The House of Cards that Nick Schorsch built was destined to collapse for a variety of reasons. But what started the demise was then-CFO of ARCP Brian Block just making up some numbers in a spreadsheet. This led to ARCP revealing a $23 million accounting misstatement. After that it became nearly impossible for the non-traded programs to raise new capital, and a whole slew bad behavior and examples of egregious mismanagement soon came to light(I’ve highlighted examples of their questionable corporate governance before). ARCP changed its name to Vereit, but the whole American Realty Capital complex of affiliated entities that depended on new fundraising would never recover.
ARCP’s culture was obsessively focused on achieving financial projections, especially for adjusted funds from operations(AFFO), a preferred Wall Street metric for REITs . According to Investment News:
In fact, the company gave employees computer mouse pads with 2014 AFFO guidance on them. “AFFO per share greater than $1.16,” the computer mousepad declared. “First believe it, then achieve it.”
I was able to independently verify the existence of this infamous mousepad. Here is a (deliberately obscured) photo:
This mousepad is a manifestation of “Goodhart’s Law” in action. Named after economist Charles Goodhart, this states that
When a measure becomes a target, it ceases to be reliable.
Goodhart’s law is very similar to “Campbell’s Law” named after social scientist Donald Campbell. Campbell’s law states:
The more any quantitative social indicator is used for social decision-making, the more subject it will be to corruption pressures and the more apt it will be to distort and corrupt the social processes it is intended to monitor.
When people are incentivized to achieve one metric above all else, there behavior will result in the number ceasing to be have its orignal meaning. Goodhart’s law was originally used to describe how monetary policy targets led to distortion. Recent examples of this phenomenon on include reclassification of crimes to reduce crime statistics, and abuse of academic citations. In Capital Returns: Investing Through the Capital Cycle , Edward Chancellor highlighted the Goodhart’s law as the reason conducting investment analysis based exclusively on the single metric of earnings per share growth. The ARCP incident certainly wasn’t the first time that Goodhart’s law led people to fudge the accounting numbers.
Goodhart’s law inevitably leads to waste of resources. One example from the Soviet Union nail factories illustrates this in a big way:
The goal of central planners was to measure performance of the factories, so factory operators were given targets around the number of nails produced. To meet and exceed the targets, factory operators produced millions of tiny, useless nails. When targets were switched to the total weight of nails produced, operators instead produced several enormous, heavy and useless nails.
Beyond just reclassifying or forging numbers, and producing useless nails, incentives distorted by the emphasis of single metrics can have even scarier effects:
During British colonial rule of India, the government began to worry about the number of venomous cobras in Delhi, and so instituted a reward for every dead snake brought to officials. Indian citizens dutifully complied and began breeding venomous snakes to kill and bring to the British. By the time the experiment was over, the snake problem was worse than when it began. The Raj government had gotten exactly what it asked for.
To avoid the trap of Goodhart’s law or Campbell’s law managers (and investment analysts) need to take think deeply about what is measured, and take multiple factors into consideration, never relying too much on any individual metric. Failing to consider Goodhart’s law can be fatal for investments.
Non-traded REITs are like thanksgiving turkey:
“Consider a turkey that is fed every day. Every single feeding will firm up the bird’s belief that it is the general rule of life to be fed every day by friendly members of the human race ‘looking out for its best interests,’ as a politician would say. “On the afternoon of the Wednesday before Thanksgiving, something unexpected will happen to the turkey. It will incur a revision of belief.”
-Nassim Nicholas Taleb The Black Swan: Second Edition: The Impact of the Highly Improbable: With a new section: “On Robustness and Fragility” (Incerto)
That chart could easily be replaced with “4 years in the life of AR Global REIT investors. ARC Hospitality(Now Hospitality Investors Trust) was offered at $25.00 a share from 2013-2015, and would never have been marked below $22.00 on a client statement until this summer. It was recently revalued at $13.20 . Likewise ARC Healthcare Trust III was offered at $25.00, and recently marked down to $17.64. Both programs were sold as conservative stable investments that wouldn’t have the volatility one experiences in the stock market.
