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.
Last week, Finance Twitter erupted over a Bloomberg article about Michael Burry[i] and how he likened passive investment in equity markets to the bubble in the synthetic CDO market back in 2007, which he famously – thanks to Michael Lewis and Christian Bale – identified.
Some of you may remember the quant crash of August 2007. As Andrew Lo wrote in his initial diagnosis, “losses were initiated by the rapid unwinding of one or more sizeable quantitative equity market-neutral portfolios…which then put pressure on a broader set of long-short and long-only portfolios.”
For a fundamental, value-oriented investor, we are reasonably active in the management of our portfolio names. This is by design, and on purpose. With a concentrated, best-ideas-only portfolio, it is imperative that we shed any anchoring biases and constantly challenge our theses. This leads to idea and portfolio turnover.
This is going to be an uncharacteristic departure for me. This story is deeply personal, for our family, and for our oldest son in particular. But it is a story he’s letting me tell, because it is a story he wants people to hear.
We manage a concentrated portfolio of investment ideas. We, essentially, try to be objective about identifying specific instances where Mr. Market may be overreacting or underreacting to particular fundamental phenomenon.
Disruption in the auto industry is a very hot topic. The embers started burning back in 2005 when Tesla dropped a powertrain into a Lotus Elise, then things started heating up in 2012 when Google drove a Prius across Nevada, without a driver; and then they started blazing in 2014 after Uber did a valuation round at $18 billion.
Following on our last post “The First Step to Regaining Credibility” we wanted to quickly highlight that the difference between the fee structure of a large, diversified, purportedly active fund and a smaller, concentrated, active fund.
We are not big fans of market timing. Those that profess to have such a skill before the fact often always turn out not to have had much skill in hindsight. Of those that do turn out to appear to have skill, that was actually supposed to happen.
The S&P is down nearly 20% since the 20thof September, turning a lovely and respectable 11.2% total return YTD into an excruciating 10.4% loss. In Europe, the pain has been even more severe. In the UK, the FTSE 100 is down 14.8% YTD; meanwhile the French CAC 40 is down 14.7%, and the German DAX 30 is down 21.9%.
October unleashed a storm upon financial markets. Here in Europe, we hadn’t had one since Brexit, but had many before then, and will surely have many more. Bad weather is a feature of investing, and as the stewards of long-term capital, we need to balance action and inaction during these bouts of market turmoil.
As we wrote in “Half-hearted is half-minded – December 2017” we aren’t big fans of dipping our toes in the water when entering a position, nor of timidly reducing when exiting. If we are right more often than we are wrong, it might feel better to inch in or inch out of a position, but it is a suboptimal strategy.
As the investment community embraces data science, we should not be blind to the reality that many of our active-management peers are or will be devoting a lot of resource to capturing whatever informational edge they think or hope is out there.
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.
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.
“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.
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 all started for me over 30 years ago. Today, I’m 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. 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.