Blue Pool arming London investors with A-share ammo
The Hong Kong-based fintech, which combines A.I. with capital-markets expertise, says China’s entry to MSCI’s index creates an opportunity for alpha-seekers.
Hong Kong startup Blue Pool is preparing to raise money to finance its expansion to the U.K. and Australia, says co-founder Luke Waddington.
The company is using artificial intelligence to provide portfolio managers, analysts and sell-side traders with signals to make sense of the huge volume of information now available, helping them to try to beat markets.
Waddington argues that a major reason why actively managed funds have lost so much ground to index funds and exchange-traded funds is because human teams can no longer process the vast expansion of data available on companies.
“There’s a fundamental shift taking place [in financial markets], but the active investor process hasn’t been redefined,” he told DigFin. Although traders and analysts have the tools to crunch numbers fed from exchanges and other venues, they can’t manage the firehose of unstructured information, from analyst transcripts to media reports.
“The consumption of information has become a random walk,” he said, referring to the popular random-walk theory that says investors can’t consistently beat markets because of perfect information.
The MSCI moment
The founders, Waddington and Samir Rath, set up in Hong Kong partly because it is a smaller, less competitive city than London, and also because it is close to China.
China should represent a rich territory for A.I.-driven insights, Waddington says. A.I. can deliver information at scale, while in the case of China, its financial markets are immature and so there are plenty more opportunities for active managers to outperform.
With MSCI earlier this year deciding to include A Shares in its benchmark emerging-markets index, global institutional investors will now have to invest there.
The decision by Blue Pool to open an office in London reflects the founders’ belief they can offer the market not just a service to boost alpha, but one that can be especially useful in China, where few managers have experience or knowledge.
The business has so far been funded by the founders, or financed through revenues. The A-round is meant to raise $20 million. Some proceeds are to open the London office, while the rest will go to buying data, such as analyst transcripts.
The company has identified the people it intends to hire in London, but Waddington declined to name them. Blue Pool is also opening an office in Sydney with two people, complementing its offices in Tokyo and Mumbai.
The business is based on the assumption that active management can once again be successful if the process is modernized, meaning it can sift through vast amounts of information about companies and deliver insights and actions.
The team uses machine learning to parse and segment English- and Chinese-language texts, decoding symbols (letters or characters) to derive meaning. This process is scalable, but not smart, so a lot of development time has gone into building software that can establish a basic set of corporate-governance rules, and compare that to the market symbols being read. In other words, they are training their computers to think more like capital-market actors.
The next step, what Waddington calls A.I., is to create relationships between the basic framework of how companies are meant to be governed with a topic or outcome that a trader or investor might want to mine, such as a theme or a sector. It works by finding correlations, rather than causations, among assets (e.g. stocks, bonds or loans).
By putting the machine learning into context, the service is meant to provide value – by figuring out signals that affect company asset prices, which human analysts might not realize were relevant.
“This produces a set of signals that explain the truth,” Waddington said. “Then we let the client’s own process take over.”
Capital markets background
Blue Pool isn’t the only player trying to arm fund managers or traders with the ability to assimilate unstructured data.
Waddington says the team’s edge is their capital-market expertise: he was previously global head of electronic business and markets at BNP Paribas, in London and Hong Kong; as well as head of RBS’s prime brokerage in Tokyo. His co-founder, Samir Rath, has run trading and investment at boutique funds in the U.S. and Singapore, as well as also working at BNP Paribas’s capital markets desks in Asia.
The partners teamed up in 2014 after deciding it would be too difficult to build a business of making money from data while working within a big bank. “Incumbents struggle with the new means of production,” Waddington said, citing their reliance on mainframe servers and slow response times.
Blue Pool leverages AWS’s cloud to stay fast and low-cost. “My unit time and cost of production blows incumbents out of the water,” he said.