Of course, the revision of value wasn’t really unexpected, so the thanksgiving turkey/black swan analogy isn’t really right. . ARC Hospitality was egregiously over leveraged, all the ARC REITs, egregiously mismanaged by a kleptocratic external adviser. However, for customers who based their belief exclusively on the account statement, rather than actual analysis of the portfolio, the experience has been like that of the thanksgiving turkey. Investors in other non-traded REITs have had even worse experiences. Account statement stability is an illusion. Snapping out of that illusion can be painful.
In the case of ARC Hospitality, Brookfield Asset Management has mostly taken over, and will likely drive some recovery of value. Brookfield provided some rescue equity financing on dilutive returns- the alternative would have been a potential “going concern issue”. They have convertible preferred with a strike price about 11% above the current NAV. In the case ARC Healthcare Trust III, management is doing convoluted affiliated merger with another AR Global managed REIT. Strangely when an affiliate is buying it, they believe its worth less than the value they were selling it at before. More on these shenanigans later.
In Grinding It Out: The Making of McDonald’s Ray Kroc tells the story of how he built McDonalds into a behemoth. The key themes that run through it are his persistence and obsessive attention to detail. There are also some interesting strategic insights on how he views store operators differently than the typical franchise business, and how he selected real estate locations. If the book is too long, there is also a movie, and a country music song telling the same general story. The book is unique, however, since it provies a direct view into Ray Kroc’s thought process.
One of the basic decisions I made in this period affected the ehart of my franchise system and how it would develop. That was that the corporation was not going to get involved in being a supplier for its operators. My belef was that I had to help the individual operator succeed in every way I could. His success would insure my success. But I couldn’t do that and, at the same time, treat him a a customer.
There is a basic conflict in trying to treat a man as a partner on the one hand while selling him something at a profit on the other. Once you get into the supply business, you become more concerned about what you are making on sales to your franchisee than with how his sales are doing. The temptation coud become very strong to dilute the quality of what you are selling him in order to increase your profit. This would have a negative effect on your franchiesees business, and ultimately, of course, on yours. Many franchise systems came along after us and tried to be suppliers, and they got into severe business and financial difficulty. Our method enabled us to build a sophisticated system of purchasing that allows the operator to get his suplies at rock-bottom prices. As it turned out, my instinct helped us avoid some antitrust problems some other franchise operators got into.
On selecting locations for new stores:
Back in the days when we first got a company airplane, we used to spot good locations for McDonald’s stores by flying over a community and looking for schools and church steeples. After we got a general picture from the air, we’d follow up wit h a site survery. Now we use a helicopter, and its ideal. Scarceley a month goes by that I don’t get reports from whatever districts happen to be using our five copters on some new locations that we would never have discovered otherwise. We have a computer in Oak Brook tat is designed to make real estate surveys. But those printouts are of no use to me. After we find a promising location, I drive around it in a car, go to the corner saloon and into the neighborhood supermarket. I mingle with the people and observe their comings and goings. That twlls me what I need to know about how a McDonald’s store would do there.
India’s opposition to One Belt One Road makes sense given the whole Kashmir issue, and general geopolitical competition. Indian think tanks have therefore been warning about risk to both China and target countries(ie this article makes some good points but is a bit cliched and hyperbolic)
Making things more interesting, India and Japan this month launched their own similar(albeit geographically narrower) initiative: The Asia Africa Growth Corridor(AAGC), aka the Freedom Corridor. Right now its still in the development bank and think tank press release phase, but India and Japan have strong incentive to follow up with real money pretty quickly. India and Africa have a deep history of mercantile and maritime connections. India’s Exim bank has already funded $8 billion in credit in Africa, according to Modi’s speech during an African Development Bank meeting, which was held in India last week. Port infrastructure in East Africa and the Indian Ocean are likely to be the first priorities, along with agriculture and electricity. Incidentally, India and Japan are also building a LNG terminal in Sri Lanka, a country that is heavily in debt to China as a result of controversial infrastructure projects.
