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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 including Hong Kong-based Aidyia . The Revolutionary Way Of Using Artificial Intelligence In Hedge Funds – The Case Of Aidyia
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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
While humans built the system being used by Aidyia in its hedge fund, artificial intelligence can trade stocks entirely without any more human intervention. The chief scientist and co-founder of the company, Ben Goertzel, quipped, "If we all die, it would keep trading." It trades in U.S. equities, and on its first day, it generated a 2 percent return. Other companies are also trading or working toward trading with similar systems including 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. Aidyia uses 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 Aidyia uses a variety of AI technologies in its trading systems is to avoid another company imitating its 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. The use of AI to trade stocks is certainly intriguing, but it hasn’t proven—yet—to be a resounding or guaranteed success. Aidyia’s CEO Ken Cooper claims in back-testing its algorithms had an average of 25 percent year-on-year return . Even though back-testing success doesn’t necessarily equate to real hedge fund success, it’s clear the company and others who are building AI systems to trade stocks have entered a new era on Wall Street.

The Revolutionary Way Of Using Artificial Intelligence In Hedge Funds -- The Case Of Aidyia

Reading Financial Data With AI
Artificial intelligence, previously just a sci-fi fantasy, is now here and outsmarting us all. Aidyia, a Hong Kong-based investment company uses an advanced AI program to read trends in trade, and execute them by itself. Human users just need to set certain parameters and modify the system as needed, but the hedge fund is practically run by the system, and it’s quite successfully. Aidyia’s chief scientist Ben Goertzel daringly says, “If we all die, it would keep trading.”
After analyzing market prices, macroeconomic data, and corporate accounting documents, the AI engines make daily predictions about the economy and then “vote” on the best course of action. Each engine is different – one is inspired by genetic evolution while another is based on probabilistic logic. Many hedge funds have been using advanced algorithmic processes for years now, but with the emergence of deep machine learning and AI, companies have been looking further into higher-level analysis and autonomous computer operations. Apart from trends in numbers, this tech can analyze more unstructured data like news articles, company reports, and social media posts, enabling them to gather broader insight. AI Future
Other investment companies focusing on AI-driven operations include Sentient in San Francisco, and Rebellion Research in New York. But financial data isn’t the only thing artificial intelligence has taken over-as a matter of fact, it’s only the start. Already, vehicles are using AI in self-driving cars that make road navigation safer and easier. AI is making waves in medicine, performing breast cancer mammograms with 99 percent accuracy. An AI-powered wearable headpiece is even letting the blind see. Because AI performs work in perfect repetition and reliability, there’s a lot of emerging studies foreseeing that the labor force will be largely replaced by cognitive technology. But takeover won’t just be for blue-collar jobs where automatons take over finicky, repetitive work. AI could take over the jobs of human experts like doctors, lawyers, and finance experts, or at least partner alongside these professionals, just like it is doing at Aidyia. What could this mean for us humans? At this point, academic discussion and study are ever imperative to ensure AI is used to benefit all.


