The secret is to make peace with walking around in a world where we recognize that we are not sure and that’s okay. As we learn more about how our brains operate, we recognize that we don’t perceive the world objectively. But our goal should be to try.
Annie duke’s “Thinking in Bets” is basically long essay with an extremely valuable message. Under a plethora of entertaining anecdotes about professional poker it contains a valuable framework for making decisions in this uncertain world. This requires accepting uncertainty, and being intellectually honest. Good decision making habits compound over time
Thinking in Bets is a slightly less nerdy and less nuanced compliment to pair with “Fortune’s Formula”. It also fits in well with some of the more important behavioral finance books, such as…. Misbehaving, and Hour Between wolf and dog, Kluge, etc.
I’ve organized some of my highlights and notes from Thinking in Bets below.
The implications of treating decisions as bets made it possible for me to find learning opportunities in uncertain environments. Treating decisions as bets, I discovered, helped me avoid common decision traps, learn from results in a more rational way, and keep emotions out of the process as much as possible.
Outcome quality vs decision quality
We can get better at separating outcome quality from decision quality, discover the power of saying, “I’m not sure,” learn strategies to map out the future, become less reactive decision-makers, build and sustain pods of fellow truthseekers to improve our decision process, and recruit our past and future selves to make fewer emotional decisions. I didn’t become an always-rational, emotion-free decision-maker from thinking in bets. I still made (and make) plenty of mistakes. Mistakes, emotions, losing—those things are all inevitable because we are human. The approach of thinking in bets moved me toward objectivity, accuracy, and open-mindedness. That movement compounds over time
Thinking in bets starts with recognizing that there are exactly two things that determine how our lives turn out: the quality of our decisions and luck. Learning to recognize the difference between the two is what thinking in bets is all about.
Why are we so bad at separating luck and skill? Why are we so uncomfortable knowing that results can be beyond our control? Why do we create such a strong connection between results and the quality of the decisions preceding them? How
Certainty is an illusion
Trying to force certainty onto an uncertain world is a recipe for poor decision making. To improve decision making, learn to accept uncertainty. You can always revise beliefs.
Seeking certainty helped keep us alive all this time, but it can wreak havoc on our decisions in an uncertain world. When we work backward from results to figure out why those things happened, we are susceptible to a variety of cognitive traps, like assuming causation when there is only a correlation, or cherry-picking data to confirm the narrative we prefer. We will pound a lot of square pegs into round holes to maintain the illusion of a tight relationship between our outcomes and our decisions.
There are many reasons why wrapping our arms around uncertainty and giving it a big hug will help us become better decision-makers. Here are two of them. First, “I’m not sure” is simply a more accurate representation of the world. Second, and related, when we accept that we can’t be sure, we are less likely to fall
Our lives are too short to collect enough data from our own experience to make it easy to dig down into decision quality from the small set of results we experience.
Incorporating uncertainty into the way we think about our beliefs comes with many benefits. By expressing our level of confidence in what we believe, we are shifting our approach to how we view the world. Acknowledging uncertainty is the first step in measuring and narrowing it. Incorporating uncertainty in the way we think about what we believe creates open-mindedness, moving us closer to a more objective stance toward information that disagrees with us. We are less likely to succumb to motivated reasoning since it feels better to make small adjustments in degrees of certainty instead of having to grossly downgrade from “right” to “wrong.” When confronted with new evidence, it is a very different narrative to say, “I was 58% but now I’m 46%.” That doesn’t feel nearly as bad as “I thought I was right but now I’m wrong.” Our narrative of being a knowledgeable, educated, intelligent person who holds quality opinions isn’t compromised when we use new information to calibrate our beliefs, compared with having to make a full-on reversal. This shifts us away from treating information that disagrees with us as a threat, as something we have to defend against, making us better able to truthseek. When we work toward belief calibration, we become less judgmental .
In an uncertain world, the key to improving is to revise, revise, revise.