There is a Chinese aphorism, “When the sandpiper and the clam grapple, it is the fisherman who profits” (鹬蚌相争渔翁得利). If China and India really end up competing by spending money around East Africa, companies involved in building or benefiting from improved infrastructure could reap a decent reward. Will the benefits accrue to any outside minority investors in publicly listed companies? Too soon to tell, but it will be interesting to watch. The usual caveats about EM corruption and waste apply to AAGC as much as they do to OBOR, but the financial media is likely to oversimplify. India and Japan’s now official strategy could impact select companies listed in India and Japan, in addition to companies in the less developed capital markets of East Africa and Sri Lanka.
Learning to think probabilistically is one of the most critical skills one can master. Nate Silver’s The Signal and the Noise: Why So Many Predictions Fail–but Some Don’t is a valuable book on thinking probabilistically and forecasting in an uncertain environment. It compares and contrasts examples across multiple disciplines, including weather forecasting, seismology, finance, and more.
This book pairs well with Against the Gods, Fortune’s Formula and Superforecasting. Against the Gods is in my opinion, the most important book on the development of probabilistic thinking. Early civilizations were good with geometry and logic, but helpless with uncertainty. Ironically it was gamblers and heretics who moved mankind forward by developing the science of probability, statistics, and ultimately risk management. Fortune’s Formula shows the connection between information theory, gambling, and correct position sizing for investors. It helps the answer the question: when you have a slight edge, how much should you bet? Nate Silver draws heavily on Superforecasting. Particularly important is the idea of “foxes and hedgehogs”. Foxes are multidisciplinary, adaptable, self critical , tolerant of complexity, cautious and empirical. In contrast, Hedgehogs are specialized, stalwart, stubborn, order-seeking, confident, and ideological. As you might expect, foxes make far better forecasters than hedgehogs, even though hedgehogs make for better television.
Anyways, here are a few key insights from my notes on The Signal and the Noise
1) Data is useless without context.
There are always patterns to find in data, but its critical to understand the theory behind the system you are studying to avoid being fooled by noise. This is true in forecasting the weather, investing, betting on sports, or any other probabilistic endeavor. The ability to understand context is also a critical advantage humans have over computer programs.
“Statistical inferences are much stronger when backed up by theory or at least some deeper thinking about their root causes. “
The importance of understanding context comes to the forefront when you compare human’s success with weather forecasting, vs relative failure with earthquake forecasting.
“Chaos theory is a demon that can be tamed- weather forecasts did so, at least in part. But weather forecasters have a much better theoretical understanding of th earth’s atmosphere than seismologists do of the earth’s crust. They know more or less, how weather works, right down to the molecular level. Seismologists don’t have that advantage. “
The ability to understand context is what separates success from failure in all pursuits dealing with uncertainty. The profile of professional sports gambler Bob Voulgaris, is highly instructive. Voulgaris focuses on NBA basketball. A key insight is that Voulgaris has powerful tools for analyzing data, and he makes good use of the data, but he also has deep understanding of the qualitative subletities of how NBA basketball works. Obvious statistical patterns are quickly incorporated into betting lines, whether they are signal or noise. Voulgaris looks deeper, and finds places where the line misprices true probabilities.
“Finding patterns is easy in any data rich environment; thats what mediocre gamblers do. The key is in determining whether the patterns represent noise or signal. “
2) Beware of overconfidence
“… the amount of confidence someone expresses in a prediction is not good indication of its accuracy, to the contrary, these qualities are often inversely correlated. “
3) Think big, and think small. Mix the macro and the micro.
