Why a Stan Druckenmiller-backed AI platform is getting into crypto

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A Duquesne Capital veteran will use artificial intelligence to help investors anticipate cryptocurrency fluctuations via his fintech company TOGGLE AI.

TOGGLE AI, co-founded by Jan Szilagyi and Giuseppe Sette, uses artificial intelligence to track price changes in stocks, commodities and fixed income securities. The company announced on Tuesday that it will start analyzing more than 400 cryptocurrencies in addition to major currencies like Bitcoin and Etherium, which were previously included in TOGGLE’s analysis.

Szilagyi, the company’s managing director, said Institutional investor that the allure of artificial intelligence lies in its ability to analyze, process and present millions of data points at inhuman speed. This means that platforms like TOGGLE can present users with predictions for over 35,000 stocks, a feat impossible for a single human analyst.

“AI is able to process a lot of data and then process some patterns that might be useful,” he said.

Szilagyi and his co-founder Sette, chairman of TOGGLE AI, have spent most of their careers in asset management. Szilagyi began his career as a quantitative trader at Stan Druckenmiller’s Duquesne Capital (Druckenmiller would later become TOGGLE AI’s first investor). After earning his doctorate in quantitative finance, Szilagyi spent the next ten years in fundamental global macro investing – studying data and understanding the drivers of individual asset performance.

Prior to launching TOGGLE AI, Szilagyi and Sette worked as Co-Chief Investment Officers of Global Macro Strategies at Lombard Odier Investment Managers. There, it became clear to them that the amount of data available far exceeded their ability to analyze it.

“The scale and speed at which we were able to get both macro and micro data became overwhelming,” Szilagyi said.

So they launched TOGGLE AI in 2020. The platform, which Szilagyi calls a “smart list,” provides analytics that incorporate factors like earnings expectations, individual company sales, price momentum of a particular stock, geopolitical events and shifts in fiscal policy – anything that could affect the future of securities in a client’s portfolio.

If any of these factors present a substantial risk or opportunity to the portfolio, TOGGLE will flag it. For example, if analysts’ expectations become progressively less positive for a certain security, the system will highlight it and alert investors.

“TOGGLE will have given you and delivered a full analysis that will say, ‘Look, we’ve noticed this type of deterioration, say, 27 other times for this stock. This is how the stock has generally behaved thereafter over the past few weeks and months, and we think it’s relevant for you to take a look,” Szilagyi said.

He said the platform is particularly useful for investors with large portfolios who may overlook certain positions, as the AI ​​is programmed to consider all positions at once, leaving nothing to chance.

Once TOGGLE gained momentum and a framework was established to identify portfolio risks and opportunities, cryptocurrencies became the obvious next step, Szilagyi said. Crypto was just beginning to enter the mainstream investing world when the company launched in 2020, but demand has since grown and the amount of related data has exploded, allowing TOGGLE to generate meaningful analysis based on historical data.

“The amount of data available on the blockchain is mind-boggling,” Szilagyi said.

Additionally, due to the relative newness of cryptocurrencies, Szilagyi said there are no widely held or long-held views on how to trade them. It is a space conducive to innovation.

“This is where computers really shine because they are able to go at such a faster pace compared to an individual trying to do it on their own,” he said.

As cryptocurrencies become more mainstream, Szilagyi said there is a greater demand for cryptanalytics.

“If you had developed a system like this five years ago, there would only have been a handful of really dedicated crypto enthusiasts who would have been interested in it,” Szilagyi said. “As the ecosystem matures, I think the demand for tools like this becomes more essential.”

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