Not much is ever certain. Samuel Arbesman’s The Half-Life of Facts is a great read about how practically every fact we’ve ever known has been subject to revision or reversal. We are in a perpetual state of learning, and that can make any prior fact obsolete. One of many examples he provides is about the extinction of the coelacanth, a fish from the Late Cretaceous period. A mass-extinction event (such as a large meteor striking the Earth, a series of volcanic eruptions, or a permanent climate shift) ended the Cretaceous period. That was the end of dinosaurs, coelacanths, and a lot of other species. In the late 1930s and independently in the mid-1950s, however, coelacanths were found alive and well. A species becoming “unextinct” is pretty common. Arbesman cites the work of a pair of biologists at the University of Queensland who made a list of all 187 species of mammals declared extinct in the last five hundred years.
Getting comfortable with this realignment, and all the good things that follow, starts with recognizing that you’ve been betting all along.
The danger of being too smart
The popular wisdom is that the smarter you are, the less susceptible you are to fake news or disinformation. After all, smart people are more likely to analyze and effectively evaluate where information is coming from, right? Part of being “smart” is being good at processing information, parsing the quality of an argument and the credibility of the source. So, intuitively, it feels like smart people should have the ability to spot motivated reasoning coming and should have more intellectual resources to fight it. Surprisingly, being smart can actually make bias worse. Let me give you a different intuitive frame: the smarter you are, the better you are at constructing a narrative .
… the more numerate people (whether pro- or anti-gun) made more mistakes interpreting the data on the emotionally charged topic than the less numerate subjects sharing those same beliefs. “This pattern of polarization . . . does not abate among high-Numeracy subjects.
It turns out the better you are with numbers, the better you are at spinning those numbers to conform to and support your beliefs. Unfortunately, this is just the way evolution built us. We are wired to protect our beliefs even when our goal is to truthseek. This is one of those instances where being smart and aware of our capacity for irrationality alone doesn’t help us refrain from biased reasoning. As with visual illusions, we can’t make our minds work differently than they do no matter how smart we are. Just as we can’t unsee an illusion, intellect or willpower alone can’t make us resist motivated reasoning.
The Learning Loop
Thinking rationally is a lot about revising, and refuting beliefs(link to reflexivity) By going through a learning loop faster we are able to get an advantage. This is similar to John Boyd’s concept of an OODA loop.
We have the opportunity to learn from the way the future unfolds to improve our beliefs and decisions going forward. The more evidence we get from experience, the less uncertainty we have about our beliefs and choices. Actively using outcomes to examine our beliefs and bets closes the feedback loop, reducing uncertainty. This is the heavy lifting of how we learn.
Chalk up an outcome to skill, and we take credit for the result. Chalk up an outcome to luck, and it wasn’t in our control. For any outcome, we are faced with this initial sorting decision. That decision is a bet on whether the outcome belongs in the “luck” bucket or the “skill” bucket. This is where Nick the Greek went wrong. We can update the learning loop to represent this like so: Think about this like we are an outfielder catching a fly ball with runners on base. Fielders have to make in-the-moment game decisions about where to throw the ball.
Key message: How poker players adjust their play from experience determines how much they succeed. This applies ot any competitive endeavor in an uncertain world.
