BlackRock’s Mark Wiseman tells IPE how the firm is integrating quant and fundamental active strategies 

As the voice of $6trn (€5.1trn), when BlackRock speaks, Wall Street and Main Street alike take note. Sometimes the dollars do the talking on their own. In line with the structural shift to passive equities over recent years, the firm now has almost $500bn, or over 8% of client AUM, concentrated in just two S&P 500 index strategies – $366bn against the index and a further $126bn in the iShares Core S&P 500 ETF, according to eVestment.

This sheer asset volume sometimes shifts the focus away from the firm’s $300bn active equities business, where Mark Wiseman was hired from Canada Pension Plan Investment Board in 2016 to oversee active equity globally, and to shepherd the integration of quant and fundamental equities on a single platform. BlackRock’s $300bn in active equity may represent less than 10% of its overall equity AUM but it still dwarfs others. For instance, State Street Global Advisors managed $73bn in active equity AUM at year-end 2016.

When BlackRock announced a restructuring of its active equity capabilities in March 2017 it was building on plans laid out over a year previously. In an internal executive communication of January 2016, CEO Larry Fink and president Rob Kapito told staff that BlackRock’s fundamental and active quant capabilities would be combined into a unified business. 

“In a market environment characterised by more volatility, lower beta and increased dispersion, clients are increasingly looking for active equity solutions irrespective of whether they are fundamental or quantitative strategies,” the two executives wrote. This was to become Project Monarch, named after the archetypal North American butterfly and chosen to symbolise transformation.

Wiseman elaborated on this in March 2017 in a public statement on Project Monarch, in which he said the project was about “harnessing the power of human and machine”. He said: “Traditional methods of equity investing are being reshaped by massive advances in technology and data sciences.”

He continued: “The active equity industry needs to change. Asset managers who simply use the same techniques and tools from the past will limit their ability to generate alpha and deliver on client expectations.”

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Speaking with IPE in December, Wiseman elaborated on the strategy, outlining what he says would be an 18-month project in all: “It’s not an easy task because it’s really about changing behaviours and changing everything from our product suite to our investment processes to incorporate more modern techniques and technologies.”

While the project has been driven by senior leadership, “it’s not about creating the unified field theory of quantamental investing,” says Wiseman, using the portmanteau term that has been deployed recently to describe such integration of quant and fundamental capabilities. “It really is about using quantitative techniques increasingly as a tool for our fundamental investors, as well as investing significant additional resources both into systematic business and into our emerging markets business.”

An overall data and integration unit has been tasked with delivering analytics more broadly. The data and analytics team, based in India, has doubled in size and has been repositioned to serve both the systematic and fundamental sides, while the overall data acquisition budget has tripled.

Simple quant screens in fundamental investing are nothing new. In concrete terms, Wiseman says, one way BlackRock can enhance its fundamental investing approaches is by applying quant analytics to optimise position sizes in fundamental portfolios. 

“If you are a bad stock picker that’s not going to help you,” Wiseman says. “But if you are a good stock picker we think you can pick up something between 15 and 25bps of outperformance just by using quantitative techniques to size your position.”

In terms of big data and advanced techniques such as machine learning, fundamental teams will be able to use BlackRock’s data and integration team to answer very specific questions that can be researched and delivered back in a format that they can use. Wiseman says: “It’s not about signals or algos but a lot of it is the same tools and datasets used in different ways.”

Most analytics are done in house by acquiring proprietary data sets or sometimes by acquiring data on a joint venture basis, while outside providers are sometimes used for bespoke analytics. Wiseman says: “By and large because we want this to be proprietary because we want to generate alpha from it so we are building these capabilities or already have of them in house.”

Another goal is for the data and analytics teams to understand the investment processes to a degree that they can deliver insights to portfolio managers independently. “It goes two ways,” Wiseman says. “One is the fundamental investors saying I want to do a study of airline ticket pricing or footfall traffic, and so forth. Then it’s also about our data scientists saying they can derive insights from a data set that could be relevant to a portfolio.”

A second part of the project has been to refine the product range around four key areas: ‘core alpha’ quant; high-conviction alpha in concentrated, unconstrained and absolute return formats; outcome-orientated strategies and country or sector specialisation. 

“What we have to do as investors is move away from being index or factor huggers, so we are barbelling our strategies.” Low tracking error portfolios will be largely delivered systematically; higher conviction, more concentrated strategies will be delivered using human intuition but increasingly with modern analytics. In the US, $30bn of client mutual fund assets has been repositioned from traditional low-tracking error fundamental to low-fee systematic.

Wiseman says the role of humans in equity investing will increasingly involve learning how to use computing power to provide better insights, building better analytical tools and overlaying those tools with a degree of human intuition. 

Overall, he concludes: “We are in the early innings of a data and information revolution in investing. And I think the rate of change will increase but I don’t think it will ever obviate the need for humans. We are still believers in the art of investing; we do not think that investing can necessarily be reduced to algorithms.”

Nevertheless, watch this space to see how BlackRock integrates artificial intelligence in portfolios – a real frontier of technology-driven investment.