Home Finance Pioneer AI Hedge Fund - DE Shaw

Pioneer AI Hedge Fund – DE Shaw

In 1988, Revolution Books, a tattered communist bookstore situated near New York-based Union Square, got some unusual neighbors: a group of programmers attempting to make it in the financial markets. Back in the day, the growing hedge fund established by a former professor of computer science at Columbia University, David Shaw, was simply a scrappy startup.

With the exposed extension cords and pipes, tripping on a given cable could have easily shut down the whole trading system.

Nonetheless, DE Shaw is one of the notable players in the hedge fund space today, with more than $50 billion assets under management.

A considerable portion of the hedge fund’s popularity is owed to being the place where Jeff Bezos first started working on the company that would later be known as Amazon.

Nonetheless, DE Shaw has not been left behind, as the broader investment industry tries desperately to reinvent itself, specifically for the 21st Century.

In fact, the hedge fund has advanced dramatically from the computer-powered, algorithmic “quantitative” trading it assisted in pioneering back in the 1980s.

DE Shaw is now a notable leader in integrating quantitative investing with conventional “fundamental” human-driven approaches like stock-picking.

This mutual benefit has been considered “quantamental,” especially by asset managers currently trying to do something similar.

Most industry stakeholders are convinced this could be the future and are now rushing to recruit computer experts in a bid to assist them in realizing the benefits of integrating artificial intelligence, machine learning, and big data into their plans.

READ MORE: 10 Applications of Machine Learning in Finance

READ MORE: Hedge Funds Testing the Waters with Artificial Intelligence

Former chairman of Google, Eric Schmidt is an investor in DE Shaw Hedge fund
Former chairman of Google, Eric Schmidt is an investor in DE Shaw Hedge fund

The former chairman of Google, Eric Schmidt, who currently has a 20% stake in DE Shaw, projects that this strategy will considerably redefine the investment management space.

“People have gone insane about this, but in a good way,” Mr. Schmidt says. “We are at the beginning of a new era in artificial intelligence. These technologies should benefit investing as well.”

However, there are still a lot of challenges; with many experts warning that improper implementation can cause catastrophic results.

Wall Street has witnessed several quant hype cycles in the past, and most remain doubtful that traditional companies can sufficiently restore culture in a bid to unleash the potential benefits of a more hybrid strategy.

The combination of DE Shaw’s performance and the secrecy surrounding what the hedge fund firm does continues to fascinate and vex both its counterparties and rivals.

“They’re like a calibrated machine that can respond to nearly every market,” said the head of an investment bank’s hedge fund trading desk.

After holding several interviews with some senior executives of DE Shaw, the Financial Times reported that is has gained some rare insight into the workings of the “machine.”

LCH Investments revealed that DE Shaw is fourth among the top-grossing hedge fund entities of all time, having generated more than $29 billion for its investors since its early days.

Back in 2018, the hedge fund’s leading $14 billion Composite Fund, which has remained closed to new investors since 2013, returned more than 11% net-of-fees to investors, in spite of the problems facing the financial markets.

READ MORE: World’s Biggest Asset Manager BlackRock Building AI Lab

READ MORE: How Hedge Funds Are Using Artificial Intelligence

That marked DE Shaw’s seventh double-digit increment of the last decade.

On the other hand, its $7.6 billion “macro” fund dubbed Oculus achieved a 5.9% return in 2018 whereas Valence, a $7 billion stocks-focused fund, returned 8%.

Among its Wall Street peers, De Shaw remains a widely unknown entity. “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.”

The hybrid technique is not a new discovery.

DE Shaw moved out of its quantitative background shortly after its inception.

However, the hedge fund currently manages a variety of strategies, from fully machine-powered and sophisticated, to artisanal and human.

Nearly half of the $50 billion worth of assets under its management are all in quant strategies whereas the rest are in more hybrid or discretionary funds.

