Early in January in a Chicago hotel, Campbell Harvey gave a rip-snorting presidential address to the American Finance Association, the world’s leading society for research on financial economics. To get published in journals, he said, there’s a powerful temptation to torture the data until it confesses—that is, to conduct round after round of tests in search of a finding that can be claimed to be statistically significant. Said Harvey, a professor at Duke University’s Fuqua School of Business: “Unfortunately, our standard testing methods are often ill-equipped to answer the questions that we pose.” He exhorted the group: “We are not salespeople. We are scientists!”
It was a typical New York summer day, the kind where arriving at Goldman Sachs’ perfectly air-conditioned offices in downtown Manhattan was a blissful release from the humid weather outside. But for Gary Chropuvka it proved to be one of the worst days of his life. Mr Chropuvka worked at Goldman’s money management arm, specifically at Quantitative Investment Strategies, a division staffed by mathematicians, computer scientists and physicists. Even at Goldman, the QIS employees were considered intellectual superstars. Their prowess at decoding the signals of financial markets meant the unit managed $165bn at its peak — more than any hedge fund group. But on August 6 2007, everything unravelled. As soon as US markets started trading, the previously wildly successful automated investment algorithms coded by the QIS brainiacs went horribly awry, and losses mounted at a frightening pace.
Andrew W. Lo of the Massachusetts Institute of Technology was named winner of the top $2,500 prize in the Bernstein Fabozzi/Jacobs Levy Awards. Mr. Lo, a professor of finance at the Sloan School of Management and director of the MIT Laboratory for Financial Engineering, was honored for his article “What is an Index?”
Es besteht eine große Kluft zwischen Daytrading/technischer Analyse und der akademischen Welt. Dies läßt sich auf die effiziente Markthypothese reduzieren, über die Sie hier mehr erfahren können. Für viele Akademiker sind Daytrader Krach machende Trader, und die technische Analyse ist bestenfalls Voodoo. Demzufolge gibt es zwischen diesen beiden Fronten keinen Austausch. Daytrader sind auf Ihre Tradingcharts fixiert. Professoren der Finanzwissenschaft labern vor Ihren Studenten, während sie versuchen, Ihre Forschungen in renommierten Fachzeitschriften unterzubringen. Der Ideenaustausch ist jedenfalls gering.
Andrew Lo is the Charles E. and Susan T. Harris Professor at the MIT Sloan School of Management and director of the MIT Laboratory for Financial Engineering. In his research, he straps sensors to traders and watches how their pulses and body temperatures change when markets dive or trades go bad. The technology could be used elsewhere in a bank to potentially address problems before they escalate.
AlphaGo, an artificially intelligent (AI) software program, defeated the world champion of an ancient board game called Go on March 15, 2016. The game is immensely complex, with a total combination of possible moves numbering several hundred orders of magnitude more than the number of atoms in the universe. Winning the series four-to-one, AlphaGo’s victory showcased significant advances in AI’s ability to recognise and learn obscure patterns, and adapt strategies.
If it sometimes feels like your boss or management are watching you like Big Brother, you may not be far wrong. Technology is increasingly allowing companies of all types to more closely monitor what their staff are doing. Tesco, for example, uses electronic armbands to track the movements of stock pickers in its warehouses in Ireland.
It has been a whirlwind year for the stock market amid the presidential election, interest-rate increases and the Dow Jones Industrial Average’s climb to the 20000 mark. And there has been no shortage of advice on what to do and what to ignore along the way. Our panel on The Wall Street Journal’s Experts blog offered their take on a variety of investing topics–from IRA rollovers to how to get in on the podcast craze. You can read what they had to say throughout the year here. And below are five of the most-popular investing-related Experts posts of 2016.
Andrew Lo, the MIT professor who recently proposed creating a megafund to finance a cure for cancer, has another way for the financial services community to help eradicate seemingly intractable diseases. Lo was the keynote speaker at a data science conference put on by the consulting group Mass Insight last Friday. The purpose of the conference was to explore how Massachusetts could become a leader in Big Data and machine learning. It brought together everyone from bank executives to venture capitalists to government officials at the Federal Reserve Bank of Boston.
The president-elect has been happily moving stocks via Twitter since even before the election. Twitter, it turns out, can also tell investors what the market will do next, at least on specific days. With Federal Reserve officials set to gather this week for their final policy meeting of the year, research has shown there might be value in combing through social-media posts before Fed days to gauge how stocks might react.