Hedge Funds

A hedge fund is an alternative investment fund available only to sophisticated investors, such as institutions and individuals with significant assets. These funds typically utilize a variety of investing techniques and asset classes to achieve their return on assets for the fund investors.

Artificial Intelligence, Machine learning, and crowdsourced algorithmic trading platforms are challenging professional fund managers as the tools, data, and data science techniques powerful enough to forecast market moves better are becoming more readily available to anyone with an internet connection.

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Quantitative Strategy, Trading, and Algo Development Industry News

Discretionary Managers Seek Alpha in Alternative Data

Alternative data providers see huge potential in providing their data to discretionary asset managers who are losing assets to quantitative and systematic funds.

As active managers trail the performance of passive index funds and exchange-traded funds (ETFs), discretionary fund managers are scrambling to consume big data analytics into their decision making process.
While early movers in the big data analytics industry have mainly been quant hedge funds and systematic fund managers, the next wave is going to be discretionary fund managers, according to panelists at an event sponsored by Wall Street Horizon, EstimizeOTAS Technologies and FlexTrade Systems.
Read the full story on Traders Magazine Online
Quantitative Strategy, Trading, and Algo Development Industry News

Quants Run Wall St. Now?

From LinkedIn by  May 30, 2017
We were sort of confused when we noticed the Wall Street Journal is doing an entire series on what they’re calling “the quants,” including the lead article title “The Quants Run Wall Street Now.” Now? Are they not familiar with Scott Patterson’s 2010 book “The Quants: How a New Breed of Math Whizzes Conquered Wall Street and Nearly Destroyed It.” Mr. Patterson was, after all, a staff reporter of… wait for it… the Wall Street Journal. We get it, algorithms and quants and machine learning and roboadvisors and all the rest are the latest buzz words in a financial world increasingly comfortable with the concept of computers running things, from self-driving cars to algorithm-driven shopping recommendations to self-adjusting thermostats. There’s also the fact that “Quant hedge funds” are responsible for 27% of all U.S. stocks traded these days, just slightly behind individual investors at 29%, and now comfortably ahead of such trading by “other hedge funds” and traditional asset managers. Read the full post on LinkedIn
Stock Market, Quantitative Strategy, Trading, and Algo Development Industry News

Machine learning set to shake up equity hedge funds – Financial Times

AI seen becoming powerful enough to forecast market moves better than humans

Financial Times May 25, 2017 by: Lindsay Fortado and Robin Wigglesworth
Machine learning poses a threat to equity hedge funds within the next decade as the technique becomes powerful enough to forecast market moves better than humans, one of the earliest investors in the industry is forecasting. Jeff Tarrant, the founder of Protégé Partners, says that the model of hedge funds charging “2 and 20” — a 2 per cent management fee and 20 per cent performance fee — for investing in large-cap stocks rising and falling “doesn’t work any more” and is ripe for disruption. He pointed to the overhaul of other industries in the past decade at the hands of engineers and scientists. “Jeff Bezos picked off the bookstore business. Apple totally picked off the music business and Netflix totally changed television. Now [machine learning] is going to pick off the hedge funds.”
Read the full story on Financial Times
quantitative algo trading conceptual dashboard

Hedge funds and VCs are throwing money at ex-Bridgewater data scientists’ startup

If you aren’t being recruited because you didn’t work at Bridgewater, maybe it is time to create your own hedge fund operation by creating an algo on CloudQuant. EFinancialCareers is reporting that hedge funds and VCs are throwing money at ex-Bridgewater data scientists’ startup. “Banks and hedge funds used to want to hire quantitative analysts, frequently PhDs in engineering, math, statistics or a hard science such as physics or chemistry. But the main problem financial services firms are facing right now is the data itself. It’s messy, unstructured and still difficult to use for alpha opportunities.” Read the full article on EFinancialCareers.com