“Good innovators typically think very big, and they think very small. New ideas are sometimes found in the most granular of details where few others bother to look. And they are sometimes found when you are doing your most abstract and philosophical thinking, considering why the world is the way that it is and whether there might be an alternative to the dominant paradigm.”
This is reminiscent of the “global micro” approach used by several manager’s profiled in Inside the House of Money: Top Hedge Fund Traders on Profiting in the Global Markets
4) Recognize the Value of Bayesian Thinking
The work of Thomas Bayes forms the framework underlying how good gamblers think.
Bayes was an English minister who argued in his theological work that admitting our own imperfections is a necessary step on the way to redemption. His most famous work, however, was “An Essay toward Solving a Problem in the Doctrine of Chances,” which was not published until after his death. One interpretation of the essay concerns a person who emerges into the world( ie Adam, or someone from Plato’s cave), and rises to see the sun for the first time:
“At first the does not know whether this is typical of some sort of freak occurrence. However each day that he survives and the sun rises again, his confidence increases that it is a permanent feature of nature. Gradually, through this purely statistical form of inference, the probability that he assigns to his prediction that the sun will rise again tomorrow approaches(although never exactly reaches) 100 percent.”
In essence, beliefs on probability are updated as new information comes in.
Ironically Bayes philosophical work was extended by the mathematician and astronomer Pierre Simon-Laplace, who was likely an atheist. Although Laplace believed in scientific determinism, he was frustrated with the disconnect between (what he believed to be the perfection of nature, and human imperfections in understanding it, in particular with regards to astronomical observations. Consequently, he developed some measuring techniques that relied on probabilistic inferences, rather than exact measurements. “Laplace came to view probability as a waypoint between ignorance and knowledge.” The combined work of Laplace and Bayes led to simple expression that is concerned with conditional probability. In essence Bayesian math can be used to tell us the probability that a theory or hypothesis if some event has happened.
5) The road to wisdom is to be less and less wrong.
forecasting, or at least operating in an uncertain environment, is an iterative process.
Nate Silver titles one of the chapters “Less and Less Wrong, as a homage to the Danish mathematician, scientist, inventor, and poet Piet Hein, author of Grooks:
The road to wisdom? — Well, it’s plain
and simple to express:
and err again
George Soros treats developments in financial markets as a historical process. In The Alchemy of Finance, he outlines his theory of reflexivity, discusses historical developments in markets, and describes a real time “experiment” he undertook while running the Quantum fund in the 1980s.
Markets are an ideal laboratory for testing theories: changes are expressed in quantitative terms, and the data are easily accessible.
Three of the key interrelated concepts in his framework, are anti-equilibrium, Imperfect Knowledge, and Reflexivity.
In markets, equilibrium is a very rare special case. Further, adjustments rarely lead to new equilibrium. The economy is always in adjustment.
According to George Soros:
If we want to understand the real world we must divert our gaze from a hypothetical final outcome , and concentrate our attention on the process of change that we observe all around us.
In trying to deal with macroeconomic developments, equilibrium analysis is totally inappropriate. Nothing could be further removed from reality than the assumptions that the participants base their decisions on perfect knowledge. People are groping to anticipate the future with the help of whatever guideposts they can establish. The outcome tends to diverge from expectations, leading to constantly changing expectations, and constantly changing outcomes. The process is reflexive.
The stock market, is of course a perfect example:
The concept of an equilibrium seems irrelevant at best and misleading at worst. The evidence shows persistent fluctuations, whatever length of time is chosen as the period of observation. Admittedly, the underlying conditions that are supposed to be reflected in stock prices are also constantly changing, but it is difficult to establish any firm relationship between changes in stock prices and changes in underlying conditions. Whatever relationship can be established has to be imputed rather than observed.
So its better to focus on nature and direction of ongoing adjustments, rather than trying to identify an equilibrium.
Perhaps more problematic with an exclusive focus on rarely occurring equilibrium conditions is the assumption of perfect knowledge. Perfect knowledge is impossible. Everything is a provisional hypothesis, subject to improvement. Soros makes the bias of market participants the center part of his analysis.
