Quants have gone from a niche practice to a dominant player — the largest and most important hedge funds in the world are heavily influenced by, or completely committed to, computer-run strategies.
The future of quantitative investing is under question, as a growing group of experts have been calling for more machine-learning techniques to be incorporated in a move away from the models that made so many people successful.
This year has not been kind to quants, as the volatility caused by the pandemic earlier in the year slammed many systematic funds that couldn’t keep up.
The power players of this area of finance will be the ones who will guide this ever-important industry subsection into its next phase.
This list is a combination of long-time, billionaire players, under-the-radar heavy-hitters, and entrepreneurial founders with serious pedigrees.
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The future of quant investing is the future of finance.
Quants are now kingmakers in the $3 trillion hedge-fund industry, with nearly every major fund dedicating ample resources to the space, whether it’s capital for strategies or resources for hiring and data feeds. And these strategies — increasingly popular over the last decade — do not operate in a vacuum.
The rapid — and emotionless — trading done by them have caused investors like billionaires Stanley Druckenmiller and Leon Cooperman to argue that they are warping the markets. Meanwhile, the unprecedented volatility in the markets in March caused many big-name quants to lose money, as their models struggled to keep up.
Funds such as Coatue’s data-driven systematic strategy and Credit Suisse’s QT Fund shut down thanks to the volatility and the unreliability of data during the beginning of the shutdown in the US.
See more: Credit-card data is broken. Here’s how hedge funds and banks are being forced to rethink one of the earliest alt-data plays.
What quant investing looks like in the next decade will largely be driven by the power players on this list — a combination of billionaire stalwarts, under-the-radar heavy-hitters at big-name funds, and new founders.
And there’s some general disagreement about what the next evolution of quant looks like. Marcos Lopez de Prado, the former head of machine-learning at AQR and a professor at Cornell, believes quants need to get away from models and focus on “nowcasting” — reacting rapidly new data as it comes in. Artificial intelligence and machine-learning techniques have spread across the industry to help digest the reams of data feeds that are the industry’s lifeblood; others are attempting to bring the quant strategies that worked so well in equities to the fixed-income space.
Lopez de Prado, in a recent webinar, said the biggest challenge the industry faces is “how can we make sense of the tremendous amount of data we have today that was not available three to five years ago?”
The power players of the industry are often a part of the firm’s data leadership, if not holding the purse strings of their data budgets themselves. How they process, structure, and …read more
Source:: Business Insider