The Future of Investing? AI-Run Hedge Funds

Then One/WIRED
Last week, Ben Goertzel and his company, Aidyia, turned on a hedge fund that makes all stock trades using artificial intelligence—no human intervention required. “If we all die,” says Goertzel, a longtime AI guru and the company’s chief scientist, “it would keep trading.”
He means this literally. Goertzel and other humans built the system, of course, and they’ll continue to modify it as needed. But their creation identifies and executes trades entirely on its own, drawing on multiple forms of AI, including one inspired by genetic evolution and another based on probabilistic logic . Each day, after analyzing everything from market prices and volumes to macroeconomic data and corporate accounting documents, these AI engines make their own market predictions and then “vote” on the best course of action. If we all die, it would keep trading. Ben Goertzel, Aidyia
Though Aidyia is based in Hong Kong, this automated system trades in US equities, and on its first day, according to Goertzel, it generated a 2 percent return on an undisclosed pool of money. That’s not exactly impressive, or statistically relevant. But it represents a notable shift in the world of finance. Backed by $143 million in funding, San Francisco startup  Sentient Technologies has been quietly trading with a similar system since last year. Data-centric hedge funds like Two Sigma and Renaissance Technologies have said they rely on AI. And according to reports, two others—Bridgewater Associates and Point72 Asset Management, run by big Wall Street names Ray Dalio and Steven A. Cohen—are moving in the same direction. Automatic Improvement
Hedge funds have long relied on computers to help make trades. According to market research firm Preqin , some 1,360 hedge funds make a majority of their trades with help from computer models—roughly 9 percent of all funds—and they manage about $197 billion in total. But this typically involves data scientists—or “quants,” in Wall Street lingo—using machines to build large statistical models. These models are complex, but they’re also somewhat static. As the market changes, they may not work as well as they worked in the past. And according to Preqin’s research, the typical systematic fund doesn’t always perform as well as funds operated by human managers (see chart below)
Preqin/WIRED
In recent years, however, funds have moved toward true machine learning, where artificially intelligent systems can analyze large amounts of data at speed and improve themselves through such analysis. The New York company Rebellion Research, founded by the grandson of baseball Hall of Famer Hank Greenberg, among others, relies upon a form of machine learning called Bayesian networks , using a handful of machines to predict market trends and pinpoint particular trades. Meanwhile, outfits such as Aidyia and Sentient are leaning on AI that runs across hundreds or even thousands of machines. This includes techniques such as evolutionary computation, which is inspired by genetics, and deep learning , a technology now used to recognize images, identify spoken words, and perform other tasks inside Internet companies like Google and Microsoft. The hope is that such systems can automatically recognize changes in the market and adapt in ways that quant models can’t. “They’re trying to see things before they develop,” says Ben Carlson, the author of A Wealth of Common Sense: Why Simplicity Trumps Complexity in Any Investment Plan, who spent a decade with an endowment fund that invested in a wide range of money managers. This kind of AI-driven fund management shouldn’t be confused with high-frequency trading. It isn’t looking to front-run trades or otherwise make money from speed of action. It’s looking for the best trades in the longer term—hours, days, weeks, even months into the future. And more to the point, machines—not humans—are choosing the strategy. Evolving Intelligence
Though the company has not openly marketed its fund, Sentient CEO Antoine Blondeau says it has been making official trades since last year using money from private investors (after a longer period of test trades). According to a report from  Bloomberg , the company has worked with the hedge fund business inside JP Morgan Chase in developing AI trading technology, but Blondeau declines to discuss its partnerships. He does say, however, that its fund operates entirely through artificial intelligence. The whole idea is to do something no other human—and no other machine—is doing. The system allows the company to adjust certain risk settings, says chief science officer Babak Hodja, who was part of the team that built Siri before the digital assistant was acquired by Apple. But otherwise, it operates without human help. “It automatically authors a strategy, and it gives us commands,” Hodja says. “It says: ‘Buy this much now, with this instrument, using this particular order type.’ It also tells us when to exit, reduce exposure, and that kind of stuff.”
According to Hodja, the system grabs unused computer power from “millions” of computer processors inside data centers, Internet cafes, and computer gaming centers operated by various companies in Asia and elsewhere. Its software engine, meanwhile, is based on evolutionary computation—the same genetics-inspired technique that plays into Aidyia’s system. In the simplest terms, this means it creates a large and random collection of digital stock traders and tests their performance on historical stock data. After picking the best performers, it then uses their “genes” to create a new set of superior traders. And the process repeats. Eventually, the system homes in on a digital trader that can successfully operate on its own. “Over thousands of generations, trillions and trillions of ‘beings’ compete and thrive or die,” Blondeau says, “and eventually, you get a population of smart traders you can actually deploy.”
Deep Investing
Though evolutionary computation drives the system today, Hodja also sees promise in deep learning algorithms—algorithms that have already proven enormously adept at identify images, recognizing spoken words, and even understanding the natural way we humans speak. Just as deep learning can pinpoint particular features that show up in a photo of a cat, he explains, it could identify particular features of a stock that can make you some money. More AI


The Rise of the Artificially Intelligent Hedge Fund

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Companies in this collection provide software and/or services to institutions participating in primary and secondary capital markets: institutional investors, hedge funds, asset managers, investment banks, and companies. 

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Aidyia deploys artificial general intelligence (AGI) technology to identify patterns and predict price movements in global financial markets. AGI is a branch of artificial intelligence aimed at learning mimicking the human brain's breadth, depth and generality of understanding. Applied to financial markets, the result is financial prediction and trading systems with a human like ability to not only recognize mathematical patterns in market data, but to understand what these patterns mean in a broader context. Without the human limitations of memory, emotion, bias and mood, AGI systems can apply their financial insights in an objective way.

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