Technological advances have enhanced the speed of the dissemination of firm-specific information, and broadened its distribution. In this new, post-internet paradigm, after also considering the maturity (and size) of the investment management industry, we propose there is very little difference between large and small-capitalization equities in terms of relevant information available to the marginal investor. Consequently, we suggest that the notion that the equity prices of smaller capitalisation companies are somehow less efficiently priced than their larger brethren may potentially be stale.
At our firm, one of our main goals is, very simply, to generate excess returns from equity investing without taking commensurate risks. When we 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 comfortably above the returns our investors should be able to capture themselves without much work, and demonstrably above the average returns of our peers in the same business.
A nightly sort of the most active US names is usually dominated by ETFs. Earlier this month, we took a peek at the most heavily traded names on one particular day.
Elon Musk made a lot of news last week, refusing to answer “boneheaded” questions from “boring” sell-side analysts. Adding fuel to the fire, he later took to Twitter and exclaimed “the 2 questioners I ignored on the Q1 call are sell-side analysts who represent a short-seller thesis, not investors.”
We’re not inclined to automatically buy in to perceived wisdom, and you probably aren’t either; but that shouldn’t stop either of us from at least exploring market proverbs to see if there a kernel of truth within them. With that, several years ago, we found an article that took a stab at return seasonality, specifically where stock market performance seems to be better in the winter than in the summer.
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.
The message below is quite compelling:
“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
“Compound interest is the eighth wonder of the world. He who understands it, earns it. He who doesn’t, pays it.”- Albert Einstein
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.
After discovering the next great investment idea, why is it so easy to start with a half-sized position, watch it a bit, and then go full-sized later?
I have immense respect for Bob Shiller. We’ve never met, but he is a forefather of behavioral finance along with Richard Thaler (and he is from Detroit, which isn’t uncool).
2017 was a pretty good year for the stock market. The 19th best since the Dow Jones Average was introduced in 1896.
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.