Max Stone, who is among the five members of the five executive committee hedge fund
Max Stone, who is among the five members of the five executive committee

“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,”

Said Max Stone, who is among the five members of the five executive committee members of De Shaw, along with Anne Dinning, Julius Gaudio, Eric Wepsic, and Eddie Fishman.

Some of DE Shaw’s rivals are concerned about the hedge fund moving far away from its roots.

Nonetheless, the hedge fund’s executives insist that their goal is to have a data-powered “quanty” strategy across the entire board, irrespective of whether it is investing in renewable energy or high-speed arbitrage.

“Our core strength is thinking scientifically about things, so it doesn’t feel like we are wandering away from our roots,” says Alexis Halaby, the company’s head of investor relations.

Currently, DE Shaw employs nearly 1,300 individuals including 25 holders of International Math Olympiad medals and 80 PhDs.

All the company’s interviewees go through a series of analytical questions intended to help them showcase their suitability to be part of the hedge fund, which is something that even Larry Summers, the ex-secretary of the US Treasury, went through in 2006.

A former hedge fund manager, Mahmood Noorani, who currently heads analytics firm Quant Insight, considers the people working at DE Shaw “less alpha male and more gentle scientists.”

This has allowed the hedge fund to survive the kind of leadership change that has brought down some of its rivals.

In fact, many hedge funds start to crumble after their founder resigns.

However, DE Shaw has flourished since Mr. Shaw semi-retired back in the early 2000s to focus on “computational biochemistry” research.

Instead of one person, DE Shaw’s central committee, made up of five individuals, handles all the daily operations of the company. “You’d be hard-pressed to find a management textbook that says a committee is a good way of running a company,” says Mr. Stone. “But it works for us.”

This is one of the aspects that grabbed Mr. Schmidt’s attention when he acquired the 20% stake in the hedge fund from the Lehman Brothers back in 2015.

“It feels like Silicon Valley in Manhattan,” he says. “People get consumed by hierarchy, but the evidence shows that flat structures and diverse teams operating collectively have better outcomes.”

MORE – Top 25 AI Software for the Banking Industry

However, sometimes things do not always work out.

Last year, DE Shaw fired a senior fund manager, Daniel Michalow, after an internal assessment revealed “gross violations of our standards and values.”

Mr. Michalow penned an open letter admitting that he may have deserved the action taken against him by DE Shaw for being “an abrasive boss.”

Nevertheless, he emphasized that his dismissal had nothing to do with sexual misconduct.

Michalow also criticized DE Shaw for its “lavish, alcohol-filled parties” and revealed that senior relationships with junior staff and regular visits to strip clubs were a common thing in the company.

The hedge fund refused to respond to the accusations, citing continuing legal proceedings.

What’s more, Michalow has filed a defamation lawsuit against DE Shaw coupled with other claims associated with the announcement of his discharge from the company.

DE Shaw’s executives are more than happy to talk about how the hedge fund manages money, even though some of the details can be vague.

The company has a reputation for running several quant strategies that are too quick or sophisticated for human understanding, an aspect of the company that most quantitative analysts are hesitant to accept.

DE Shaw’s executives claim that they also rely on common sense to rule against their algorithms, another abomination in a sector where human involvement can be seen as a weakness.

Several of these manual interventions are evident.

For instance, when Russia seized the Crimean portion of Ukraine back in 2014 and began stirring up conflict in the country’s eastern province, DE Shaw responded by rapidly dialing back its exposure, primarily to the Moscow stock market.

Other techniques need more than a human hand, for example taking advantage of prolonged disagreements between Tencent and Naspers, a South African-based holding company behind the ownership of almost a third of the Chinese-based technology giant.

Usually, they carry out their trading in lockstep, even though they at times diverge due to South African politics or wider emerging market stress – which opens up a lucrative opportunity.

Even though the right moment to make a move can mostly be modeled, it is best combined with the secrecy of a human fund manager.

However, DE Shaw still notices a lot of opportunities available in the quantitative investing side, particularly its non-hedge fund investing enterprise, DE Shaw Investment Management (DESIM).

