Markets, Murmurations, and Machines

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"Virtually undetectable market manipulation" by high frequency traders hard-wired to the world's exchanges have figured out a way to use complexity to their advantage and shape the market for brief moments like a flock of starlings reacting to an unseen and invisible force.

self-organizing starlings murmuration

/merr'meuh ray"sheuhn/, n.

1. an act or instance of murmuring.
2. a flock of starlings.

"What makes possible the uncanny coordination of these murmurations, as starling flocks are so beautifully known? Until recently, it was hard to say. Scientists had to wait for the tools of high-powered video analysis and computational modeling. And when these were finally applied to starlings, they revealed patterns known less from biology than cutting-edge physics."1

Starlings Go Viral

I'm not sure if you've noticed or not, but over the past year or so there's been a surging interest in the flocking behavior of starlings. Why? Well, other than the awe-inspiring beauty of one of nature's most beautiful and mysterious phenomena (see video), it represents a steadily growing dynamic at work within our own society and financial markets—namely, the collective behavior of any highly interconnected system.

To be quite honest, there may be no better way of capturing the mysterious behavior of complex systems than the unpredictable and yet highly coordinated movements of a thousand or so starlings flying in mid-air. Thus, it is easy to understand why TED-talks, morning shows, or long-time market commentators have all been inspired by this amazing phenomena and, in the case of James Dines, to create splashy headlines like "The Coming Worldwide Murmurations."

Whether we refer to it as herding, collective intelligence, mass psychology, or complex self-organizing behavior—this property of the markets is something that we as humans have a hard time perceiving since, well, we're often part of it. As Dines went onto explain in a recent interview:

It is very hard to see and it doesn't show up very often. All psychology today is vertical, so to speak. It's a combination of our genes and experiences individually, whereas I believe there is another level of mind that is horizontal. And it's a mass mind, and it grips us without us even being aware of it. And the examples of it in the market were the real estate craze of a few years ago. People buying real estate at way higher prices, way too high prices, [which led to] the excessive gloom...[this herding or collective behavior] shows roughly in the market sometimes. But a more visible one sometimes occurs in nature. And we called attention to a free video site that showed thousands of starling birds moving in fractal exotic shapes as if they were one unit. And my theory is that they are. The scientists studying them couldn't possibly have gotten a signal from those next to them because they were moving in tandem with birds hundreds of feet away. And I feel that this is a visible example of the "mass mind", which excites me because I watch it in the Stock Market. But I've never actually seen it. And it seems to be something, a ‘pre-birdness’ of some kind, such that the birds themselves are actually manifestations of it. I'm a trained scientist, so it's not easy for me to accept this kind of thing, but a real scientist has an open mind to everything.

From a person who wrote the classic book on How Investors Can Make Money Using Mass Psychology, it is interesting that Dines simultaneously admits "never actually seeing" the murmurations of the market. But this isn't a criticism of Dines—merely an observation of how limited human beings are in recognizing minute and ever-changing patterns as visibly we do in a group of starlings or school of fish. Ironically enough, the global markets are continually "murmuring" at a level of complexity that is far beyond human speed or execution, which is why we are seeing a fundamental shift take place that is sure to get more interesting.

Rise of the Quants

If we step back for a second though, it should be noted that a number of key events have brought us to where we are currently—one of which is monetary policy. As the return on savings through bond yields began to steadily decline from their highs in the early 80's to their current all-time record lows, one of the unintended consequences of pushing investors further out on the risk curve was a growing dependency on increasingly complex investment strategies created by financial engineers and "quants" to generate returns.

Right after the initial peak and steady fall in interest rates large financial institutions got creative and began a hiring campaign of the most talented mathematicians, physicists, and computer scientists to apply experimental cutting-edge computation, which in some cases traced back to the Cold War2. Then, as these largely computer-driven institutional players began to penetrate increasingly large portions of the market, a confluence of human-led events triggered a machine selling frenzy similar to the flash crash of 2010. As Benoit Mandelbrot—the father of fractal geometry—tells it3:

On October 19, 1987, the worst day of trading in at least a century, the [Dow] index fell 29.2 percent. The probability of that happening, based on the standard reckoning of financial theorists, was less than one in 1050.

Of course, 23 years later, the whole situation repeated itself when, facing a series of chaotic human events, automated trading systems began a vicious feedback-loop of selling until large financial institutions and hedge funds simply pulled the plug.

Beyond the similarities of what exacerbated the 1987 and 2010 crashes however, there have been a large number of disturbing changes since then. Where program trading was only a fraction of the overall market decades ago, today nearly 3 quarters—that is, 73%—of every single decision or trade being made on Wall Street is now from a machine4, with oversight being conducted, of course, by other machines. Or, how about this? In 1987 the average length of time stocks were held was around two years. Now it is 22 seconds,5 which is about the amount of time it currently takes for a machine to whip out a few thousand trades.

Embracing the Machine

Tempting as it is to shrug the above facts off as merely the product of inevitable technological progress, keep in mind one small but critical point: regulators didn't just idly sit back and allow these forces to shape the market, in some cases they enforced them. As explained in Deus Ex Machina:

In 2006 Regulation NMS (National Market System) minimized the required time of trade execution from the normal 30 seconds down to 1, making the dependency upon high speed computer-driven orders almost a necessity.

Although the Securites and Exchange Commission (SEC) maintained that a whopping 30-fold decrease in trade execution time—which facilitated a clear structural advantage toward high frequency trading—was necessary to ensure modernization and efficiency of the marketplace, most likely it was a capitulation to massive technological shifts already taking place in the industry when, for example, the world's largest stock exchange—the NYSE—phased out many of its slower and costly floor traders and reorganized as a largely automated for-profit company in 2005.