In natural sciences, usually the thinking of participants and the events themselves can be separated. However, when people are involved, there is interplay between thoughts and actions. There is a partial link to Heisenberg’s uncertainty principle. The basic deductive nomological approach of science is inadequate. Use of probabilistic generalization, or some other novel scientific method is preferable.
Thinking plays a dual role. On the one hand, participants seek to understand the situation in which they participate; on the other, their understanding serves as the basis of decisions which influence the course of the events. The two roles interfere with each other.
The influence of this idea is inseparable from the theory of imperfect knowledge.
The participants’ perceptions are inherently flawed, and there is a two-way connection between flawed perceptions and the actual course of events, which results in a lack of correspondence between the two.
This two way connection is what Soros called “reflexivity.”
The thinking of participants, exactly because it is not governed by reality, is easily influenced by theories. In the field of natural phenomena, scientific method is effective only then its theories are valid, but in social political , and economic matters, theories can be effective without being valid.
Effective here, means having an impact. For example, in a bubble, the cost of capital for some companies drops to be absurdly low, relative to the risk of their respective enterprises. Consequently, some businesses that would have otherwise died, may go on to survive. (Example from two decades after the Alchemy of Finance was written: Peter Thiel mentions when being interviewed in Inside the House of Money, that Paypal did a massive capital raise right a the height of the tech bubble, even though it didn’t need the money at the time) On the flip side, a depression can be self fulfilling, if businesses are unable to refinance.
This seems to be especially true in the credit markets:
Loans are based on the lender’s estimation of the borrowers ability to service his debt. The valuation of the collateral is supposed to be independent of the act of lending; but in actual fact the act of lending can affect the value of the collateral. This is true of the individual case and of the economy as a whole. Credit expansion stimulates the economy and enhances the collateral values; the repayment or contraction of credit has a depressing influence both on the economy and on the valuation of collateral. The connection between credit and economy activity is anything but constant- for instance , credit for building a new factory has quite a different effect from credit for a leveraged buyout. This makes it difficult to quantify the connection between credit and economic activity. Yet it is a mistake to ignore it.
This is reminiscent of Hyman Minsky’s Financial Instability Hypothesis
In terms of the stock market, Soros asserts (1)Markets are always biased in one direction or another. (2) Markets can influence the events that they anticipate.
“Always take a company seriously, even if its financials are knee-slapping, hoot-promoting drivel”
I’m about halfway through The Art of Short Selling. It has some incredible short selling case studies. One accounting issue that comes up is where accounts receivables spikes without a proportionate increase in actual cash sales. Tracking the ratio between accounts receivable and sales is a way to track a pretty simple trick that company accountants can pull. The example used is that of the a corporate/government training company with a famous politician on the board. It ended badly for shareholders. This happens a lot in questionable companies getting “out over their skis.”
“Receivables can be up by more than sales for several reasons:
1. The company acquired a company, and the acquisition is not yet under control-collections do not have the same billing cycle or terms for sales, for example. If the acquisition was a large one relative to sales, the relationship of year versus year in receivables is not comparable.
2. The company is booking revenues too aggressively-for example, a three-year contract recognized at the front end, so that receivables stay high because the rate of payment is slow.
3. The company changed its credit policy to easier terms or is giving incentives for sales, thereby jeopardizing future sales.
4. The company is having trouble collecting from customers. Building accounts receivables is a cost to the company because investing in business already booked hurts cash flow. Timely collections are sensible in a growing business because growth eats money by definition.”
How companies book revenues is a particularly quarrelsome issue for analysts: There are many ways to fool around, and technology and training companies are two categories of regular abusers. Revenues booked should have a consistent relationship with collection-if a company ships now and collects in 60 days, the accounts receivable schedule should consistently mirror that policy. So rising receivables versus sales or a lengthening number of days in receivables should always trigger a question: Something has changed, it says.
