Big-Data Analytics Firm Palantir Technologies Eyes IPO - Report


Palantir Technologies Inc. - a private big-data analytics software company - is considering going public, according to a report in The Wall Street Journal on Thursday, Oct. 18. The 14-year-old California company could see its valuation hit $41 billion, the Journal reported, as the company was in discussions with investment banks Credit Suisse (CS) and Morgan Stanley (MS) for a possible initial public offering later next year, according to the report. Palantir has so far raised $2 billion in venture capital and private equity, according to The Journal reported that the company plans to bring in $750 million in revenue over 2018, about $150 million more than in 2017. Co-founded by famed venture capitalist Peter Theil, Palantir today has around 2,000 workers and has worked with global intelligence agencies as well as various industries, most recently inking deals with major airlines and signing a $7 million contract with the National Institutes of Health.

How Big Data Can Use Language To Find The Hidden Reason To Sell A Stock


Traders and financial professionals work at the opening bell on the floor of the New York Stock Exchange (NYSE). It's no secret on Wall Street that a "sell" recommendation in sell-side research reports is exceedingly rare, and it can't be chalked up to today's bull market recently surpassing its ninth birthday. According to FactSet data, only 6% of analyst recommendations on S&P 500 companies are "sell" ratings or the equivalent, lending credence to the notion that conflicts of interest persist despite reform efforts to make recommendations more objective in nature. Put simply, negative recommendations can place an analyst in the virtual penalty box when it comes to getting access to companies, and the effects are clear in a business where access is king. So, is there still use to looking through research reports to figure out which stocks are worth buying and selling?

Will AI eat the fund manager's job in India? AccuraCap shows it will


Hedge fund Renaissance Technologies is looked upon by Wall Street with awe and envy in equal measure. Particularly, Medallion Fund, an employees only fund it runs. Bloomberg last year wrote the fund has returned more than $55 billion, making it more profitable than funds run by feted veterans such as George Soros. The Renaissance flagship fund, which will turn 30 next year, has returned more than 25% profits in most of its years of investing. Money doubles in a little more than three years at that rate.

Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy: Cathy O'Neil: 9780553418811: Books


A New York Times Book Review Notable Book of 2016 A Boston Globe Best Book of 2016 One of Wired's Required Reading Picks of 2016 One of Fortune's Favorite Books of 2016 A Kirkus Reviews Best Book of 2016 A Chicago Public Library Best Book of 2016 A Best Book of 2016 An On Point Best Book of 2016 New York Times Editor's Choice A Maclean's Bestseller Winner of the 2016 SLA-NY PrivCo Spotlight Award "O'Neil's book offers a frightening look at how algorithms are increasingly regulating people… Her knowledge of the power and risks of mathematical models, coupled with a gift for analogy, makes her one of the most valuable observers of the continuing weaponization of big data… [She] does a masterly job explaining the pervasiveness and risks of the algorithms that regulate our lives." She is an academic mathematician turned Wall Street quant turned data scientist who has been involved in Occupy Wall Street and recently started an algorithmic auditing company. She is one of the strongest voices speaking out for limiting the ways we allow algorithms to influence our lives… While Weapons of Math Destruction is full of hard truths and grim statistics, it is also accessible and even entertaining. O'Neil's writing is direct and easy to read--I devoured it in an afternoon." Weapons of Math Destruction opens the curtain on algorithms that exploit people and distort the truth while posing as neutral mathematical tools. This book is wise, fierce, and desperately necessary."