The Revolutionary Way Of Using Artificial Intelligence In Hedge Funds
The integration of artificial intelligence and the financial industry has always been a match made in heaven—high volumes, the quantitative aspect of finances, need for expediency and accuracy are ideal for the unique skill-set of AI. But, can it impact the high-risk, high-return world of hedge funds? Several companies think so.
What is a hedge fund?
Today, there are more than 10,000 hedge funds that manage approximately $3 trillion in assets. A hedge fund is an investment partnership between a professional fund manager and “limited partners” or investors. The limited partners contribute funds, while the general partner manages the fund according to the fund’s strategy to maximize investor returns and minimize risk. Hedge fund managers can use trading techniques where they “hedge” themselves by going long (if they predict that the market will rise) or shorting stocks when they believe the market will drop. Hedge funds are generally considered riskier investments.
AI on Wall Street
Hedge fund companies use humans to build and train the original system but soon the system can use artificial intelligence to trade stocks entirely without any more human intervention. Companies trading or working toward trading with AI systems include San Francisco startup Sentient Technologies, Renaissance Technologies, and Bridgewater.
Market research firm Preqin estimates that 1,360 hedge funds use computer models to make the majority of their trades. While hedge funds have used computer models to help make trades, it’s the innovation of an AI machine having full autonomy and not relying on a data scientist for an assist that is revolutionary. While models are helpful, unless they get updated as quickly as mark conditions change, they will diminish in performance over time without being updated to reflect new market intelligence.
How AI Trades Stocks
Artificially intelligent machines analyze inordinate amounts of data at extraordinary speeds that is impossible for humans. They learn from the information they analyze to improve their trading acumen. This information includes market prices to corporate financial reports and accounting documents to social media, news trends, and macroeconomic data. Once the information is analyzed by thousands of machines, the machines then “vote” on what action to take and the best trades to make.
Many firms use AI technologies including deep learning and one inspired by genetic evolution to power its AI trading team.
Deep learning helps train large neural networks to recognize patterns in the data and be able to analyze data in a variety of forms such as audio, images, and text. Today, unstructured data is a crucial piece of the puzzle and allows the AI systems used for trading to review news articles, social media posts, and other unstructured data to help inform their strategy.
Even though “past performance does not predict future returns” AI systems also use historical stock data to test their performance and learn from how the market reacted in the past. In a form of “evolutionary computation,” the AI determines the winners and uses their “genes” to create the next generation of trades. This process continues indefinitely, and the result is a smarter trader population. Eventually, this technology can be used to improve today’s deep learning capabilities.
One of the reasons hedge funds tend to use a variety of AI technologies in their trading systems is to avoid another company imitating their methods. If everyone would be able to use the same smart systems to trade and the unique recipe for success was realized, it would undermine the competitive advantage companies get by using AI to stay a step ahead of their competition.
Marr, B. (2019, March 6). The Revolutionary Way Of Using Artificial Intelligence In Hedge Funds. Retrieved from https://www.forbes.com/sites/bernardmarr/2019/02/15/the-revolutionary-way-of-using-artificial-intelligence-in-hedge-funds-the-case-of-aidyia/#3274b36357ca
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