Quants

Hedge fund managers, market academics and risk experts are channeling their data-mining smarts to the world of clinical sciences.

The setback for the hedge fund, which slid as much as 14% in the first quarter, is another example of the turmoil wrought by the coronavirus.

In need-for-speed markets lashed by the spreading coronavirus, this breed of rules-based trading is paying off.

The investing strategy “is close to saturation,” and the cost of keeping up with the competition may be to blame, a new study suggests.

The academic duo who fueled the strategy’s boom want to know if worsening performance signifies a bout of misfortune or if something’s fundamentally broken.

David Vogel, who spent five years using data to study the impact of global warming, is starting the fund as pensions and large investors increasingly seek ESG investments.

It’s the second straight year that Cliff Asness’ quant firm is announcing layoffs.

Financed by their personal savings, the team behind the machine-learning fund have harnessed their engineering acumen to invest in developed markets.

Financial market data — unlike photos or road traffic information or chess games — is finite, and the algorithms can learn only from past performance.

Asset manager Millburn Ridgefield is banking on artificial intelligence as it moves further away from its 1970s-era tradition in trend following.

Claims by one firm executive that systematic investing “lends itself to providing liquidity” remain largely untested in a post-crisis bull.

Managers will actively evaluate an asset’s characteristics — its value or momentum, for example — to determine what to buy.

The activity began last Friday when 6.4 million shares hit the tape, fueling a record daily inflow for the fund.

The math wizards of the investment world are hoping to disrupt the established giants of the trillion-dollar credit market.

New products give institutional investors a fresh way to exploit the rise of machines.

Fear of a liquidity plunge outweighed political risks in a recent JPMorgan survey.

Even experienced managers are closing shop amid mounting costs, a tough capital raising environment and investors’ reluctance to pay high fees.

The model, which runs on IBM’s Watson platform, has suffered from overweight positions in technology and energy, the month’s worst-performing sectors.

Even momentum, which has made money in eight of the last 10 years, has plunged in 2019.

An AQR executive just sketched a blueprint for traders seeking to hitch a high-octane ride on the global credit cycle.