new construct
Robot Analysts Outwit Humans on Investment Picks, Study Shows
They beat us at chess and trivia, supplant jobs by the thousands, and are about to be let loose on highways and roads as chauffeurs and couriers. Now, fresh signs of robot supremacy are emerging on Wall Street in the form of machine stock analysts that make more profitable investment choices than humans. At least, that's the upshot of one of the first studies of the subject, whose preliminary results were released in January. Buy recommendations peddled by robo-analysts, which supposedly mimic what traditional equity research departments do but faster and at lower costs, outperform their flesh-and-blood counterparts over the long run, according to Indiana University professors. "Using this type of technology to make investment recommendations or to conduct investment analyses is going to become increasingly important," Kenneth Merkley, an associate professor of accounting and one of the authors, said by phone.
Robot analysts outwit humans on investment picks over long run, study shows
They beat us at chess and trivia, supplant jobs by the thousands, and are about to be let loose on highways and roads as chauffeurs and couriers. Now, fresh signs of robot supremacy are emerging on Wall Street in the form of machine stock analysts that make more profitable investment choices than humans. At least that's the upshot of one of the first studies of the subject, whose preliminary results were released in January. Buy recommendations peddled by robo-analysts, which supposedly mimic what traditional equity research departments do but faster and at lower cost, outperform their flesh-and-blood counterparts over the long run, according to Indiana University professors. "Using this type of technology to make investment recommendations or to conduct investment analyses is going to become increasingly important," Kenneth Merkley, an associate professor of accounting and one of the authors, said by phone.
HBS/MIT Sloan Professors Use New Constructs' Earnings Distortion Scorecard to Reveal First-Ever Empirical Evidence Corporate Managers Are Biased & Exploit Footnotes to Manipulate Earnings
NASHVILLE, TN / ACCESSWIRE / November 19, 2019 / New Constructs, the leading provider of insights into the fundamentals and valuation of private and public businesses, today announced an update to its Oct. 15 announcement of Harvard Business School (HBS) and Massachusetts Institute of Technology (MIT) Sloan School of Management's findings that markets inefficiently assess core earnings because too few investors read footnotes, which include a steadily increasing number of material unusual gains/losses. The professors used New Constructs' AI-powered Earnings Distortion Scorecard to reveal the first-ever empirical evidence that corporate managers are biased when reporting earnings and exploit footnotes to manipulate quarterly results. The New Constructs dataset solves a very big problem for investors: how to get an accurate measure of profits. In the past quarter, New Constructs' Earnings Distortion Scorecard accurately predicted earnings beats and misses for major publicly traded equities including AmerisourceBergen, Qualcomm, CVS, AbbVie, Dupont de Nemours, and Lam Research. New Constructs' founder and CEO David Trainer commented, "There's a new landscape for fundamental data and research. We now have proof that we can't just trust the numbers analysts or executives give us. Money managers and advisors have a fiduciary duty to provide advice based on the true earnings or put their clients at undue risk. On the bright side, we are seeing the democratization of access to higher-quality research based on this new technology. Individual investors can now get the same unvarnished data as large institutional investors."