The best players analyze their performance with extreme intellectual honesty. This means if they win, they may end up being more focused on erros they made, as told in this anecdote:
In 2004, my brother provided televised final-table commentary for a tournament in which Phil Ivey smoked a star-studded final table. After his win, the two of them went to a restaurant for dinner, during which Ivey deconstructed every potential playing error he thought he might have made on the way to victory, asking my brother’s opinion about each strategic decision. A more run-of-the-mill player might have spent the time talking about how great they played, relishing the victory. Not Ivey. For him, the opportunity to learn from his mistakes was much more important than treating that dinner as a self-satisfying celebration. He earned a half-million dollars and won a lengthy poker tournament over world-class competition, but all he wanted to do was discuss with a fellow pro where he might have made better decisions. I heard an identical story secondhand about Ivey at another otherwise celebratory dinner following one of his now ten World Series of Poker victories. Again, from what I understand, he spent the evening discussing in intricate detail with some other pros the points in hands where he could have made better decisions. Phil Ivey, clearly, has different habits than most poker players—and most people in any endeavor—in how he fields his outcomes. Habits operate in a neurological loop consisting of three parts: the cue, the routine, and the reward. A habit could involve eating cookies: the cue might be hunger, the routine going to the pantry and grabbing a cookie, and the reward a sugar high. Or, in poker, the cue might be winning a hand, the routine taking credit for it, the reward a boost to our ego. Charles Duhigg, in The Power of Habit, offers the golden rule of habit change….
Being in an environment where the challenge of a bet is always looming works to reduce motivated reasoning. Such an environment changes the frame through which we view disconfirming information, reinforcing the frame change that our truthseeking group rewards. Evidence that might contradict a belief we hold is no longer viewed through as hurtful a frame. Rather, it is viewed as helpful because it can improve our chances of making a better bet. And winning a bet triggers a reinforcing positive update.
Note: Intellectual Honesty thinking clearly= thinking in bets
Good decisions compound
One useful model is to view everything as one big long poker game. Therefore the result of individual games won’t upset you so much. Furthermore, good decision making habits compound over time. So the key is to always be developing good long term habits, even as you deal with the challenges of a specific game.
The best poker players develop practical ways to incorporate their long-term strategic goals into their in-the-moment decisions. The rest of this chapter is devoted to many of these strategies designed to recruit past- and future-us to help with all the execution decisions we have to make to reach our long-term goals. As with all the strategies in this book, we must recognize that no strategy can turn us into perfectly rational actors. In addition, we can make the best possible decisions and still not get the result we want. Improving decision quality is about increasing our chances of good outcomes, not guaranteeing them. Even when that effort makes a small difference—more rational thinking and fewer emotional decisions, translated into an increased probability of better outcomes—it can have a significant impact on how our lives turn out. Good results compound. Good processes become habits, and make possible future calibration and improvement.
At the very beginning of my poker career, I heard an aphorism from some of the legends of the profession: “It’s all just one long poker game.” That aphorism is a reminder to take the long view, especially when something big happened in the last half hour, or the previous hand—or when we get a flat tire. Once we learn specific ways to recruit past and future versions of us to remind ourselves of this, we can keep the most recent upticks and downticks in their proper perspective. When we take the long view, we’re going to think in a more rational way.
Life, like poker, is one long game, and there are going to be a lot of losses, even after making the best possible bets. We are going to do better, and be happier, if we start by recognizing that we’ll never be sure of the future. That changes our task from trying to be right every time, an impossible job, to navigating our way through the uncertainty by calibrating our beliefs to move toward, little by little, a more accurate and objective representation of the world. With strategic foresight and perspective, that’s manageable work. If we keep learning and calibrating, we might even get good at it.
Carl Icahn is one of my favorite capitalists. For all his flaws, his glory days were epic. He shook up the corporate aristocracy, and created massive value for his early financial backers. The economy has benefited from the disruption of complacency led by corporate raiders like Icahn.
Below are some of my notes from Icahn’s bio:
The importance of philosophy
Icahn studied philosophy in college. This proved useful in understanding markets and navigating high stakes situations. He focused on the concept of empiricism.
Empiricism says knowledge is based on observation and experience, not feelings,” Icahn said. “In a funny way, studying twentieth-century philosophy trains your mind for takeovers. “. . There’s a strategy behind everything. Everything fits. Thinking this way taught me to compete in many things, not only takeovers but chess and arbitrage.
