Robots Are Eating Money Managers’ Lunch - "A wave of coders writing self-teaching algorithms has descended on the financial world, and it doesn’t look good for most of the money managers who’ve long been envied for their multimillion-­dollar bonuses."

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Rishi Ganti used to help manage the personal fortunes of hedge fund founders David Siegel and John Overdeck, whose quantitatively driven strategies turned them into billionaires. Ganti, 45, says he’s glimpsed the future of his industry. A wave of coders writing self-teaching algorithms has descended on the financial world, and it doesn’t look good for most of the money managers who’ve long been envied for their multimillion-­dollar bonuses.
On a cold spring day, Ganti, clad in a gray hoodie, takes quick sips of Earl Grey tea at a bakery in Manhattan’s Tribeca neighborhood and explains that many of his peers don’t yet realize their careers won’t last. “Algorithms are coming for your job—they only ask for electricity,” says Ganti, jabbing his finger on a lime-green laminated table. “Algorithms are already reading, processing, and trading the news even before the photons have hit your retina.” Yet few money managers are alarmed by the threat. “They’re anesthetized,” Ganti says.
 


He started plotting out the impact of algorithms while working for Siegel and Overdeck at Two Sigma Investments, before striking out two years ago to start his own firm, Orthogon Partners Investment Management Co. To survive, Ganti says, money managers should look beyond the multitrillion-dollar stock exchanges, bond-trading platforms, and big deals backed by private equity and venture capital. To a greater or lesser extent, computers can see all those markets, assess how they’re performing, and start detecting patterns that could reveal profitable trading strategies.
Ganti’s answer is to look for what are known in the industry as esoteric assets—the most obscure stuff he can find. He’s arranged alternative funding for charter schools in the U.S. and paid cash upfront to collect judgments due at Brazil’s supreme court. His team also has purchased nonperforming loans at a discount in Portugal and partnered with local experts in Mexico to fund government infrastructure programs. It’s even provided interim financing for refugee camps in Italy. The point about these investments, he says, is that they require “high human capital” to manage, even if they’re plentiful. “It’s like dark matter,” Ganti says. “They dwarf the visible stuff lit up by markets.”
It’s not unusual to hear hedge fund managers argue that investors need to go off the beaten path to boost returns. What Ganti is saying is that money managers need to go there to save their own careers. He thinks that about 2 percent to 7 percent of the hedge fund industry’s $3 trillion of assets will jump every year from predominantly human oversight to computers.
Ganti, who earned his Ph.D. in economics at Harvard, concedes this is just his guesstimate, but there’s plenty of evidence of a trend gathering force. Funds that use algorithms for trading, according to Hedge Fund Research Inc., already account for almost a third of the industry’s assets. BlackRock Inc., the world’s biggest asset manager, is shifting some stock analysis to machines. Bridgewater AssociatesPoint72 Asset Management, and JPMorgan Chase are trying automation techniques. Then there’s the huge shift of assets to index funds, which can be thought of as a very simple but dirt-cheap and effective form of computerized investing. The problem for hedge fund managers is they cost so much, traditionally charging 2 percent of assets and taking a 20 percent cut of profits. “Those are vast sums of money for recognizing patterns,” Ganti says.
Ganti’s former boss Siegel said last year he’s “very worried” that machines could soon cost large swaths of the global workforce their jobs. Some economists think financial managers in general, unlike most other categories of workers, will be protected from automation. But the ones who make their living picking investments for clients and trading in the markets may be at risk, says David Autor, an economist at the Massachusetts Institute of Technology who studies labor markets. “The distribution of rewards in finance will become even more skewed, with a small number of ‘superstars’ making huge sums, and much of the routine work done by machines,” he says. “With luck, the cost of financial services will come down. It’s not a great era in which to be a midlevel fund manager.”
It’s one thing to delve into esoteric markets to distinguish yourself from the quants. It’s quite another to do well—the assets are hard to value and risky by nature. Orthogon’s strategy, for example, includes scooping up receivables and other claims owed to those in need of immediate cash—a refugee facility waiting for payment on a contract from a charity, for example. Tod Trabocco, a managing director at Cambridge Associates LLC, a Boston-based firm that advises clients on investing, says fund managers have to research such assets carefully. “There’s the risk that a hospital, for instance, billed a government agency incorrectly and now is owed less,” he says. “Or a purchaser claims that it got a defective product and now doesn’t owe any money.”
Orthogon, which runs $110 million and started investing in 2016, returned 5.4 percent in its first eight months and 5.6 percent this year through May, according to an investor document. At Two Sigma’s private proprietary investment group, which also managed employee money, Ganti’s wagers on esoteric assets returned an annual average of about 14 percent from September 2008 to December 2014, according to the investor document. Prior to Two Sigma, Ganti did stints at hedge fund HBK Capital Management and JPMorgan’s proprietary trading group.
“He’s smart, a little eccentric, and you can’t get further away from public markets and computers than what Rishi does,” says Paul Morelli, a managing partner at Vernal Point Advisors, which invests in Orthogon. Ganti says the demise of money managers won’t happen all at once—there are still bank tellers and candlemakers. He likens the process to a mountain surrounded by rising flood waters: The base is easily traded markets, such as stocks. Higher up are bonds and derivatives, then niche investments such as aircraft leasing, movie rights, and drug royalties, followed by human-heavy dealmaking such as mergers and buyouts. Esoteric assets are at the peak. “I’m surprised how slowly people are walking up the mountain instead of running,” he says. “They’re moving much too slowly.”

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