If your screener sets of an alarm due to a spike in receivables relative to sales, running through this list might help you find the answer. Understanding this question gets back to the basic question: how does this company make(or fail to make) money?
One more quote to top it off:
“For the last week I’ve been carrying “The Art of Short Selling” around with me just about everywhere. Every time I get a break, I just open to a chapter. Doesn’t matter if I’ve already read it. I just read it again.”
I recently reread Common Stocks and Uncommon Profits by Phil Fisher, while I was flaneuring in Morocco. Fisher held stocks for years and even decades, and focused on situations where he could get a several hundred percent gain over his holding period. His process focused on “Fifteen Points” to look for in a common stock. Not every investment was positive on every point, but good long term investments would need to exhibit many of them.
Here are my notes on the Fifteen Points.
- Does the company have products or services with sufficient market potential to make a possible sizable increase in sales for at least several years?
Fisher didn’t spend time on “cigar butts”- he wasn’t interested in squeezing cash out of a dying business, even though it could be lucrative for certain investors. Likewise, he acknowledges that its possible to make a quick profit from one time cost cuts in an inefficient business, although that wasn’t his niche. Notably Buffett described himself as 85% Graham and 15% Fisher, and the Fisher component arguably made him more money over the long term.
It’s important to consider what the limits of growth might be- once every potential customer has purchased once, then what? During Fisher’s time he focused on a lot of high-tech product companies. In modern times, there are a lot more service focused companies which can potentially generate recurring revenue streams.
A company with massive long term growth potential may have lumpy sales growth. Annual comparisons generally don’t mean that much, instead investors should compare multiple years.
If management is decent and lucky they might find themselves with a long run growth opportunity. If their truly good and lucky, they’ll find a way to creat it.
If a Company’s management is outstanding and the industry is subject to technological change and development research, the shrewd investor should stay alert to the possibility that management might handle company affairs to produce in the future exactly the type of sales curve that is the first step to consider in choosing an outstanding investment.
One of the key examples is Motorola.
I wrote on Seeking Alpha about the short thesis on Western Union(WU). The company is paying $586 million settlement in which it admitted to aiding and abetting wire fraud. However competitive decline is an even larger long term threat. Not mentioned in the article, I was actually long the stock from 2012-2015, having bought because I thought the market overreacted to its decision to cut prices on remittances. I ultimately sold because I was disappointed with the company’s response to the technological disruption in the global remittance market. I didn’t go short till late 2016. Its a relatively small position(about 2%), but I generally avoid shorting in size. As this chart shows, the incumbents are losing pricing power in the remittance market:
For more details, see the full writeup.
Dead Companies Walking, by Scott Fearon is one of the most fascinating business books I’ve ever read. The author is a talented hedge fund manager with a great track record on both the long and the short side. His ability to spot “Dead Companies Walking” is a key part of his edge. Even for long only investors, the tales of what to avoid are valuable. The book describes 6 main reasons why companies fail:
1) Historical myopia: learning from only the recent past.
This seems to be most prevalent in cyclical industries, such as energy. The author’s formative experience was starting at a Texas bank right before the oil bust of the 1980s. People looked at charts going back only a couple decades, and assumed that prices would drop only to a certain level. Equally absurd assumptions can be applied to all sorts of metrics that people use in the investment decision making process.
2) Relying too heavily on a formula.
If a company follows a strict formula or metric, such as adding a certain number of stores annually, they can quickly find themselves making illogical decisions. Value Merchants, a retailer is an example used in this chapter.
Investors that rely too much on formulas can end up investing in zombie companies on the cusp of obsolescence. Various yellow page companies, for example, looked extremely cheap on an EBITDA basis in the early 2000s.
Relying too much on formulas an result in errors of omission. For example, investors may that relied on a strict valuation formula would have turned down Starbucks and Costco in their early days.