It seems to me that the quest for an explication of the empiricist meaning criterion, as it has progressed, may be likened to the tale of the city that suddenly finds itself in possession of a great homogeneous mixture of gold and sand. If the gold could be separated from the sand it would prove a great deal more valuable to the inhabitants. The wise men of the city diligently search for a method of separation. By so doing they not only vastly increase their insight into the nature of gold, sand, homogeneous mixtures, etc., but also produce a series of increasingly potent methods of separating the chaff from the gold, the meaningless from the significant.”
Waiting for the right opportunity to pounce
He waits until someone is so stretched out and in need of a deal that he can come in and buy under the most favorable terms.
From the PPM/pitchbook for Icahn’s first fund:
It is our opinion that the elements in today’s economic environment have combined in a unique way to create large profit-making opportunities with relatively little risk. Our nation’s huge need for energy has resulted in a massive flow of dollars abroad. This, coupled with huge deficit spending and decreasing productivity, has caused a high inflation rate and a sharply declining dollar. As a result, the value of gold and goods in general has skyrocketed. An obvious corollary to this is that the real or liquidating value of many American companies has increased markedly in the last few years; however, interestingly, this has not at all been reflected in the market value of their common stocks. Thus we are faced with a unique set of circumstances that, if dealt with correctly, can lead to large profits…
Non linear thinking
Like most great investors, Icahn is a non-linear thinker.
In part, his success is based on an intellectual skill that enables him to plot dozens of moves in advance. While his adversaries are thinking in linear fashion—”If I can get from A to B, then I’ll proceed to C”—Icahn sees dozens of possibilities on a single screen. The mental agility that enables him to zigzag from C to F to Z and back to R, leaves his opponents so thoroughly confused and frustrated they are on the verge of shorting out. “In trying to beat Carl, and failing to do so, people come away baffled,” said Brain Freeman. “But I can tell them why they fail. Because they think they know what Carl’s goal is when in fact he has no fixed goal.
Presented with an ultimatum in which he is told to choose between evil A or lesser evil B, Icahn moves into intellectual overdrive, expanding the range of options. In this way, he turns the tables on his adversaries, who find themselves facing a more ominous threat than they hurled at the raider.
Limitations of Icahn’s approach
Icahn was a great liquidator, a great investor in asset intensive businesses, but sticking too closely to his methods would cause a modern investor to miss great opportunities to invest in rapidly growing businesses. Additionally, based on the performance of IEP, its possible that he has failed to adapt to recent technological disruption, and the age of asset lite businesses.
Carl is a smart Neanderthal,” said Marty Whitman. “He’s a Neanderthal because he doesn’t listen. He has fixed ideas. He doesn’t see that you can’t make money by investing in a business. He only wants to cash out—to get cash flow. He doesn’t understand that most of the great businesses built in this country were cash consumers. They used public markets and consumed cash to build fabulous wealth for their owners. But Carl just wants the cash-out approach.
As with most corporate titans, sometimes his ego gets the best of him. He nearly went bankrupt messing around with airlines, for example. Nonetheless his story is valuable and entertaining, and he wrote the playbook for many situations faced by investors today.
Everybody has access to Bloomberg and Google. Every global macro investor closely follows macro data out of every country. To gain an an edge, one must look beyond headline numbers, and find underutilized datasets.
This applies when finding countries, industries, and individual companies in which to invest. Any time you want to combine top down and bottom up insights, you need to get creative with finding the right data.
Schumpeter and Perez
Joseph Schumpeter pointed out that aggregate figures “conceal more than they reveal”.
Relations between aggregates are
“entirely inadequate to teach us anything about the nature of the processes which shape their variations, aggregative theories of the business cycle must be inadequate too…”
In Technological Revolutions and Financial Capital, ( Carlota Perez emphasizes that new technological paradigms can only be analyzed by looking closely at inner workings of an economy. Within the same country, or industry some subsectors will grow at astonishingly high rates, while others decline. Perez’s framework is valuable to analyzing times of great technological change, which is basically anytime. Examples she uses include the first British Industrial Revolution( the age of Steam and Railways, the Age of steel, electricity, and heavy engineering, age of oil, automobile and mass production.
