Can ‘Big Data’ Help Boost Investment Returns?

Many fund managers are turning to big data and automated processes for more detailed stock research

Sam Shaw 9 February, 2017 | 9:55AM
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Investors around the world will often talk about the ‘whites of the eyes’ test when considering an investment decision.

That may pertain to a fund selector who likes to have a coffee with a fund manager on whom they are conducting due diligence, or it might be a fund manager who insists on sitting across the table from the CEO of a prospective holding.

In these cases, human instinct and emotional decision-making are integral to the research process. But what about the apparently growing trend for funds to strip out the personality, rely on the rise of the machine and tap into the now-ubiquitous concept of ‘big data’.

Not so much a direct replacement for traditional human interaction, the use of data is more a supplementary method of conducting research – harnessing more information, more quickly. And the advances made possible are extreme.

Obtaining an Information Advantage

Goldman Sachs Asset Management (GSAM) runs a range of six Core Equity Luxembourg Sicavs, investing by geography and market capitalisation.

The team gives the example of Apple (AAPL). If one were to search for ‘Apple’ with a data provider, around 20,000 report results and 60,000 news articles would come up per year.

While you or I couldn’t possibly read them all within any meaningful timeframe, using data and automated processes, that information can not only be read, but analysed and then included in a due diligence file to help influence a particular investment decision.

BlackRock runs a range of quantitative funds grouped together as Scientific Active Equity (SAE) that similarly uses algorithms and big data to help gain an information advantage that supports the investment process.

As David Wright, EMEA head of product strategy for SAE, summarised: “The main advantage is the way we can use the explosion of information - whether that's a ramping of the information that already exists on companies or the explosion of data because of the internet. We see so much human activity happening online and now we have ability to record it.”

Using Data To Support Traditional Investment Techniques

He believes investors must have the instinct in the first place, and subsequently use data to help validate, or perhaps refute, those ideas.

“We are not saying these techniques should replace traditional investing but they can be a powerful tool alongside some of the other techniques,” he said.

Big data is often linked to impressive numbers: the number of internet users rose from 9% of the world’s population in 2000 to 43% by the end of 2013, according to World Bank statistics, which has led to an explosion in the volume of data generated to 2.5 trillion bytes every day.

Jacques-Aurélien Marcireau, who runs the Global Data fund at Edmond de Rothschild, explained that the pace of growth is so fast that 90% of today’s data has been created in the last two years.

“No one could expect this trend to change or even reverse. Big data is an investment theme in its own right, and decision-takers are fully aware of that," he said.

Investing In the Data ‘Mega-Trend’

He explains that while the technology sector may be the start point, it is only part of the story, with industrial maintenance, customised offers, energy efficiency, preventive medicine and driverless cars being just a few ways in which big data can be exploited.

“[That can have] potentially significant repercussions on the economy as a whole," he said.

Data isn’t just about numbers and spreadsheets. Images, videos, light and sound can all be scanned, logged and interpreted to help build a fuller picture of companies and trends, indicating a particular sentiment or direction of travel.

It grants you the ability to read through tens of thousands of reports, in multiple languages, instantly, while text mining for clues around a positive or negative tone, for instance.

Satellites are being used to take photographs of oil storage tanks to assess the size of the shadows, which can indicate how much oil is held in the tanks, assisting with estimating inventories ahead of official figures released by Opec.

“I find the whole area fascinating and believe big data is definitely here to stay,” said Richard Philbin chief investment officer at Wellian Investment Solutions.

“It's just a different way of solving the same problem, which is how to find the right assets to put into our portfolios. I see it as a way of still doing fundamental research to gain an information advantage.”

Don’t Forget The Long-Term Fundamentals

But not everyone is convinced.

Gary Potter, co-head of the multi-manager team at BMO Global Asset Management, isn’t a fan of quantitative investment approaches.

“So many of them tend to fail at inflection points,” he said.

Potter is concerned the industry might be moving away from its fundamentals.

"These concepts that are based on macro input and linked to big data... they might work, but very often they don't. I fear the industry may be going down a road of launches based on whims and fads around short-term momentum, rather than the fundamentals of building a long-term, quality investment portfolio." 

The information contained within is for educational and informational purposes ONLY. It is not intended nor should it be considered an invitation or inducement to buy or sell a security or securities noted within nor should it be viewed as a communication intended to persuade or incite you to buy or sell security or securities noted within. Any commentary provided is the opinion of the author and should not be considered a personalised recommendation. The information contained within should not be a person's sole basis for making an investment decision. Please contact your financial professional before making an investment decision.

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Securities Mentioned in Article

Security NamePriceChange (%)Morningstar
Apple Inc186.88 USD-2.11Rating

About Author

Sam Shaw  is a financial journalist and broadcaster writing for Morningstar.

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