Fidelity Investments is turning to its internal big data and behavioral science to create a competitive advantage, as the asset management giant lays the foundation for systematic funds.
The company’s head of quantitative research and investments, Neil Constable, told MarketWatch in an interview that he hired Gilbert Haddad, who previously worked at that of Steven Cohen Point72, to lead Fidelity’s scientific investment decision-making team. Haddad started at Fidelity last week, according to Constable, former head of global equities at Jeremy Grantham’s GMO.
The decision science effort is new to Fidelity and builds on the activities of its fundamental portfolio managers and analysts, according to Constable. He said the company, which oversees $ 4.2 trillion in discretionary assets, has massive internal data on trading activity, analysts’ ratings on stocks and bonds, events surrounding investment decisions – and results.
“Think of it like you’re playing ‘Moneyball’,” Constable said, referring to the title of Michael Lewis’s book on the important ideas that contribute to the success of baseball. “It’s really about applying behavioral finance and behavioral science to understand” what portfolio managers and analysts are doing and not doing.
The aim is to “help them understand their own biases” so that they can strengthen their investment processes, Constable explained. It also aims to use the collective information from Fidelity’s fund managers and analysts to create ‘signals’ used in new ‘quantitative products’.
Read: The explosion of ‘alternative’ data gives regular investors access to tools previously used only by hedge funds
Fidelity’s scale and decades of internal trading and analytical data give it a ‘unique’ informational advantage in the asset management world, where fund managers can access the same alternative external data, according to Constable . He expects the team led by Haddad to initially consist of a few associates and grow from there.
A Point72 spokesperson declined to comment on Haddad’s departure.
The Fidelity agent spent several years studying math and science before starting a career in finance.
After earning an undergraduate degree in Physics and Mathematics from the University of Calgary in 1996, he obtained his Masters in Applied Mathematics from the University of Cambridge in 1997. He then obtained a PhD in Physics from the University of Cambridge. McGill University in 2001 and later the same year he became a postdoctoral fellow at the Massachusetts Institute of Technology.
Constable entered finance in 2004 as a quantitative researcher at State Street Corp. He then worked for nearly 13 years at GMO in Boston before becoming Director of Investments at CircleUp in San Francisco in 2019. He joined Fidelity in July 2020 to lead its quantitative research. and investment group, or QRI.
“This job did not exist before at Fidelity,” said Constable, who reports to Bart Grenier, the chief of staff. asset management company. He said Grenier created QRI last year to bring together quants of fixed income and equities, as well as data scientists who work in artificial intelligence and machine learning.
At the head of QRI, Constable supervises more than 80 people. The teams in quantitative fixed income, quantitative equities, advanced data and analytics, quantum index solutions and quantitative research services have been brought together under him to provide differentiated data and analysis to traditional active management teams of Fidelity in equities and fixed income securities.
QRI’s second mandate, he said, is to develop systematic products based on single data sources for Fidelity clients.
“One of the reasons I was hired was to create a systematic, scalable and ultimately very customizable product line for Fidelity’s customers,” Constable said. “To start this we just have announced a month ago that we will acquire the quant active team of Geode Capital Management.
Under the deal, Fidelity brings actively managed quantitative equity funds and separately managed account businesses to Geode for a total of $ 15 billion in assets, according to Constable. Both companies will report to QRI, he said.
Pressure from Fidelity to step up its quantitative efforts comes as 2021 marks the 75th anniversary of the founding of the Asset Manager by Edward C. Johnson 2d in 1946, according to his website. The scale of the company across asset classes over the decades, along with its technology, creates “opportunities everywhere”, in Constable’s eyes.
“The amount of data generated internally is huge,” he said. “So the systematic collection, organization, analysis and use of this data in all of our investment products is a significant competitive advantage, especially as a quant. “
“Data, data everywhere”
Data is much easier to obtain today than it was when Fidelity began decades ago.
Nicholas Colas, co-founder of DataTrek Research, captured this in an August 4 memo in which he described a visit to Fidelity as a Wall Street analyst who began covering the auto industry in 1991. “Fidelity was the largest client in the brokerage industry in the United States. He wrote.
He remembered walking into Fidelity’s “card room”, the walls of which were lined with “data graphics” plotting everything from inventory to gross domestic product. Colas saw a “group” of portfolio managers around a wall with charts showing each sector’s weighting in the S&P 500 as well as other stock indexes dating back decades, according to its note.
“In the days before the Internet, it was not easy to get information,” he wrote.
“In the modern world, it’s data, data everywhere,” Constable said. “A lot of technologies are needed to harness this data and turn it into real information. “
Fund managers have turned to so-called alternative data in an attempt to beat the market. The data can be collected from online sources such as social media or come from “really obscure” or specialist groups in areas such as the shipping industry and retail, Constable said.
Fidelity’s advanced data and analytics team acquires alternative data, much of which requires some form of AI, such as natural language processing, to organize it and make it useful to investment teams, a he declared.
As for the “card room,” the agent said it still exists at Fidelity, with another group maintaining it. In his view, the room, a “first manifestation” of the firm’s emphasis on data collection and analysis in active management, is “very much in line with the overall philosophy of Fidelity.”
It also means how times have changed.
“In 1950, the cutting edge of technology was collecting all of this data manually and systematically putting it on charts so that investment teams could use it for stock or bond selection,” Constable said. Now, that involves computers collecting “every piece of random data generated by every industry or every government entity,” he said, and systematically “cleaning” it for portfolio managers to use.
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But it’s Fidelity’s own data that will set it apart from the quantitative competition as it ventures into new areas, according to Constable.
The asset manager already has a few examples of funds that are “mostly systematic”, such as the Fidelity High Yield Factor ETF, FDHY,
he said. Constable added that the exchange traded fund is also managed with some managerial discretion.
QRI also leverages internal Fidelity data with the longer-term view of managing purely systematic equity and fixed income funds, which will eventually be available to Fidelity’s retail clients.
“A purely systematic approach is on the horizon,” Constable said. “But we have certainly established a foothold in that direction.”