Does AI Spell The End For Portfolio Managers? by Alex Barrow, Macro Ops
The early 90’s classic had Arnold at his best and changed the sci-fi action genre forever.
People have always had a particular fear of technology and machines, but Terminator really solidified that picture. How many times have you heard the “Skynet” argument when it comes to today’s technology?
Fortunately, I don’t spend much time worrying about robots taking over the world. I’ll leave that to Elon Musk.
But what does interest me is what artificial intelligence (AI) means for financial markets.
While some believe the new technology will make human investors obsolete, I think that fear is overblown.
Here’s the thing… technology is always progressing. And it always has. Every innovation has provided advantages to certain groups for certain periods of time, but the playing field always evens out.
Tammer Kamel over at Quandl recently wrote a great piece on the transience of alpha in markets. In it he covers innovations throughout the years that produced alpha for investors. He explains how none of these advantages persisted because of the “inevitability of diffusion”. Eventually others got access to the information or technology that produced the alpha and nullified it.
The pre-1930’s had robber baron-esque investors planting moles in the government left and right. This gave them a heads up on any large government purchases or sales coming down the pipeline.
Back then embedded players frequently used their connections to get a jump on the markets. But this advantage didn’t last. In this case it wasn’t that everyone else started getting insider information too, but rather the government stepped in with security laws. Either way the source of alpha was eaten up.
Fast forward to the 80’s and 90’s and you had the first wave of computers taking over the markets.
Derivatives were all the rage — the more complex the better. Convertible bonds became popular because of how easy it was to use a computer to arbitrage your way to risk-free profits. But of course once computers became run of the mill, this easy money disappeared too.
Today the Internet of Things (IoT) is the latest informational advantage used to create alpha sources. James from the Operator community recently pointed out a nice graphic depicting the use of IoT sensors and their data in different industries like farming and energy.
Smart farming, for example, involves placing sensors in the soil to determine moisture and nutrition levels to help calculate potential crop yields.
Not only will this information help farmers with their resource utilization, but imagine how much it could help futures traders?
Another emerging technology providing an informational edge is Computer Vision (CV). CV involves using specialized cameras to collect detailed imagery data to be analyzed by computers. The insights produced are far beyond anything possible with the human eye.
And yes, I know what you’re thinking. CV is absolutely how Arnold chose his legendary leather jacket in T2…
But this type of robo-vision is no longer science fiction. It’s becoming more and more common. You can find it in everything from cars to even baby monitors. Nanit for example is a super high-tech baby monitor that’s looks like a small lamp post hanging over a crib.
This thing is ridiculous. It does everything from measuring a baby’s height and weight, to its sleeping patterns, temperature distribution, and general well-being. It’s billed as a cure to the sleepless nights parents have to suffer through with their crying babies.
My parents had a better, more cost-effective solution back in the day. They’d just let me cry. Classic parenting right there…
But Nanit has larger goals in mind than just a better night’s sleep. They plan to aggregate all the data from the eventual broad network of Nanit monitors to help research early child development. That research can then be used to assist doctors in medical diagnosis. Doctors haven’t had access to this type of data before and the hope is that it could lead to some great new insights.
Now apart from cars and baby monitors, CV technology is being used in all types of tracking. There’s simple applications like Density, which tracks people’s movements in a workspace.
And then there’s more advanced facial recognition features that are highly useful in things like anti-terrorism.
CV is a brand new technology that’s making far more data available than ever before. And this is where the informational advantage comes in.
Imagine a hedge fund with enough resources to use a satellite with CV to track the number of customers coming in and out of department stores. What could do they do with that data? Possibly extrapolate the foot traffic into something more? Maybe use to help predict future earnings? This application of CV and others like it have the potential to give these funds a huge leg up on other investors.
But like I said, this tech is already becoming more and more common. You even have it in baby monitors now!
Technology is inherently deflationary. The high-tech sensors and CV cameras used in the IoT movement are constantly getting cheaper to produce. This brings prices down and opens the tech up to more and more people. As they gain the same advantages from the cheaper tech, the alpha in the process disappears.
And so it goes, on and on. No matter the technology, alpha is transient, and the playing field always evens out.
But now we we’re on the cusp of highly functional AI. This is the game changer right? This is the technology that marks the end of human involvement in the market.
“This time it’s different.”
Nope, sorry. Don’t think so.
AI will likely go the way of all our past technology. It will be a tool for us to use, not something that takes over the market.
But I see why people think AI could replace us as market participants. When you read about the innovation in the space, you start to think “damn… I don’t have a chance”.
The New York company Rebellion Research, founded by the grandson of baseball Hall of Famer Hank Greenberg, among others, relies upon a form of machine learning called Bayesian networks, using a handful of machines to predict market trends and pinpoint particular trades. Meanwhile, outfits such as Aidyia and Sentient are leaning on AI that runs across hundreds or even thousands of machines. This includes techniques such as evolutionary computation, which is inspired by genetics, and deep learning, a technology now used to recognize images, identify spoken words, and perform other tasks inside Internet companies like Google and Microsoft.
In the simplest terms, [evolutionary computation creates] a large and random collection of digital stock traders and [tests] their performance on historical stock data. After picking the best performers, it then uses their “genes” to create a new set of superior traders. And the process repeats. Eventually, the system homes in on a digital trader that can successfully operate on its own. “Over thousands of generations, trillions and trillions of ‘beings’ compete and thrive or die,” Blondeau says, “and eventually, you get a population of smart traders you can actually deploy.”