Mad scientists from MIT have taken over the markets to conduct the world's greatest experiment. What are the unintended consequences? Financial disaster is only part of it...
As recently reported by the Wall Street Journal many of the world’s most powerful central bankers—including our own distinguished Ben Bernanke—received their PhDs at MIT. ZeroHedge chose to frame this by saying:
“...a handful of people from MIT, deeply steeped in economic theory (not practice), the same people whose actions incidentally were responsible for the first great financial crisis, and who yield more power than any potentate in the history of the world - people who, as the ECB showed in the case of Berlusconi, can take down presidents and PMs with the flick of a switch, meet in private. No transcripts or butlers are allowed.
In other words, they are accountable to absolutely nobody.
Which is to be expected: after all they are conducting the greatest experiment in monetary, geopolitical and social history. If they fail... when they fail, everyone loses.”
Given ZH’s popularity, they probably speak for a substantial majority. Is this all to the story though? For example, what is the significance of MIT? What is being researched there? How is it applied to the markets? When we start to look at these questions we discover that a fundamental transformation is taking place—one that we need to fully understand.
Right off the bat, the first thing we should recognize is the following: big banking and finance have fully merged with cutting edge math, science, and technology—the very reason those “who yield more power than any potentate in the history of the world” are getting their PhDs from MIT and not your typical business school.
The second thing we need to understand is the implications of this fact. That is, the financial markets have become, as ZH says, the “greatest experiment in monetary, geopolitical and social history.” When most commentators express this sentiment, it is usually limited to those who leverage monetary policy; however, the experimental nature of what is operating in the markets today goes far beyond central bank intervention. It includes hedge funds, large commercial banks, and financial institutions using such high powered math and computation that it would make Einstein's head spin.
Code-Breaking Meets String Theory
A former code cracker for the U.S. National Security Agency, [Simons]...abandoned academia to start what would become Renaissance [one of the most successful hedge funds in the world], hiring professors, code breakers and statistically minded scientists and engineers who'd worked in astrophysics, language recognition theory and computer programming.
“All the quants in the world are trying to follow in Jim's footsteps because what he's built at Renaissance is truly extraordinary,'' says Andrew Lo, director of the Massachusetts Institute of Technology Laboratory for Financial Engineering and chief scientific officer of quant hedge fund firm AlphaSimplex Group LLC. “I and many others look up to him as a tremendous role model”...
At the core of Renaissance's success — and the wealth Simons is creating — is his own mathematical mind-set. Outside the financial markets, he's best known for the Chern-Simons theory, which he co-developed with Chinese-American mathematician Shiing-Shen Chern in 1974.
In simple terms, the theory provides the tools, known as invariants, that mathematicians use to distinguish among certain curved spaces — the kinds of distortions of ordinary space that exist according to Albert Einstein's general theory of relativity.
Chern-Simons is viewed as important partly because it has proven useful in explaining aspects of another field: string theory. This describes the building blocks of all matter and the universe as vibrating one-dimensional extended filaments or loops called strings.
“It turns out these things we invented, Chern-Simons invariants, had their real applications to physics [and, oh yeah, vast sums of money in gaming the financial markets].
For all we know, Simons—another graduate from MIT—may have succeeded where Einstein left off by discovering the holy grail of science, a grand unification theory of the universe, and then chose fortune over fame. Or perhaps it just turns out that finding patterns in the complex vibrations of the market is a bit like code-breaking combined with string theory?
Given that no one knows what exactly lies in Renaissance Technologies' black box, the doors are wide open for speculation. If you do a little digging however, you’ll find he was probably one of the first to combine AI and high frequency trading on a massive scale.
In order to understand what’s truly taking place in our markets today, the most logical place to start such an investigation is none other than MIT’s Laboratory for Financial Engineering—the global focal point for today’s sci-finance. If you visit their site and click “Research”, one of the first items listed is “Artificial Markets”, which gives the following description:
“Fully electronic market[s] will be ubiquitous in the near future. Because financial markets are the most efficient and best studied of all markets, they can provide unique insights in designing the next generation of electronic markets. In particular, in addition to automated electronic financial markets, there will be similar markets for bandwidth, for telephone time, and for many other commodities. The electronic markets of the future will achieve real-time, efficient and transparent allocation of resources between people and organizations and within electronic networks. In this project, we propose to study computational systems of loosely coupled, asynchronous, adaptable software agents with learning abilities. We will design, implement, and characterize artificial markets in which software agents endowed with different learning modules can interact, evolve, and compete.“
Naturally, in order to design and experiment with “software agents endowed with learning modules" that "interact, evolve, and compete" you’ll need to take a few classes—with funding provided by DARPA—across the hall at MIT’s Computer Science and Artificial Intelligence Laboratory, where it is explained:
“Computation lies at the heart of understanding all physical and biological systems. Many solutions to the most challenging problems of our lives, our work, and our world, therefore, are based in computation. MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) studies this vast, compelling field in an effort to unlock the secrets of human intelligence, extend the functional capabilities of machines, and explore human/machine interactions. We apply that knowledge with a long-term lens to engineer innovative solutions with global impact.”
Since this is still somewhat vague, I scanned through a number of MIT’s subpages and listed some of the topics that financial engineers, central banks, computer scientists, and hedge funds are toying with: evolutionary computing, neural networking, predictive modeling, sublinear time algorithms, cloud scale machine learning, genetic algorithms, nonparametric VAR models (Jim Rickards is not a big fan of these), artificial intelligence, behavioral modeling, neuroeconomics, and psychophysiology.