Top line numbers such as GDP or earnings could deceive an analyst, especially when looking at a new market.
Valuation and pricing
“People living through the period of paradigm transition experience real uncertainty as to the ‘right’ price of things(including that of stocks, of course).”
Extreme jumps in productivity change relative price structures in the economy. “The change in relative price structure is radical and centrifugal. Money buying electronics and telecommunications today does not have the same value as money buying furniture or automobiles.” Therefore, looking at inflation or deflation in aggregate is deceptive. Many years after Perez’ book, this now exacerbated by the Amazon effect. To some effect this may impact valuation in some industries.
Long term aggregate data, spanning multiple periods of technological change are senseless. This goes for GDP, corporate earnings etc. Yet disaggregated stats are rarely available(except during more stable phases), as Perez points out.
The internet has provided more opportunities to find disaggregated, unique, underutilized datasets. Often this means poking around on weird regulatory websites, and following up on footnotes to academic papers.
This process might be about to get a lot easier.
Google launched a new dataset search engine. I’m excited to see how its impact snowballs as more datasets are added. Although intended for journalists, it is likely to be a valuable tool for investors seeking differentiated alpha.
Of course that means today’s edge, will be tomorrow’s table stakes.
See also: The hard thing about finding easy things
“All under heaven is in utter chaos. The situation is excellent.”
Mao Zedong (1)
Non-traded REITs, in most incarnations, have been reprehensible financial products sold by the unscrupulous to the naive. Nevertheless, they persisted. The 7% commission was just irresistible to brokers while it lasted.
Now the mess of legacy products is left for vulture investors to cleanup. Technologically advanced secondary markets will make the process a little smoother than last time. While the traditional group of Sponsors and brokers struggle to raise capital, institutional players such as Blackstone and Oaktree are launching new non-traded REITs, and finding no shortage of demand. The next generation of non-traded REITs are a major improvement over the previous generation,although the bar isn’t exactly that high.
New entrants distributing newly improved product to new distribution channels will define the future of non-traded REITs. Several large “brand name” asset managers have recently launched non-traded REITs. They are selling via wirehouses, which have generally avoided non-traded REITs for over 20 years. They’re also selling via registered investment advisers, who, as fiduciaries, previously avoided non-traded REITs. Furthermore several well known real estate firms are launching non-traded REITs or other products and selling directly to investors online, a phenomenon completely unheard of a decade ago.
Legacy non-traded REITs and secondary market
There is a massive overhang of legacy product that is preventing sales of new non-traded REITs via the independent broker dealer(IBD) channel. Post financial crisis, non-traded REIT Sponsors tried to take non-traded REITs full cycle(either via merger or IPO) after 2-4 years. This allowed financial advisers to collect the 7% commissions over and over again. Constant recycling became a critical source of income for IBDs, and an absolute bonanza for Sponsors However, after the AR Global scandal, fiduciary standard, and FINRA 15-02, the pace of new product slowed down suddenly.
The most dangerous feeling in finance is “fear of missing out”(FOMO). FOMO causes people to make hasty emotional decisions, generally near to the top of a speculative mania. FOMO is the force behind ponzi schemes, stock promotions, and simple legit bubbles. The Stanford Business School has even looked into this
The danger of FOMO impacts people regardless of socieoeconomic status or education. It even impacted Isaac Newton:
Source: the Vantage, (which has some excellent personal finance tips on avoiding the dangers of FOMO)
Last week things got a bit volatile. Markets corrected all the way to… (wait for it) the price level of a couple months ago. This was the result of a sudden sharp reversal of record retail inflows. Although it wasn’t really an abnormal reversal, the media made it sounded like the beginning of another financial crisis.
