Ever-increasing torrents of data from emerging markets hold the key to peer-beating returns, according to Man Numeric, a quant investment arm of Man Group, the world’s largest publicly-listed hedge fund manager.
(Bloomberg) — Ever-increasing torrents of data from emerging markets hold the key to peer-beating returns, according to Man Numeric, a quant investment arm of Man Group, the world’s largest publicly-listed hedge fund manager.
Ori Ben-Akiva, director of portfolio management at Boston-based Numeric, says his core emerging-market funds have largely ditched the traditional country-by-country approach. They focus instead on trawling social media accounts, e-commerce websites and other sources to inform their choices from around 5,000 developing-nation companies.
What Numeric’s strategists call a “data revolution” in emerging markets comes as stock pickers struggle to beat benchmark indexes and exchange-traded funds take the lion’s share of investment flows amid an ongoing debate on whether humans or machines provide better returns.
“Compared with history, it is much more difficult to generate equity outperformance by getting a handful of top-down country calls correct,” Ben-Akvia said in an interview. “Our focus is really about trying to identify the most of attractive company specific opportunities within an investment universe.”
Man Group acquired Numeric in 2014 and since then its assets under management have more than doubled to $36 billion, with 20% of that invested in emerging markets.
Numeric’s emerging-markets core fund has handed investors a 4.5% return since its inception in 2015 compared with 2.3% for relative MSCI Inc. indexes. In the last three years through March 31, it has returned 11.1% per year, net of fees, versus 3.2% for the benchmark.
Still, it failed to negotiate the global turmoil that followed Russia’s invasion of Ukraine, losing 9.8% in the past 12 months compared with a 0.9% gain for the index, according to a statement on its first-quarter results.
Man Group is known for its early adoption of AI and machine learning, but Ben-Akiva said flesh-and-blood fund managers are still needed in parts of the asset class.
He cited the example of Russian stocks, whose low valuations triggered buy signals from a range of quantitative analytical models. With the war in Ukraine ongoing and international sanctions in force, it took a human to decide they were cheap for a reason, he said.
“Timing markets, predicting market outcomes is very difficult,” Ben-Akiva said. “We focus on what we think is more repeatable and sustainable, which is to focus on the company-level opportunities.”
–With assistance from Esteban Duarte and Nishant Kumar.
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