Posted by & filed under Hedge Fund Performance.

By Susan Barreto, Editor of Alternatives Watch

While the hedge fund indices and inflow data tell us that this year was less than optimal for hedge funds, much can be learned about what the future for the industry holds by eyeing some of the main trends at the three largest global hedge fund firms – Bridgewater, Renaissance Technologies and AQR Capital Management.

Combined the firms manage approximately $290 billion. Each, however, have their own technological pursuits when it comes to trading, investing and views for what is around the bend.

It’s been a big year at Bridgewater, with big changes coming next year as well. The firm’s leadership succession plan is being executed, while a new senior investment team member will also be joining in 2020.

In early December, the $160 billion firm announced the next phase of its leadership transition with the pending departure of Co-CEO Eileen Murray, who will be leaving the world’s largest hedge fund firm in March 2020. David McCormick is now planning on serving as the firm’s sole CEO as Founder Ray Dalio remains co-CIO and co-chairman. 

“It is a remarkable thing when a founder who built a company over a number of decades can successfully transition the company to the next generation,” said Dalio. “Eileen Murray was key to that. Now that we have made that transition, Eileen wants to move on to something new and to make room for others. I can’t possibly express how grateful I am to her for helping us get to this point. I expect that she will always be a close friend.”

It is worth noting that Murray was one a growing number of women in top leadership positions within the hedge fund industry, but that is not to say other talented women are not waiting in the wings. Former Bessemer Trust CIO Rebecca Patterson will be joining Bridgewater Associates as a senior member of the hedge fund firm’s investment research team in January.

Meanwhile Jim Simons, founder of Renaissance Technologies and one of the most legendary hedge fund managers may be preparing for a hefty tax bill, according to the Wall Street Journal. 

Reportedly the firm sent out a letter to its current and former employees warning that the Internal Revenue Service could act by demanding back taxes and penalties if they invested in the firm’s hedge funds through its 401(k) plan and IRAs, without paying fees. The tax case could affect other investment management shops that also allow employees to invest in in-house fund offerings in a tax-advantaged way free of fees.

Still Simons had a good 2019 having recently been profiled by Gregory Zuckerman in “The Man Solved the Market.” The book was released in early November and has already become a bestseller in detailing how Simon’s algorithmic driven trades made history and forged a $23 billion fortune. 

While Simon’s computer-driven trading revolutionalize the hedge fund industry in the 1980s, machine learning has made steady headlines in 2019. 

AQR Capital Management has struggled with its alternative risk premia product with returns of -1.21% for the year ending November 30. This is all the while winning over trustees to manage equity portfolios at large pension plans with its academic approach to asset management.

A new white paper released by the firm that manages $61 billion in hedge fund assets details how machine learning can provide money-making insights from news articles. 

The firm’s academic ties and mindset is what has attracted many institutional investors to its various products. The authors of “Predicting Returns with Text Data” include Bryan Kelly, professor of finance and associate director of the International Center of Finance at Yale University in addition to his work at AQR. 

The team in the paper introduces a new text-mining methodology to extract sentiment information from news articles to predict asset returns. The paper analyzed text mining of the Dow Jones Newswires to extract return-predictive signals through isolating a list of sentiment terms, assigning weights to the terms via topic modeling and then lastly aggregating the terms into an article level “sentiment score.”

What the team dubs a supervised learning approach also relies on less computing power than other machine learning methods. 

“The portfolio based on our model delivers excellent risk-adjusted out-of-sample returns, and outperforms a similar strategy based on scores from RavenPack (the industry-leading commercial vendor of financial news sentiment scores),” the researchers wrote.  

For AQR, it could be another new product offering in the works, but the researchers behind the new methodology say that it is just that they targeted business news articles for the purpose of portfolio choice. Ultimately it could be adapted in any setting.

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