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.

Die Zeit, da man sich in Österreich mit Hedgefonds oder Ma­naged-Futures-Produkten an normal verdienende Privatkunden wenden konnte, ist lange vorbei. Vielfach enttäuschte Anleger und strengere Regularien gestalten jeden Neuzugang im Massengeschäft schwierig bis unmöglich. Hinzu kommt, dass Trendfolgestrategien seit der Finanzkrise relativ schwach abgeschnitten haben, weshalb das Interesse daran stark nachgelassen hat. Wer also heute mit Alternative-Investment-Konzepten startet, kann sich allenfalls an Vermögensverwalter, Dachfondsmanager oder Family Offices wenden, die sich darüber im Klaren sind, dass der Bullenmarkt bei Aktien nicht ewig weiterlaufen wird.

Professor Andrew Lo of the Massachusetts Institute of Technology (MIT) says he wants to be like Harvey Lodish and help save the life of a relative one day. Lodish, a molecular and cell biologist at MIT, helped develop a drug to treat a rare genetic disorder known as Gaucher disease. Little did Lodish know at the time that later his grandson would be diagnosed with this disorder and Lodish’s pioneering work would save his grandson’s life. Lo’s goal may seem lofty considering he is a financial economist, not a doctor or a scientist. Like many of us, he has watched helpless as family members and friends are diagnosed with cancer. But sitting in the waiting room of a doctor’s office one day, Lo decided to follow in Harvey Lodish’s footsteps and take the first step towards saving a life.

Patients with a rare, chronic disease can find themselves in a conundrum when seeking treatment: Researchers can’t find enough patients to enroll in a statistically rigorous clinical trial and there is uncertainty in the regulatory path. Frustrated by the lack of treatment options on the market, patients may be willing to accept a certain level of risk that device manufacturers normally shy away from.

Nowadays, it’s a rare selloff that isn’t blamed on the growing heft of a strategy called risk parity. But to a 52-year-old quant who helped develop it, the problem isn’t that risk parity is too big, but too small. From his office on Boston Harbor, Edward Qian of PanAgora Asset Management has made it his life’s work trying to prove that the strategy — more popularly associated with Ray Dalio’s Bridgewater Associates — isn’t just a tool for divvying up stocks and bonds in hedge funds. Nor is it the destructive force that critics say could ruin markets. Pointing to three small photos of star clusters propped up at the edge of his desk, Qian says its principles are to investing what gravity is to the universe.

Professionals from the finance and technology sectors convened in New York City on 16 September to learn about how recent technology innovations are transforming banking and the stock market as well as credit cards, loans, and other financial products and services. The theme of the event, hosted by MIT Sloan, was “FinTech (Financial Technology) and the Disruption of Finance.” The speakers made it clear that machine learning and other new technologies are certain to bring big changes to the financial industry.

From her office overlooking the sprawling trading floor of a major bank, a risk manager sits before a bank of computer monitors. Suddenly a buzzer sounds and a red message flashes on a screen: Biometric alert, trader # 37. With a few mouse clicks, she’s looking at the data. Blood pressure – elevated. Heart rate – elevated. Adrenaline – elevated. Cortisol – elevated. When she ponders this information, she notes that none of the dozens of other traders on the floor are showing elevated readings. Leaving her office, she walks quickly down a long row of desks, traders and flashing screens until she arrives at station # 37. There, a man in his early thirties, tie loosened at his neck, his foot tapping, sits staring intensely at the screen in front of him.