The Use of A.I. in Trading Hedge Funds is Heating Up

BusinessThe Use of A.I. in Trading Hedge Funds is Heating Up

The Use of A.I. in Trading Hedge Funds is Heating Up

Leading funds including Renaissance Technologies, Two Sigma, and Bridgewater Associates are among the hedgies placing bets on the future of AI. Jeff Tarrant, the founder of Protégé Partners, recently launched a business that will invest solely in start-up investment funds that employ AI.

Companies Stepping Up From Algorithms to A.I.

AI is niche segment of the computer science industry that in theory can place in machines aspects of reasoning. AI is a broad term that also includes machine learning, the ability of computers to learn by analysing vast reams of data and the ability to read and produce text.

All the biggest systematic hedge funds already use computer algorithms to make trading decisions. So-called quantitative or “quant” hedge funds got their eighth straight year of client inflows in 2016, doubling their assets from 2009 to $918 billion, according to a report from Hedge Fund Research, a data provider.

Now some have started employing machine learning techniques in their search for Alpha. They comb through data for lucrative patterns that inform trades. IDC reckons that the amount of digital data will reach 44 zettabytes by 2020.

Smart Machines Can Beat Human Traders

There is evidence that hedge funds who replace their human traders with smart machines can outperform the market. At AI-heavy hedge fund Renaissance Technologies, the Medallion Fund has produced positive returns of between 20–98% from 2002 to 2016.

Another reason behind the adoption of AI is the ability to reduce employment levels and to slash staffing costs. The consultancy Opimas said in March that AI could lay waste to 230,000 finance jobs by 2025, with 90,000 asset management jobs on the chopping block.

Firms’ clients request algorithms over people because electronic trading is faster and cheaper than manual execution. The outlook for the equity sales trader is gloomy. Opimas also said many as 27,000 new jobs will be created for technology and data workers, however.

AI may also help hedgies move into the cryptocurrency space. Once the preserve of criminals, digital money such as bitcoin has entered mainstream finance, with a plethora of large hedge funds intelligence seeking to trade cryptocurrencies.

Guy Zyskind, CEO of Enigma, told recently: “It is important to understand the history of equity markets to understand how the crypto markets will evolve. Fifteen years ago, financial markets were less sophisticated, and you had traders on every floor. Traders bought stocks and they did some re-balancing from time to time. That was pretty much it.

“Now, computers and machine learning process the data and execute trades, not traders. Hedge funds in the financial markets today predominantly use algorithms and quantitative trading. We are going to see the crypto markets evolve in that same direction, but crypto will evolve 10 times faster than the way it did in the traditional equity markets.”

Financial services firms more broadly are using AI and machine learning to asset the credit-worthiness of borrowers, price insurance contracts, automate communication with some clients, and assess the risk of trades, according to a report from the Financial Stability Board.

AI Could ‘amplify financial shocks’, Claims FSB

However Mark Carney, FSB chief and Bank of England governor, has warned that new financial technologies have not yet proven they can weather a significant economic downturn or another financial meltdown. Technology like AI could “amplify financial shocks”, the has claimed.

The FSB warned of the “arms race” in AI which, as a result, may see financial services firms rely third-party providers. If those were to fail, the effect would ripple across the wider financial system and contribute to major disruptions at large financial firms, the FSB claimed.

“These risks may become more important in the future if AI and machine learning are used for ‘mission-critical’ applications of financial institutions,” said the FSB.

“Moreover, advanced optimization techniques and predictable patterns in the behavior of automated trading strategies could be used by insiders or by cyber-criminals to manipulate market prices.”

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