In terms of size, DESIM has quintupled since 2011 and currently manages $24 billion.

To boost this figure, the company is currently growing into what is called “risk premia,” steadily taking advantage of hypothetically timeless drivers of returns, including the tendency for cheaper or smaller stocks to outdo the entire market over time.

Traditionally, these have been some of the factors that hedge funds may have indirectly or explicitly harnessed as well as charged high fees for – even though they have nowadays been packaged up into cheaper, simpler vehicles by companies like BlackRock and AQR.

DE Shaw is also now increasing its investment in computer science, establishing a machine learning research entity headed by Pedro Domingos, an author of The Master Algorithm and a professor of computer science and engineering.

Cede Crnkovic, a DE Shaw managing director, said that a fully-operating quantum computer could be revolutionary. “Computing power drives everything, and sets a limit to what we can do, so exponentially more computing power would be transformative,” he says.

Almost all traditional investment entities are rushing to recruit technologists, programmers, and data scientists, and transform themselves into human-machine hybrid companies.

DE Shaw’s undeniable success in connecting both worlds provides an appealing template for the company’s rivals.

Nonetheless, most “pure” quants are not convinced that traditional asset managers possess the cultural expertise required to attain success, citing that companies cannot merely recruit a group of scientists and ask them to work together with 50-year-old fund managers armed with MBAs and expect to get things done.

Others fear that by failing to understand the challenges, they may end up harming themselves and or their investors.

“There are some good ideas at the intersection of systematic and discretionary investing,” says Mr. Stone. Nonetheless, “if you don’t have experience of separating signal from noise,” he adds, “you can easily be led astray by extraneous data.”

READ MORE: The Big Problems with Machine Learning Algorithms in Finance

READ MORE – Data Science – 8 Powerful Applications

For most, the 1998 summer was defined by France’s impressive victory at the World Cup, the Spice Girls losing one of its members, and the Monica Lewinsky saga involving the White House.

However, for the financial industry, that particular summer is remembered as the duration when some of the best Wall Street minds fell apart.

The fall of Long-Term Capital Management, a hedge fund firm that was headed by Salomon Brothers’ ex-trader John Meriwether and advised by two Nobel laureates Robert Merton and Myron Scholes, made the headlines.

However, the market turmoil also almost killed DE Shaw, which had made a considerable number of similar trades as LTCM with the same substantial chunks of leverage.

“The market environment was harrowing,” says Eddie Fishman, who now sits on the DE Shaw executive committee. “But the lessons served us well in subsequent crises.”

The “quant quake” back in August 2007 and the 1998 crisis act as reminders that even some of the most complex computer-driven strategies can collapse.

Looking at the popularity surrounding quantitative investing, and the scramble to identify and mine emerging trading signals, there have been concerns that markets could be headed into a repeat of historic industry turmoil.

According to history, the two key dangers include “crowding” and leverage.

The harm associated with aggressive leverage is well-known.

However, if most investors are crowding into a similar trade or security, they can lead to severe harm, primarily when trading conditions decline rapidly.

Although many hedge funds utilize far lower leverage than in 2007 or 1998, the massive amount of money that quant funds have raised since the crisis is triggering crowding fears, reducing returns for everybody, and increasing the risk of a sudden reversal that would ultimately lead to a collapse as the affected investors pull out.

READ MORE: RPA – 10 Powerful Examples in Enterprise

Source FT

Subscribe to our newsletter

Signup today for free and be the first to get notified on the latest news and insights on artificial intelligence

KC Cheung
KC Cheung has over 18 years experience in the technology industry including media, payments, and software and has a keen interest in artificial intelligence, machine learning, deep learning, neural networks and its applications in business. Over the years he has worked with some of the leading technology companies, building and growing dynamic teams in a fast moving international environment.
- Advertisment -

MOST POPULAR

AI Model Development isn’t the End; it’s the Beginning

AI model development isn’t the end; it’s the beginning. Like children, successful models need continuous nurturing and monitoring throughout their lifecycle. Parenting is exhilarating and, if...