I recently went back and re-read the Berkshire Hathaway letters from during the dot-com bubble. Buffett and Charlie Munger mostly sat out the mania, then used Aesop’s Fables to explain it all when it was done. Investors can learn from their ability to maintain equanimity amidst the madness of crowds. However its also important to note that they made errors of omission as technology altered industries. Investors do themselves a disservice if they automatically reject tech investments, just because those are not areas that Berkshire Hathaway invested. Buffett’s letters to investors are a pretty good vantage point from which to understand repeating historical patterns.
As the dotcom bubble started gathering momentum, Warren Buffett reaffirmed commitment to discipline:
Though we are delighted with what we own, we are not pleased with our prospects for committing incoming funds. Prices are high for both businesses and stocks. That does not mean that the prices of either will fall — we have absolutely no view on that matter — but it does mean that we get relatively little in prospective earnings when we commit fresh money.
Under these circumstances, we try to exert a Ted Williams kind of discipline. In his book The Science of Hitting, Ted explains that he carved the strike zone into 77 cells, each the size of a baseball. Swinging only at balls in his “best” cell, he knew, would allow him to bat .400; reaching for balls in his “worst” spot, the low outside corner of the strike zone, would reduce him to .230. In other words, waiting for the fat pitch would mean a trip to the Hall of Fame; swinging indiscriminately would mean a ticket to the minors.
If they are in the strike zone at all, the business “pitches” we now see are just catching the lower outside corner. If we swing, we will be locked into low returns. But if we let all of today’s balls go by, there can be no assurance that the next ones we see will be more to our liking. Perhaps the attractive prices of the past were the aberrations, not the full prices of today. Unlike Ted, we can’t be called out if we resist three pitches that are barely in the strike zone; nevertheless, just standing there, day after day, with my bat on my shoulder is not my idea of fun.
Although way too early, he started lamenting high prices:
In the summer of 1979, when equities looked cheap to me, I wrote a Forbes article entitled “You pay a very high price in the stock market for a cheery consensus.” At that time skepticism and disappointment prevailed, and my point was that investors should be glad of the fact, since pessimism drives down prices to truly attractive levels. Now, however, we have a very cheery consensus. That does not necessarily mean this is the wrong time to buy stocks: Corporate America is now earning far more money than it was just a few years ago, and in the presence of lower interest rates, every dollar of earnings becomes more valuable. Today’s price levels, though, have materially eroded the “margin of safety” that Ben Graham identified as the cornerstone of intelligent investing.
Notable Actions in 1997:
Net sales of 5% of the stock portfolio
increasing emphasis on “unconventional commitments”, including oil derivatives, and direct investments in silver.
Conventional wisdom holds that credit markets are “smart institutional money” that sees problems faster than equity markets that are full of less sophisticated retail investors. I question whether that is still empirically true. Retail investors now own large portions of the credit market, including high yield. Credit markets appear to be distorted by a combination of indexation and a reach for yield. Its possible that bonds trading at par can be a false comfort signal for an equity investor looking at a highly leveraged company, because in many recent cases equity markets have been faster to react to bad news.
Retail ownership of credit markets.
However you slice and dice the data, there is clearly a lot more retail money in credit than there was a decade ago. The media mostly reports on noisy weekly or monthly flows, even though there has been a clear long term change.
Bond funds in general have experienced dramatic inflows over the past decade:
Source: ICI Fact Book 2017
The issues becomes more serious when you look just at the high yield part of the market. Boaz Weinstein of Saba Capital estimated that between ½ or ⅓ of junk bonds are owned by retail investors in the current market. The WSJ cited Lipper data that says mutual fund ownership of high yield bonds/loans is $97 billion today vs $18 billion a decade ago. ICI slices the data differently, and comes up with a much nosier data set for just floating rate unds, indicating large outflows in 2014 and 2015. However it shows net assets in high yield bond funds up 3x compared to 2007, and the total number of funds up over 2x during that time.
