Rock, Paper, Scissors
December 28, 2018·AI
Investment managers are flooding money into AI to find hidden patterns in market data. The computers get faster. The data gets richer. The disappointment stays constant. The problem isn't the technology or the data. It's the assumption buried in how we're using both: that markets work like machines with discoverable answers. What if the entire foundation of this approach is backwards?
• We treat markets as clockwork. Every investor, from rigorous quants to casual analysts, runs structured historical data through computers looking for repeating patterns. This is built into how we think about markets. The assumption is that if we just examine the machine closely enough, we'll find the gear that predicts its movement.
• This model fails because it's fundamentally anthropomorphic. We're projecting human logic onto markets. We're asking computers to solve for future behavior by learning from the past. But markets aren't machines with hidden algorithms. They're social systems where behavior can never be fully reduced to pattern.
• AI is being used to strengthen the wrong approach. Adding computational power to pattern-matching just makes us better at something that doesn't work. It's like using a telescope to measure the retrograde motion of Mars in a geocentric model. More precision doesn't fix the model.
• Real AI doesn't predict from the past. It observes the present. The janken robot doesn't analyze historical hand-shape preferences. It captures ultra high-speed images of the human hand as it descends, calculates the final shape in 20 milliseconds, and reacts. It observes what's actually happening, not what happened before.
• Markets need the same kind of machine. Not one that solves for future behavior through historical data, but one that observes unstructured present conditions and calculates how actors will respond. The micro-behaviors of fear and greed can never be arbitraged away. But they can be observed as they happen.
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Comments
Ben Hunt…”We care about observing the unstructured conditions of the present and understanding the physics of what hand shapes will be made next. Because those micro behaviors of fear and greed can NEVER be arbed away.”
So what are the indirect effects of markets now and what do you want to solve or change? There is a conversation about how markets in they’re current state are not healthy/normal but anything but that due to a host of factors…HFT, VC’s, Sharebuybacks, ICO’s, Growth models over fundamentals, QE and primarily Central Banking who serve the “Banks” and not the citizens. So you get distorted markets that jump over a thousand points in one day…the negative feedback loops are destroyed for positive feedback loops so that todays markets are always in a state of “Over-Reaction” because computer algorithms separate data from narrative much more efficiently/optimized than human algorithms.
Is this a correct synopsis? If not, what is? What are the currents conditions and what do you want to change them to? What’s your 5 W’s? I ask from the perspective is the above on the right path? or What is the right path more specifically? If the questions bother anyone, then please spell it out for me (layman terminology)? Just trying to get a better understanding at my non-expert individual investor level?
“The first principle is that you must not fool yourself and you are the easiest person to fool.” -Richard Feynman
Ben,
Ray Dalio has been wildly successful and made an enormous fortune assuming the markets act like a machine.
He has been quite public about this and shared his ideas, that I’m sure you’ve read.
What are your thoughts on Dalio and Bridgewater ?
Thanks
Peter
Ben’s thoughts on Dalio… https://www.epsilontheory.com/the-narrative-machine/
The Janken machine sounds a lot like what the High Frequency Trading shops were doing several years ago (“cheating” by using technology (and complicit exchanges) to front run order flow) and what I suspect RenTec et al have been doing for decades (using technology and a ton of PhDs to predict securities movements over a few minutes time-frame).
I found this article from yesterday’s NYT on machine learning fascinating – https://www.nytimes.com/2018/12/26/science/chess-artificial-intelligence.html?emc=edit_th_181227&nl=todaysheadlines&nlid=18635851227
“on Dec. 5, 2017, the [Google/DeepMind] team had stunned the chess world with its announcement of AlphaZero, a machine-learning algorithm that had mastered not only chess but shogi, or Japanese chess, and Go. The algorithm started with no knowledge of the games beyond their basic rules. It then played against itself millions of times and learned from its mistakes. In a matter of hours, the algorithm became the best player, human or computer, the world has ever seen.”
By playing against itself and updating its neural network as it learned from experience, AlphaZero discovered the principles of chess on its own and quickly became the best player ever. Not only could it have easily defeated all the strongest human masters — it didn’t even bother to try — it crushed Stockfish, the reigning computer world champion of chess. In a hundred-game match against a truly formidable engine, AlphaZero scored twenty-eight wins and seventy-two draws. It didn’t lose a single game.
Most unnerving was that AlphaZero seemed to express insight. It played like no computer ever has, intuitively and beautifully, with a romantic, attacking style. It played gambits and took risks."
“AlphaZero had the finesse of a virtuoso and the power of a machine. It was humankind’s first glimpse of an awesome new kind of intelligence.”
“What is frustrating about machine learning, however, is that the algorithms can’t articulate what they’re thinking. We don’t know why they work, so we don’t know if they can be trusted. AlphaZero gives every appearance of having discovered some important principles about chess, but it can’t share that understanding with us. Not yet, at least. As human beings, we want more than answers. We want insight. This is going to be a source of tension in our interactions with computers from now on.”
And on August 29th, Skynet became self-aware…
Thanks Andy
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