If you wanted to "unlock the secrets of human intelligence" and replicate it in a machine I imagine it would involve some combination of the above. Is it simply coincidence then that financial engineering and AI are closely related? Not at all. The financial markets are the perfect testing ground for rewarding highly adaptive, intelligent software. Question is, aside from profits, how do we measure success? By how well it can model and predict the mathematics of human behavior in the market, of course.
Psychohistory: Sci-Fi or Sci-Finance?
This brings us back to the mad scientists from MIT who are unknowingly turning the market into a massive cybernetic intelligence. We might think a lot of this sounds far-fetched if it weren't for the fact that well-known financial engineers and Nobel Prize winning economists trace their inspiration to 1940s sci-fi novels.
Consider Unlocking the Economy of the Mind
“Andrew Lo traces his interest in economics to a seemingly unlikely source: science fiction author Isaac Asimov. As a student at New York’s Bronx High School of Science in the mid-’70s, Lo was a fan of Asimov’s Foundation series, whose central character, Hari Seldon, develops a fictional field of study called psychohistory that combines history, psychology, and statistics to predict the actions of a large group of people. “The idea that you couldn’t tell what an individual was going to do but that you could say with more certainty what a population of individuals might do struck me as being quite plausible...That’s exactly what the field of financial economics is all about.”
Then there’s Paul Krugman, writing for the New York Times:
“Asimov, and specifically the Foundation trilogy, was my great inspiration; I became an economist because I wanted to be a psychohistorian, saving civilization through the mathematics of human behavior.”
I should point out that—surprise, suprise!—both Andrew Lo and Paul Krugman come from MIT. Andrew Lo, as mentioned earlier, is the director of MIT’s Laboratory for Financial Engineering and Paul Krugman received his PhD there.
Amazingly, this notion of “saving civilization through the mathematics of human behavior” was once an unattainable fantasy that made for good sci-fi. Today, we are closer than ever in reaching Asimov’s pychohistorical vision as central bankers from MIT, i.e. technocrats, use global monetary policy in combination with high powered modeling and computation to financially engineer market stability. Given the trillions at stake, many are wondering whether the world's greatest experiment is going to succeed or lead to the fall of the global economy.
In an interview for NPR, Asimov said that he believed his technocratic vision of the future was not only inevitable, but a response to reading Gibbon's History of the Decline and Fall of the Roman Empire. Evidently, he (along with many other sci-fi writers) believed there'd be a day when rulers could prevent catastrophes by applying science and technology to manage society. When asked,
"Do you think that would be good if there really was such a science?"
Asimov: "Well, I can't help but think it would be good, except that in my stories, I always have opposing views. In other words, people argue all possible... all possible... ways of looking at psychohistory and deciding whether it is good or bad. So you can't really tell. I happen to feel sort of on the optimistic side. I think if we can somehow get across some of the problems that face us now, humanity has a glorious future, and that if we could use the tenets of psychohistory to guide ourselves we might avoid a great many troubles. But on the other hand, it might create troubles. It's impossible to tell in advance."
Lo, himself an aspiring psychohistorian, is applying its tenets quite literally. As a distinguished MIT professor, associate of the National Bureau of Economic Research (NBER), and a well awarded scholar, he believes that its modern day equivalent, financial engineering, can actually be used to “cure cancer, stop global warming, and solve the energy crisis.”
Quoting from one of his slides he asks:
What If We Could Focus This Power For “Good”?
- Financial engineering with a “conscience”
- Apply expertise to solve society’s biggest challenges
- Finance facilitates collaboration; collective intelligence
- With the proper financial engineering, I believe we can solve the following problems in 20 years or less:
- Energy Crisis
- Global Warming
To him, the construction of complex financial products or applying AI to the markets is only the tip of the iceberg. Not only can financial engineering create (or destroy) vast sums of wealth, but by giving it a “conscience” and leveraging its “collective intelligence” humanity can unleash a vast source of innovative power and guide itself into Asimov’s “glorious future.”
Once again, as MIT’s Computer Science and Artificial Intelligence Laboratory states:
"Computation lies at the heart of understanding all physical and biological systems. Many solutions to the most challenging problems of our lives, our work, and our world, therefore, are based in computation."
If we can't solve our problems, computers will solve them for us. But, what if we are the problem? Break out the sci-fi books!
Let’s tie all this together: Lo and Nobel Prize-winning economist Paul Krugman believe that by using some combination of math, finance, and technology, high powered computation will not only tackle the world’s greatest problems but, perhaps, even save civilization from disaster, to use Krugman’s words. Furthermore, when we consider that a massive number of central bankers are now coming from MIT, it is clear that even in the domain of monetary governance this technocratic vision is taking hold.
It is much easier to believe that our financial authorities are bumbling idiots moving from one crisis to the next rather than mad scientists experimenting with high powered computation to predict the future and manage society but, then again, that's the direction we seem to be heading. Like I said in the beginning though, this experiment goes far beyond central banking—with unintended consequences far larger than merely financial disaster.
In Part II of Sci-Finance: The Great Cybernetic Experiment we’ll look at the market as a complex adaptive system, how it’s evolving, and some insights from game theory to see where things are headed.