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The 'artificially intelligent' hedge fund rises

- By Sweenie Dabas and Mayur Bansal

Right now, artificial intelligence (AI) is certainly the buzzword in financial services. From robo-advisors (automated financial advisors and planners) and humanoid robots in branches, to chat-bots (chat robots for customer service) and machine learning algorithms for fraud detection and credit scoring, AI is inundating the world of banking, payments, and wealth management. And the big, secret world of hedge funds is actively exploring this technology as well.

The traditional systematic trading techniques used by hedge funds have to rely on human beings to develop the mathematical models to find trading opportunities. Now, AI is enabling the development of self-learning programs where the initial software application is created by humans, but after which it can develop itself, learn through real-time experience, and adjust its strategies accordingly. The shift from discretionary to systematic hedge funds is fast taking place and is visible in the number of hedge funds being launched. In 2014, more than 40 percent of new hedge funds launched were systematic funds, i.e., they utilized computer systems to select investments, which was the highest ever till that time. AI-based hedge funds have also justified their existence by outperforming average industry returns consistently since 2008, with 2012 being the only exceptional year in which they under-performed.

Artificial intelligence is being used for natural language processing (NLP), sentiment analysis, big data analysis, and deep learning to explore investment opportunities. In addition to processing vast amounts of financial data to extract hidden trends, AI techniques enable the analysis of non-financial data like news articles, tweets, pictures, videos, etc., and recognize patterns though human-like inferences. Advanced techniques such as Bayesian networks and evolutionary computation are also being used to build machine learning models for hedge funds.

Artificially intelligent systems are being explored and developed by well-established hedge-funds like Bridgewater Associates, Two Sigma Investments, and Renaissance Technologies, as well as new AI-focused firms including Sentient, Rebellion Research, and Aidyia, with the total managed capital running into trillions of dollars.

Some examples include:
1) Two Sigma manages assets worth US$35 billion and uses advanced AI technologies to discover new investment opportunities. One of the applications it uses is NLP to analyze the Federal Reserve (FED) minutes of meeting in order to gain insights into focus areas of the FED
2) Hong Kong-based Aidiyia is another flag bearer which has developed a trading robot inspired by genetics. Aidiya started trading in US equities in 2015
3) San Francisco-based startup, Sentient Technologies, has also been trading using AI-based systems since last year
4) Numerai is another AI-based hedge fund which has been developed by a community of anonymous data scientists. It makes use of a monthly tournament to get AI based-models from various data scientists to predict the stock market movements. Numerai received a funding of US$1.5 million from Renaissance Technologies

Since its inception, AI has witnessed contrasting hype cycles. Currently, however, the industry seems primed for disruption and innovation and AI's evident broad-based applications and benefits make it a potential game-changer. But it will not be devoid of challenges - AI requires not just skilled human resources, but also technology infrastructure that can work on extremely low latencies. It will also need extremely supportive reconciliation, reporting, and various other operation support applications. In addition, the regulatory side of use of AI in hedge funds remains hazy. But as AI becomes more mainstream, more robust regulations will surface that will require financial institutions (FIs) to develop stringent controls and risk assessment frameworks.

Like any other disruptive technology, there would be some AI techniques that fail or lead to unexpected results. But overall, it could lead to some big systemic changes in the hedge fund industry.

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