The implications of such a massive event didn't go unnoticed, however, as Stephen F. Diamond at the Santa Clara University School of Law warned at the time:

Because the NYSE was a not-for-profit corporation, the merger was also a change in organizational form. The change from nonprofit to for-profit, or demutualization, has mostly been viewed as a long-overdue response to new, on-line competition from “electronic communication networks” (ECN’s)...

In this case, investment bankers and other financial intermediaries organized to produce liquidity. The resulting nonprofit was the former NYSE, which was able to align issuing firms’ incentives to disclose with those of investors. Banker-owners of the NYSE acted as gatekeepers to the exchange, screening issuing firms through an extensive “due diligence” process, providing capital via underwriting, and connecting issuing firm insiders to one another via initial public offering (IPO) allocations. Over a period of many decades this system maintained an equilibrium in which issuing firms, big and small investors, and exchange members could participate with relative ease, transparency and fairness in the exchange. The shift to a for-profit corporation will have a significant, and potentially deleterious, impact on this equilibrium as it breaks up the longstanding components of the nonprofit system.6

Certainly it isn't hard to understand how exchanges competing for profit versus mutually cooperating to ensure market stability would have a damaging impact on the entire system, especially when securing those profits means eliminating much slower human oversight in the aggressive pursuit of lightning-speed execution.

Say Bye-Bye to Traditional Investing

With all these massive structural changes taking place, tipping the scales against average investors, it is no wonder traditional approaches to investing have been almost completely "swept aside" under a tidal wave of high-frequency trading, which care little of companies' net worth, cash flow, or any of the other metrics commonly used to price a company's stock or value an underlying asset. Of course, why would they when they're only holding it for a few seconds?

Consider "The Marginalizing of the Individual Investor" published by the global think-tank, International Economy, whose editorial advisory board includes, among many others, former and current presidents of the European Central Bank, George Soros, Martin Feldstein, and various Federal Reserve Chairmen:

For decades, professional investment advisers have continued to teach reliance on “value investing” and “buy-and-hold” as long-term guides to successful investment...

Technology may now have overridden such investment concepts. High-frequency trading platforms are focused solely on ramping up speed and volume so as to maximize tiny gains per transaction. Computerized algorithms that are momentum-sensitive are increasingly high-frequency trading-driven, raising serious doubts about traditional concepts of how markets should work. Investment strategies based on fundamentals such as a company’s long-term performance have been swept aside by high-frequency trading algorithms hunting for inefficiencies in daily pricing and super arbitrage opportunities. In so doing, they open investors to a new form of risk that has not been accounted for in most “buy and hold” asset allocation models.

In effect, individual traders are confronted with overwhelming momentum-driven forces that are unrelated to performance of individual businesses. A “fair price” may exist, but high-frequency traders are not seeking fair prices—they are focused solely on immediate profit. They are seeking transaction volume boosted by any form of momentum they can generate. Unfortunately, high frequency trader interaction with computerized algorithms of large-cap financial institutions is providing opportunities for high-speed, virtually undetectable market manipulation. Where there is opportunity to “shape” the market for advantage, it is likely that such opportunity will be exploited.7 (emphasis mine)

Remember, the people who review and help decide what I just quoted also dictate global policy. Apparently, there is widespread agreement among them that high-frequency trading can "shape" the market at a "virtually undetectable" level for profit. So what will they do about it? As far as I can tell, there's only one truly comprehensive way of regulating the international markets to prevent the rise of the machines: create a bigger machine!

Consider Is the Entire Market Rigged?

In the end, government and regulatory agencies must be able to out-compete prevailing technology by building something smarter, faster, and more pervasive. Something that can proactively recognize market-shaping patterns before they reach a tipping point. Of course, such a system cannot be constrained by the speed or limitation of human beings—it must be able to act and respond within microseconds. So, the question of whether or not the market is rigged is not necessarily one of great importance anymore. It's what’s going to be created in response that I dread most.

It's a Brave New World

Most have yet to realize it, but we are now in a very strange and different world—"virtually undetectable market manipulation" by high frequency traders hard-wired to the world's exchanges have figured out a way to use complexity to their advantage and shape the market for brief moments like a flock of starlings reacting to an unseen and invisible force.

This is where we are currently. What about the future? I've alluded somewhat with the quote above to where I think we are headed. Let's just say we might be seeing the beginnings of a huge paradigm shift in how we perceive our place in the world and how we define both intelligence and living systems.

I'll leave with this final thought: many inventors failed to harness the power of flight in trying to mimic the appearance of birds. The true breakthrough came only when the underlying principles were understood and applied to mechanical systems that not only may appear quite different from birds, but now far exceed anything they're capable of—except, of course, a flock of starlings...or so it would appear.

Consider How Algorithms Shape Our World by Kevin Slavin:

p.s. For a bit of science-fiction fun, here's probably the most famous Hollywood depiction of collective machine intelligence amassing chaos upon humanity: http://www.youtube.com/watch?v=DX3qLIwHoUo

References:

[1] The Startling Science of Starling Murmuration

[2] How Algorithms Shape Our World

[3] The (Mis)behavior of Markets: A Fractal View of Risk, Ruin, and Reward

[4] Yan Ohayon on the Impact of Algorithmic Trading

[5] Ibid

[6] Ringing the Bell on the NYSE: Might a Nonprofit Stock Exchange Have Been Effcient?

[7] The Marginalizing of the Individual Investor: The inside story of flash crashes, systemic risk, and the demise of value investing

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About Cris Sheridan

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