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.

A Cowlar for every employee: Have you heard about the Cowlar? It’s a smart collar that dairy farmers can strap around the necks of cows to monitor their herds. It promises improved milk production, early disease detection, heat detection, and real-time monitoring and alerts. How would you feel about wearing one? I ask because it seems like it’s a question that more and more employers are asking their employees.

An employee ID badge that can track workers’ movements and listen in to their conversations is in the works to be available for companies to use starting very soon, according to a Washington Post article published on September 7. Critics of the new device are calling it “Orwellian” in nature, meaning it sounds like something that would take place in the book 1984 by George Orwell, which depicts an extreme totalitarian society where the government always has its eye on you, and freedom is nowhere to be found for the average citizen. In the book, the government is referred to by its citizens as “Big Brother,” and there are signs everywhere repeatedly reminding people that “Big Brother is watching you.”

Do you hog office conversations? Or not talk enough? Does your voice squeal? Do you sit very still at your desk all day? Or do you fidget under stress? Where do you go in the office? How much time do you spend there? To whom do you talk? An employee badge can now measure all this and more, all with the goal of giving employers better information to evaluate performance. Think of it as biometrics meets the boss.

"The trader was in deep trouble. A millennial who had only recently been allowed to set foot on a Wall Street floor, he made bad bets, and in a panic to recoup his losses, he’d blown through risk limits, losing $4.9 million in a single afternoon.

"It wasn’t a career-ending day. The trader was taking part in a simulation run by Andrew Lo, an MIT finance professor. The goal: find out if top performers can be identified based on how they respond to market volatility..."

Awareness of threats to global financial stability rose to unprecedented heights in the aftermath of the crisis of 2008-’09. Prodigious volumes of research have ensued, influencing analytical and monitoring approaches that continue to recast the way banks and other financial companies are regulated as well as those institutions’ sensitivity to systemic impacts on their business. There are, indeed, official bodies with systemic risk management responsibilities, engaged along with regulators, academics and other experts in the ongoing search for new ways to monitor and prepare for systemic risks to financial stability.

Healthcare Finance, a new course to be taught by Andrew W. Lo, the Charles E. and Susan T. Harris Professor, a Professor of Finance, and Director of the Laboratory for Financial Engineering at MIT Sloan, will cover the role of finance in the healthcare industry. It will emphasize the application of novel financing methods to facilitate drug discovery, clinical development, and greater patient access to transformative high-cost therapies.

During a half-hour interval on May 6, 2010, stock prices for some of the largest companies in the world dropped precipitously, some to just pennies a share. Then, just as suddenly and inexplicably, shares recovered to their pre-crash prices. This unprecedented event, burned into the memories of investors and regulators alike, is now known as the Flash Crash. Since that day, financial markets have seen flash crashes in US Treasury securities, foreign currencies, and exchange-traded funds (ETFs). Other puzzling, system-wide glitches are becoming more frequent as well. Without a doubt, our financial systems are complex and often unpredictable, and when they swing out of control they remind us how much we still have to learn about how they work and how inadequate our traditional methods of controlling them are.

"At the most rudimentary level, AI involves teaching machines to learn and to interact in order to undertake cognitive tasks that were usually performed by humans. The type of AI featured in sci-fi films in which machines possess a human-like intelligence, sometimes referred to as general artificial intelligence, remains a distant and elusive prospect. The most optimistic experts, such as Google’s director of engineering, Ray Kurzweil, predict that AI will be able to outsmart humans by 2029. Conservative predictions expect this to take at least 100 years, if at all..."

"Not that long ago, it looked like it was game over for the field of study that produced the mortgage backed security, the credit default swap and all manner of other exotic derivatives that exploded so spectacularly in the financial crisis of 2008.

"Now, financial engineering theory is being touted by several academics as the key to curing cancer faster, reducing the impact of climate change and imposing better risk discipline on the same banks that were once almost felled by the discipline’s creations..."

On this episode of the HBO documentary series, Andrew Lo discusses an idea he and colleagues developed with regard to the FDA approval process. They've developed a model that incorporates patient preferences into the design of clinical trials in order to set appropriate thresholds for FDA approval.

At a conference last year, I was approached by an audience member after my talk. He thanked me for my observation that it’s unrealistic to expect investors to do nothing in the face of a sharp market-wide selloff, and that pulling out of the market can sometimes be the right thing to do. In fact, this savvy attendee converted all of his equity holdings to cash by the end of October 2008. He then asked me for some advice: “Is it safe to get back in now?” Seven years after he moved his money into cash, he’s still waiting for just the right time to reinvest; meanwhile, the S&P 500 earned an annualized return of 14% during this period. Investing is an emotional process. Managing these emotions is probably the greatest open challenge of financial technology. Investing is much more complicated than other chores like driving, which is why driverless cars are already more successful than even the best robo advisers.