the lousiest company for as short a period as possible, and then turn our portfolio over by selling one miserable business model and buying an even worse one.”
If we define being “right” or “wrong” as outperforming or underperforming the market, respectively, then in order to be right or wrong, we basically need to hold something different (either securities or bet sizes) than the “market”. Bill Sharpe taught us that over two decades ago
We’re on a continual search for the very best ideas for our concentrated portfolio. The “best ideas” component not only requires a continuous and rigorous analysis and reanalysis of the buy case for each of our names (and a continuous monitoring of expected returns), but a similar inspection of the sell case. With the perfect crystal ball, we’d love to know ahead of time which of our positions aren’t going to work out.
Students of decision-making and bias will all have seen the work by Cornell psychologist Tom Gilovich, where he reviewed the experience of London residents during World War II. Richard Thaler in Nudge highlighted some of Gilovich’s work, and described how the English newspapers published maps showing strikes from German V-1 and V-2 missiles in Central London.
Several years ago, we did an analysis of companies starting with a specific starting growth rate, and assumed that they would do a straight-line ten-year fade to a growth rate equalling inflation. We treated all the earnings as if they were free cash flows, assumed 100% equity financing, and then determined a value for each theoretical security.
The goal of our business, very simply, is to generate excess returns for our investors without taking commensurate risks. If you take a step back and think about it, another way of stating this is to say this: over time, we hope to generate returns that are well above the average returns of the market, and demonstrably above the average returns of our peers in the same business. In order to achieve these excess returns, we not only need to be right, we need to be willing to be wrong.
There are very few growth investors that stayed in business long enough to become a household name in the investment community, and even less of them that ended up writing books about their lifetime experiences.
Unlike many other market observers, we just don’t see the point in discussing or debating the macroeconomics driving overall markets, volatility, or sentiment. We’re in the camp that thinks successful prediction of market direction is, broadly, a coin flip. Well, we’re sure that we don’t have the skill; although we’re happy to concede that some of our top-down macro friends appear to do this quite well. However, over any time horizon that isn’t decades long, it is extremely difficult for any of us to know whether their “success” is due to luck or skill.
Several months back we joined a call with colleagues who were interviewing Larry Fink, the CEO of Blackrock. Blackrock – already a very passive, ETF driven shop – had just announced that it was firing several prominent active fund managers, and that a more quantitative, passive, or systematic, manager (aka a robot) would replace them.
It’s October of 2017, and that makes me old. Old enough that I’ve seen quite a lot in the world of psychology and investing, but wise enough to be certain that I don’t know everything there is to know, and never will. Thirty years ago, in the autumn of 1987, I wasn’t old enough to know much of anything at all, and too young to know how little that was.
We are human. Human beings make mistakes. We make lots of mistakes. We’re always trying to identify and eradicate them, but they happen. As we investigate fundamentals, much of our work revolves around meeting with management teams, and developing conviction in their ability to steer a business down the road.