Defined as extreme events with high impact, Black Swans are infrequent occurrences that pack a punch (i.e. in financial markets the 2008 crisis, or 2010 flash crash). However a new study shows as the combination of machine trading and speed intertwine, these extreme events are occurring more often than previously imagined. As markets continue to connect and participants become linked, each extreme bounce and/or collision may slowly break the system.
Nassim Nicholas Taleb is the person most responsible for burning the concept of low probability, high impact events into the minds of global business executives. Coining the term “Black Swans” as the name for extreme outliers with devastating consequences, Taleb has put executives on notice that they need more built-in redundancy and should incorporate slack in business processes to cushion against failure.
However as technology proliferates and advances thus speeding processes, it appears humans are increasingly removed from decision making. Thus ensuring a little slack in the system may not be enough to protect from system meltdown.
Take for example a complex “system” such as global financial markets. In an effort to gain competitive advantage, computer scientists, quants, and software programmers are building machines that scan data streams, analyze, and decide trading strategies in micro-seconds. These individuals (sometimes hedge fund managers) or corporations (such as larger investment banks) are shrinking the window for decision making down to levels where humans cannot react fast enough—microseconds today and nanoseconds in the future.
Trading equities is now a technological “arms race”, where companies compete buying and selling at near light speed. And while the concept of using speed for competitive advantage doesn’t sound like such a bad idea, there are also ramifications for a race to zero.
The first issue with this trading arms race is exclusion of participants who cannot afford the requisite technology. Just as it takes nearly a billion dollars to win a US election thus ensuring few can join the fray, it takes multi-millions to build and co-locate ultra-fast computerized trading platforms. A second issue is that as trading nears the speed of light, there is ultimately less and less slack in the system to correct trading errors. And since financial markets are tightly coupled, this means that one single error in a fragile system can cascade with cataclysmic results.
Trading at near light speed – in an already fragile and tightly coupled system—is driving more extreme events, which appear to be fracturing global markets. And contrary to common knowledge, these events aren’t just happening once every two to three years.
A team of physicists, system engineers, and software programmers recently published a paper suggesting that abrupt “events” are occurring in the financial markets much more than previously thought. In fact, over the years 2006-11, the authors report a total of 18,520 spikes in stock movements—or extreme events (I’ll call them baby black swans) that arguably should have low probability of occurring according to normal distribution statistical models.
The aforementioned study notes; “There is far greater tendency for these financial fractures to occur, within a given duration time window, as we move to smaller timescales.” Meaning that in financial markets, as faster computers slice decision making windows down to nanoseconds, we should expect more volatility. Moreover, if a given system is not designed to handle extreme volatility, there is a high probability of fissures and potential for total system breakdown.
In 2010’s Flash Crash, the US stock market plunged 1000 points in nine minutes and then regained those losses just as fast. Never before had market participants seen thousand point swings within a ten minute timeframe. If the authors in the study cited in this article are correct, this kind of extreme volatility is only the beginning.
- Is this “race to zero” latency risky, or is this much ado about nothing?
- Speed is a competitive advantage. Do you see a similar “race to zero” in decision making processes in other industries?