Source: ICI Fact Book 2017
Its not just mutual funds either- there are now more closed end type fund structures that market towards retail investors. BDCs experienced a fundraising renaissance through 2014, and are now active in all parts of the high yield credit markets- from large syndicated loans to lower middle market. Closely related, before the last financial crisis, ago there was minimal retail ownership of CLO equity tranches, but now there are a few specialist funds, and a lot of BDCs have big chunks of it as well. Oxford Lane and Eagle Point were sort of pioneers in marketing CLO investments to retail investors but many others have followed. Interval funds are a tiny niche, but over half the funds in registration are focused on credit. It seems just about every asset manager is cooking up a direct lending strategy. The illiquid parts of the credit market are harder to quantify, but there has been a clear uptick in retail investor exposure since before the financial crisis. The marginal buyer impacting pricing is increasingly likely to be a retail investor rather than an institution.
Retail investors to exhibit more extreme herding behavior. According to Ellington Management Group:
This feedback loop between asset returns and asset flows has magnified the growth of the high yield bubble.
Its pretty easy to make a loan, its much harder to get paid back.
King of Capital: The Remarkable Rise, Fall, and Rise Again of Steve Schwarzman and Blackstone discusses the early days of the leveraged buyouts(LBOs) and junk bonds from the vantage point of Blackstone’s founders.
In 1978, KKR did an LBO of an industrial pumps make (Houdaille Industries). There had been many small LBOS of private businesses, but no one had gone that big, done a public company. A young investment banker named Steve Schwartzman heard about the deal and realized he had to get his hands on that prospectus. “He sensed something new was afoot — a way to make fantastic profits and a new outlet for his talents, a new calling.
“I read that prospectus, looked at the capital structure, and realized the returns that could be achieved.” he recalled years later. “I said to myself, ‘This is a gold mine.’ It was like a Rosetta stone for how to do leveraged buyouts. “
Speculative Bridge Financing
It quickly became apparent how lucrative leveraged buyouts could be.
LBOs were financed with Junk Bonds. The process of issuing junk bonds was messy and cumbersome. It took most banks an extremely long time to issue bonds. Drexel was so adept at hawking junks, that companies and other banks in a deal would go forward on an LBO based solely on Drexel’s assurance that it was “highly confident” it could issue bonds. Other banks that couldn’t do that would offer short term financing, aka bridge loans, so a buyer could close a deal quickly, and then issue bonds later to repay bridge loans This alowed DLK, Merril Lynch, and First Boston to compete with Drexel in the LBO financing space.
But what if the bonds couldn’t issued? How would the bridge loan be paid for?
… bridge lending was risky for banks because they could end up stuck with inventories of large and wobbly loans if the market changed direction or the company stumbled between the time the deal was signed up and the marketing of the bonds. The peril was magnified because bridge loans bre high, junk bond-like interest rates, which ratcheted up to punishing levels if borrowers failed to retire the loans on schedule. The ratchets were meant to prod bridge borrowers to refinance quickly with junk, and up until the fall of 1989, every bridge loan issued by a major investment bank had been paid. But the ratchets began to work against the banks when the credit markets turned that fall. The rates shot so high that the borrowers couldn’t afford them, an the banks found themselves stuck with loans that were headed towards default.
In the late 80s/early 90s. several junk bond deals fell through with disastrous consequences. The $6.8 billion United airlines buyout turned out poorly. Several stores ended up going bankrupt due to a failed junk bond deal: Federated Department stores , the parent of Bloomingdale’s, Abraham & Strauss, Filene’s and Lazarus, etc. etc. First Boston nearly failed due to its exposure to junk bond deals. Blackstone mostly sidestepped the worst problems of the era, but fought hard to get refinancing in some cases, and had a couple deals jeopardized.
The Minsky view of junk bonds and LBOs
The collapse of the bridge financing market in the junk bond era illustrates a key idea in Hyman Minsky’s Financial Instability Hypothesis: the idea of three types of leverage.
…shareholder activism can be put to good use and bad. It challenges inefficient corporations that waste valuable assets, but it can also foster destructive and destabilizing short-term strategic decisions. The key issue in an activist campaign often boils down to who will do a better job running the company—a professional management team and board with little accountability, or a financial investor looking out for his or her own interests.
