By Review of Chaos Kings: How Wall Street Traders Make Billions in the New Age of Crisis
Scott Patterson
New York: Scribner, 2023; 293 pages
Scott Patterson has delivered an unusual book. At least to this reader, it produced the same effect as watching a Black Mirror episode where you think you know where the story is heading, then suddenly all of your moorings go out the window in a most unpleasant fashion. In the case of Chaos Kings, the book starts out as an interesting and well-paced biographical treatment of Mark Spitznagel and Nassim Taleb, developers of a tail-hedging approach to financial risk. Patterson is a veteran Wall Street Journal reporter, and his devotion to detailing a specific trade that Taleb had made on out-of-the-money currency options makes it appear that this will be a book catering to finance nerds.
Yet, in the final fifth of the book, the narration adopts a partisan garb. It is presented as an uncontroversial fact that a United States carbon tax (with a rebate for the public) is an obviously wise move that could only be opposed by those who deny science or are in the pay of Big Oil. Patterson gives lip service to other possible remedies to climate change suggested by various experts but confidently assures us that “in the end, geoengineering is a terrible solution.” Later, detailing the events of January 6, 2021, Patterson explains matter-of-factly that “right-wing media shifted the narrative of a violent mob attacking Congress on live TV to one of peaceful protestors rallying to protect democracy” and that democracy was at risk in the United States.
Contrast the treatment of January 6 with a passing reference to the reaction to the George Floyd killing, which the author calls “protests” and doesn’t mention how left-wing media hilariously tried to cast these protests as “mostly peaceful” while cities burned. To give one final example of the ideologically lopsided narrative at the end of the book: Huge Democratic donor Sam Bankman-Fried is introduced in the context of “effective altruism,” and readers learn that effective altruists “pursue career paths that would produce the highest possible winnings, resulting in the highest possible giving.” Three pages later, when winding down his coverage of Bankman-Fried, the book does disclose that FTX “imploded in late 2022” and that this “was a harsh lesson for young Bankman-Fried in the chaotic, often violent nature of financial markets dominated by Black Swans and Dragon Kings.” There is then a single sentence devoted to the allegations that Bankman-Fried had overseen gargantuan amounts of fraud, which was counterbalanced by a sentence saying he had denied the allegations.
Notwithstanding the tribal signaling that I would have expected more from a New York Times reporter than one from the Wall Street Journal, the first 80 percent of the book is still worth reading for those interested in the lifestyles of the rich and clever. Specifically, the book outlines the two major approaches to dealing with extreme risk. First, there is the Black Swan approach, developed by Spitznagel and Taleb, in which we don’t know what we don’t know. Then, there is the Dragon King approach, favored by French mathematician Didier Sornette, in which we can adequately model the probabilities of extreme (and rare) events and prepare for them in that fashion. In the remainder of this review, I will summarize the Black Swan approach because it is the one I understand better and will be more appealing to readers interested in Austrian economics. (Disclosure: I have corresponded with both Spitznagel and Taleb and was a consultant on two of Spitznagel’s books.)
I believe the best way to describe the Spitznagel and Taleb approach is that they believe most participants in the financial markets understate the level of risk in the system. (In this review, I am using the word “risk” in the everyday sense, rather than making the standard Austrian distinction between quantitative risk and qualitative uncertainty.) For example, standard models of the stock market suppose that the index follows a random walk (with upward drift) where the future level is of course unknown, but the value is drawn from a well-behaved Gaussian distribution (think bell curve) where the extreme outliers of very high returns or large crashes are so unlikely as to be negligible.
Yet—as explained in the book by fractal pioneer Benoit Mandelbrot—over a ten-year period, there were really only ten days that determined the winners and losers. Mandelbrot explains, “The great fortunes were made in a very few days. And great ruins happened in very few days. So, one gets into a situation which is very, very unsettling. That is, in this context, only the very few rare events count overwhelmingly. The rest count hardly at all.”
In his book Fooled by Randomness, Taleb expresses a related frustration, reminiscing on meetings with conventional finance suits who went around the table asking what everyone’s best guess was as to where the market would move soon. Taleb thought this was too simplistic of a framework. It would have been more appropriate to give answers along the lines of “I expect the market to move up so many points, but there is also at least a 10 percent chance that it will fall by more than 2 percent.” (These are my words. I’m paraphrasing Taleb.)
For his part, Spitznagel’s mentor in the Chicago trading pits, Everett Klipp, taught him the motto, “You’ve got to love to lose.” The idea was that you must be patient and endure a long string of small setbacks in order to seize an enormous payoff when the time was right. (In his book The Dao of Capital, Spitznagel relates this to the Böhm-Bawerkian notion of roundaboutness.) First in their jointly run fund Empirica Capital and then in Spitznagel’s Universa Investments (which still benefited from Taleb’s consultation), the two pioneered what has been called tail hedging or dynamic hedging.
