Robin Wigglesworth, Financial Times, has an excellent piece on hedge fund DE Shaw, here… Do read the whole thing…
“Even among peers on Wall Street, DE Shaw is still a largely unknown quantity. “They’re really smart, but I’ve never quite understood them,” says one quant hedge fund manager. “They are one of those places where you just don’t know exactly what [it is] they do, except that it is some mix of quantitative and discretionary investing.”
This hybrid approach is not new. DE Shaw ventured out of its quantitative roots soon after its founding. But it now manages a wide array of strategies, ranging from completely machine-driven and dizzyingly complex, to human and artisanal, such as “distressed debt” investing and activism. Roughly half of the $50bn it manages are in quant strategies, and the rest in discretionary or more hybrid funds.
“The world tends to view quantitative and fully discretionary investing as distinct and separate, but the opportunity set [to make money] is not as cleanly divided,” says Max Stone, one of the five members of DE Shaw’s executive committee, along with Eddie Fishman, Eric Wepsic, Julius Gaudio and Anne Dinning.”
And this:
”The goal is to find patterns on the fuzzy edge of observability in financial markets, so faint that they haven’t already been exploited by other quants. They then hoard as many of these signals as possible and systematically mine them until they run dry — and repeat the process. These can range from tiny, fleeting arbitrage opportunities between closely-linked stocks that only machines can detect, to using new alternative data sets such as satellite imagery and mobile phone data to get a better understanding of a company’s results.”
And:
““Mr Stone has a stuffed albino peacock sitting on a cabinet in his office, a reminder that sometimes markets — like nature — serve up the unexpected. He is wary of criticising the quantamental rush, but also cautions that it could end in tears.
“There are some good ideas at the intersection of systematic and discretionary investing,” he says. Nonetheless, “if you don’t have experience of separating signal from noise,” he adds, “you can easily be led astray by extraneous data.””
Leave a Reply