Elliott Management is a prominent hedge hedge fund with a succesful 4 decade track record, perhaps most infamous for seizing a ship from Argentina’s Navy during a debt dispute back in 2012. Elliott has become a most widely known as an activist investor in recent years. Its impact has also been important because it has shaken up large companies previously thought immune to activists. Furthermore, Elliott has been a successful activist in Europe and Asia, where conventional wisdom once held that activism didn’t really work.
Elliott’s tactics are extreme, and controversial, but they work. Although sometimes there are unintended consequences- Elliott has indirectly affected regime change in two different sovereign nations. Fortune’s latest issue has an in depth profile of Elliott Management that is well worth reading.
For more on the history of corporate activism, and its impact on the history of capitalism, Dear Chairman is a definitive guide.
Business history teaches us that the pursuit of profit brings out an extreme and obsessive side of people. When we harness it well, we get Wal-Mart, Les Schwab Tires, Southwest Airlines, and Apple. When we don’t, we get salad oil swindles, junk bond manipulations, and Steak ’n Shake funneling its cash to its CEO’s hedge fund. The publicly owned corporation has been a remarkable engine engine for progress and economic gowth because it can place large amounts of capital in the hands of the right people with the right ideas. Without proper oversight, however, public companies can squander unimaginable amounts o money and inflict great harm on everything around them. The emergence of the shareholder as the dominant force in corporate governance has bestowed a tremendous amount of power and responsibility on investors….
No Economy is too small, no political crisis is too dire, and no country is too bankrupt for a solo operator like me to find riches among the ruins.
Riches Among the Ruins: Adventures in the Dark Corners of the Global Economy is an incredibly entertaining bottom up look at frontier market crises over the last 3 decades from the perspective of a travelling distressed debt trader. Each chapter is dedicated to Robert Smith’s experience in a particular country: El Salvador, Turkey, Russia, Nigeria, Iraq, etc, etc. Each country is unique, but Smith’s weaves several key lessons throughout his memoir.
Anyone who seeks profits in inefficient markets could benefit from Smith’s experience.
Information vacuums are key for middleman and arbitrageurs
In the mid 1980s no one had any idea what an El Salvador bond was worth- which is to say, they had no idea what value others might attach to it. The ignorance, this information vacuum, was my bliss. The seller’s price was simply a measure of how desperately he wanted to dispose of a paper promise of the government of El Salvador, and the buyer’s measure of how eager he was to convert his local currency into a glimmer of hope and seeing dollars down the road. The spread, my profit, was the difference between the two. In a fledgling market, with no reporting mechanisms and precious little information floating around, the spread can be enormous, and there was no regulatory or legal restrictions on how much you could make on a transaction.
Though my sellers and buyers, usually the representative of foreign companies doing business in El Salvador, often knew each other , played golf together, or broke bread together at American Chamber of Commerce breakfasts, I knew it would take some time before they eventually started to compare notes. At the beginning I doubt any of them even mentioned they were trying to sell or buy El Salvador bonds because the market didn’t exist yet. But until the market matured it was a gold rush, and I developed a monopoly on that most precious of all commodities in any market: information. I found out who wanted to sell, who wanted to buy and their price, and I held that information very tight to the vest.
In some cases buyers and sellers were on different floors in the same office building, or different divisions of the same global corporation. The biggest challenges for foreign companies doing business in the developing world was converting local currency revenues back into dollars. One way to get money out was to buy dollar bonds at fixed exchange rate and over time collect principal and interest in dollars.
Creativity and information edge: Struggles over bondholder lists
In almost every country, Smith, goes through difficulty to get the list of people holding the bonds in which he was seeking to make a market. Arbitrageurs and brokers who had access to the list guarded it aggressively, because it gave them an edge in acquiring positions at a discount, or profiting as a middleman. This was a key bit of information, available from connections at the Central Bank or other places.