McKenzie source.  

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Today’s investment landscape is radically different than it was even a decade ago. Information moves faster, market leadership can shift quickly and investors must contend with everything from earnings reports and regulatory filings to geopolitical developments, shifting supply chains and rapidly evolving narratives around artificial intelligence.

For investors, the challenge goes beyond finding and analyzing information. It’s also a matter of knowing what to do with it.

As the volume of market data grows, investors are looking for ways to process that information more efficiently and reliably, and they are increasingly considering quantitative approaches to meet that need. For the first time, Quant funds are now the most sought-after hedge fund category, according to a survey of institutional investors collectively managing more than $1 trillion in assets, MarketWatch reported in January.

Along with this growing interest, quantitative investing has evolved considerably. Rather than replacing traditional investment research, many modern quant managers are combining fundamental analysis with advances in computing power, machine learning and natural language processing to evaluate opportunities at a scale that would be impossible through human analysis alone.

“The way we do things is much more akin to a fundamental manager, except we are using computing power to the hilt,” says Arup Datta, Head of Mackenzie Investments’ Global Quantitative Equity Team.