George Soros is about as close to a household name as it gets for a hedge fund manager. He’s legendary for his billions, “breaking” the Bank of England, and is even an alleged mastermind of left-wing, political conspiracy theories. For me, though, Mr. Soros’s theory of reflexivity is his most impressive achievement. Introduced in his book, The Alchemy of Finance, I simply see reflexivity everywhere. In fact, we might be in the midst of a reflexive event of epic proportions as we speak.
While I didn’t find The Alchemy of Finance to be much of a read, I was blown away by Mr. Soros’s theory of reflexivity. More commonly accepted today, it was truly groundbreaking and highly controversial at the time of its publishing in 1987. In a lot of ways, I’m not surprised that it took a philosophically-minded person to stand so boldly against the over-zealous mathematicians who seemingly commandeered economics. Reflexivity is far from a neat and tidy theory. However, its potential explanatory power appears greater than others’.
What Is Reflexivity?
Reflexivity is simply a theory of feedback loops. While Mr. Soros contemplates a wider applicability, he contends that the behavior of market participants today impacts tomorrow’s outcomes. It flies firmly in the face of the Efficient Market Hypothesis (EMH) and the related theory of rational expectations which dominate modern financial thought. According to these orthodoxies, market prices reflect all current and known information; trading is futile. Occurrences of booms and busts run contrary to EMH yet they are commonplace throughout history. Reflexivity, in my opinion, offers a more plausible alternative explanation.
“I contend that financial markets are always wrong in the sense that they operate with a prevailing bias, but the bias can actually validate itself by influencing not only market prices but also the so-called fundamentals that market prices are supposed to reflect.”George Soros, The Alchemy of Finance
Reflexivity as a model for market behavior is more widely accepted today. More commonly referred to as complexity theory, complex adaptive system analysis, or some other variant, it is both growing as a field of study as well as in stature. (Please note that for the remainder of this article I will use “reflexivity” to refer to these collective views.) To be sure, there are still plenty of EMH holdouts. Institutional inertia and its mathematical neatness keep it entrenched. Reflexivity requires messy abstraction and accepting unknowns. Surely EMH has utility as an approximation for market behavior, but it fails as anything more. I find reflexivity to meet such demands, though putting it into practice is anything but easy.
“The crux of the debate boils down to whether we should consider investors to be rational, well informed, and homogeneous—the backbone of standard capital markets theory—or potentially irrational, operating with incomplete information, and relying on varying decision rules. The latter characteristics are part and parcel of a relatively newly articulated phenomenon that researchers at the Santa Fe Institute and elsewhere call complex adaptive systems”.Michael J. Mauboussin, Revisiting Market Efficiency: The Stock Market as a Complex Adaptive System
According to Michael Mauboussin’s research, reflexivity addresses a number of key shortfalls that underpin the EMH. First, it better explains the “fat tails” of return distributions (i.e. booms and busts). EMH assumes returns are normally distributed which is unsupported by the data. Reflexivity also demonstrates how returns can persistent under certain conditions rather than follow the “random walk” of EMH. It similarly shows how diversity of investor opinions can change over time, and why most portfolio managers underperform the market, yet some prove to be exceptional. Here, EMH turns a blind eye.
After familiarizing myself more with reflexivity, I simply see instances of if everywhere.
I See Reflexivity In Bitcoin
Bitcoin’s value is inextricably linked to its use. The more people who transact over the Bitcoin network, the greater its value should be. After all, you need bitcoin tokens to use it. This means buying and selling bitcoin as needed. Thus, we can see the establishment of a feedback loop between the value of bitcoin and the amount of users it garners.
The fixed amount of bitcoins and early phase of its adoption created ripe conditions for speculation. Reflexivity can shed some light on its bubble and subsequent bust.
Bitcoin’s price history closely resembles …
Chart by TradingView
… that of a textbook asset bubble.