Battle of the Quants: what’s shaking up the quantitative trading world?

The dataset business is changing, and this year’s Battle of the Quants is taking a closer look at what that means for trading with the theme “Big Data”. BotQ’s founder and host, Bartt Kellermann, said that data companies have advanced considerably, moving from compiling to alpha generating.

That means that instead of just giving raw data, the cleaning, analysis, indexing, etc, is now part of the deal. Two of the companies presenting at BotQ are M Science and, which will give some idea of how it’s done in a new world of 24-hour satellite imagery and machine learning advances for processing such images.

But it’s also a world of data privacy regulations, and it seems like the industry is definitely cleaning up its act: if data providers want to sell, then fund managers insist data is not at individual level, or if it is, has been anonymized.

Big data + AI + crypto = ?

The agenda includes discussions on: winning quant hedge fund strategies now and beyond; technological disruption – where and what opportunities?; as well as quantum computing and crypto.

Kellermann noted that the confluence of big data with crypto and artificial intelligence is a development the quant hedge fund community is keen to understand because of arbitrage between inefficient exchanges. Meanwhile, the institutional mindset is taking root: just recently, he heard about the impending launch of a crypto fund of funds in Luxembourg.

“These exchanges are so inefficient in the crypto space that you can make money manually trading between exchanges,” said Kellermann. The fusion of big data/crypto/AI is a natural evolution for quants, he added.

Some of the biggest hedge funds, like Two Sigma and World Quant, are trading on thousands of data feeds, supplementing exchange data with so-called alternative data in order to improve predictability of stock prices for example.

Meanwhile, a lot of CTAs are taking the exact same strategy and overlaying it onto crypto, which is becoming another asset class that can be traded systematically, he explained.

Robot trading

Another panel looks at the future “robotic trader”, which is a bit of a tongue-in-cheek reference to the way artificial intelligence is misused as a term. If a fund is executing simple, straightforward algorithms, is it an “AI fund”?

“It’s taken on a life of its own in that even simple algorithms are labelled as artificial intelligence systems,” Kellermann said. “That doesn’t preclude the fact that in the future there will be AI systems that completely dominate the industry, but it’s not for generations to come.”

At the same time, AI hedge funds have not been doing very well this year, based on Eurekahedge’s tracking. The industry has noticed.

“If you take all the systematic trading funds that are using machine learning and big data, they are not really generating the returns everybody expected,” he said. “But that’s part of the growth phase, so, even though they are not returning big numbers, there’s still a tremendous amount of interest, money, work and brainpower being applied to this.”

Kellermann pointed to research from McKinsey that said time is running out, a kind of FOMO for integrating technology into the trading process.

“It’s a warning for people who are considering incorporating intelligence of some type, whether it’s machine learning or even simple algorithms, if they don’t get started now, they won’t be able to catch up,” he said.

Battle of the Quants is taking place November 15 at the Royal Automobile Club in London. Fintech Capital Markets looks forward to seeing you there.

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