The basic idea is simple. Everybody knows that, over time, the stock market will go up. However, the problem is that the stock market is very volatile. A typical way to dampen the risk is to water down a portfolio’s exposure to equities with some fixed-income securities (ideally “safe” ones from stable companies or the US Treasury)—for example, staying 60 percent in stocks and 40 percent in bonds. Yet the theory and practice from Spitznagel and Taleb showed that a “better buy” for hedging was to stay, perhaps, 97 percent long in the stock market, while allocating the remaining 3 percent of the portfolio to constantly rolling over deeply out-of-the-money put options on the stock market index.
A put option gives the owner the right, but not the obligation, to sell the underlying asset at a specified strike price. So, if the S&P 500 index is currently at 4,000, a trader could buy a put option that gives the ability to sell S&P 500 at 3,000 anytime over the next twelve months. If, during the course of the year, the market doesn’t fall below 3,000, then the put options would expire worthless. However, if the market drops to 2,000, then the options would be very valuable, conferring the ability to buy at 2,000 and sell at 3,000, pocketing the difference (or, more directly, selling the option to someone for a price reflecting the 1,000-point gap). In such a scenario, the original purchaser of the put options would have made a killing because, at the time of purchase, most people thought it very unlikely that the stock market would fall more than 25 percent (from 4,000 down to 3,000) in the next year, so the original purchase price of the options would be quite low.
With this type of tail-hedged long position, Spitznagel and Taleb’s fund would still appreciate in a rising bull market because they still had 97 percent exposure to the upside (with only 3 percent drag from the options that would be purchased and then never exercised). Yet, during a crash, the put options would explode in market value, whereas the more orthodox hedge funds would simply contain their losses by diluting them with a large chunk of bonds.
The following excerpt from Chaos Kings captures the essence of what the two innovators accomplished:
As of the early 2020s, it had been a strikingly successful strategy. Ernst & Young audited Universa’s Black Swan strategy from its launch in 2008 through December 2019 and found that its average annual return on invested capital, a common metric for measuring hedge funds’ success (or failure), was an eye-watering 105 percent. That is, on average Universa returned 105 percent per year, a track record putting it on par with or better than the best hedge funds in the world. And that didn’t even include the 4,000-plus percent bonanza of early 2020.
The gains came entirely without anyone at Universa making a single prediction about the direction of the market, up, down, or sideways. But while Spitznagel would never attempt to predict when the market might crash, he does absolutely, deep-in-his-soul, believe that the American stock market—and bond market—fueled by central bank interventions, has long been trapped in an unsustainable super bubble that will ultimately explode like a barrel full of TNT. A core tenet of Spitznagel’s worldview is that the U.S. Federal Reserve has been addicted to blowing bubbles for decades, creating dry tinder for crash after crash. (bold added)
As the latter part of the quote I’ve put in bold indicates, Spitznagel’s outlook is quite sympathetic with the Austrian school. (Elsewhere in the book, Patterson explains that Spitznagel was a fan of Ron Paul.) I should also add that—unlike some gurus in the financial media who name-drop to appeal to a certain demographic but who lack substance—Spitznagel is the real deal, who has devoted serious study to difficult economic texts. The Dao of Capital incorporates an Austrian structure of production approach into the investment philosophy Spitznagel learned at the Chicago Board of Trade, while his more recent Safe Haven profoundly enhanced my understanding of Daniel Bernoulli and John Kelly’s work on uncertainty and utility theory.
In closing, I will contrast the emphasis that Patterson in Chaos Kings puts on the “precautionary principle” with the criterion Spitznagel advances in his Safe Haven, namely “cost-effective risk mitigation.” It is understandable why Patterson gets so much mileage out of the principle in his book. So much of his narrative—particularly in the final chapters—moves away from finance and into climate change and pandemics. The precautionary principle urges extreme caution “in extreme situations: when the potential harm is systemic . . . and the consequences can involve total irreversible ruin, such as the extinction of human beings” (as Taleb and coauthors explain in a quoted paper). Whether or not one agrees with the precautionary principle and how it is typically applied in these (heavily politicized) arenas, Patterson didn’t invent the approach, and it makes sense that he would weave it into his narrative about fat-tailed distributions in the stock market, especially since the prolific Taleb wrote on all these varied topics.
Yet, in practice, the only way to truly exercise the “precautionary principle” in investing would be to not invest at all. Of course, such a policy would open one up to a different risk of not having enough wealth to handle future problems, which is why a literal interpretation of the precautionary principle can be paralyzing and self-defeating. In contrast to this criterion, one could instead adopt the approach Spitznagel explains in Safe Haven. As sketched out earlier in this review, Spitznagel shows that the conventional Wall Street approach to risk management is far too expensive, sometimes with the cure being worse than the disease. With the 60/40 portfolio example, Spitznagel shows that the standard mean/variance reward/risk framework derived from the Chicago school is fundamentally misguided.
Scott Patterson’s Chaos Kings provides an interesting background for readers who already know the work of Spitznagel and Taleb and who want to learn about their origin stories. However, to truly grasp their profound insights into financial markets, I encourage readers to check out the other books I’ve mentioned earlier.
