BOSTON — Cold weather this week didn’t matter to the crowds at the AI World conference here, as activity around artificial intelligence continues to heat up. Over three days, more than 2,200 attendees learned about the latest advances in machine learning, deep learning, and the industries being affected by AI.
Andrew W. Lo é um autor prolífico. Professor de finanças na Sloan School of Management, do Massachusetts Institute of Technology (MIT), ganhou reconhecimento do público, por causa de seu livro A non-random walk down Wall Street ( Uma caminhada não aleatória por Wall Street , sem edição em português), e dos profissionais, por seus artigos em periódicos importantes de finanças e economia. Lo conquistou muitos prêmios em sua carreira.
Thus far, 2018 has proven to be a prosperous year for many in the industry, thanks in no small part to the strength of the U.S. economy.
And while economists are predicting a slowdown in growth next year, the next 12 months, barring unforeseeable incidents, should remain strong, with few signs of a pullback on the horizon.
"The economy is clearly strong," said Andrew Lo, a professor at MIT's Sloan School of Management and director of the MIT Laboratory for Financial Engineering. "We've got pretty low unemployment, very reasonable inflation, and all eyes are on the stock market, which has done quite well. I think, overall, both in the United States and more broadly around the world, things are going quite well. In that kind of an environment, it's no wonder people are confident about the future and willing to spend money on things like vacation and travel."
At its worst, finance leads to crises and economic dislocation and, yet, it's absolutely vital to solving many of the problems society faces today. MIT's Andrew W Lo introduces some of the best books on finance and explains how it can change the world for the better.
At the height of the credit crunch in 2008, academics at the London School of Economics were infamously caught off guard when the Queen of England asked why no one saw the financial crisis coming. Now, 10 years after the collapse of Lehman Brothers Holdings Inc. on Sept. 15, 2008, economists, regulators, policymakers and finance industry insiders are asking themselves where the next financial crisis could come from, and what danger signals they should watch for, to avoid being blindsided again.
While there are several areas of potential concern, industry experts broadly do not believe a systemic collapse on the same scale of 2008 is on the horizon.
If your house is on fire, what is the plan? Head for the exit, naturally. But if a market crash is burning a big hole in your investment portfolio, selling out may not be the best course of action. The very same emotions and biases that can lead to good decisions in many areas of daily life can lead us astray in matters of money, experts say.
Statisticians use it. Non-statisticians have heard of it (likely in the context of the standard threshold of p = 0.05). While it’s not the only component of a clinical trial design, the p-value helps determine the maximum acceptable level of uncertainty associated with clinical evidence and, in a way, the fate of patient access to a new medical device.
But, is the traditional 0.05 threshold too restrictive for the patient populations willing to accept more uncertainty, depriving them of treatment options? Is it too permissive for other patient populations? Can we optimize clinical trial design by considering patients’ urgency for new therapeutic options, as well as their willingness to accept uncertainty?
Artificial intelligence will reshape the world of finance over the next decade or so by automating investing and other services—but it could also introduce troubling systematic weaknesses and risks, according to a new report from the World Economic Forum (WEF).
Compiled through interviews with dozens of leading financial experts and industry leaders, the report concludes that artificial intelligence will disrupt the industry by allowing early adopters to outmaneuver competitors. It also suggests that the technology will create more convenient products for consumers, such as sophisticated tools for managing personal finances and investments.
But most notably, the report points to the potential for big financial institutions to build machine-learning-based services that live in the cloud and are accessed by other institutions.
On June 17- 21, the Becker Friedman Institute at the University of Chicago (BFI) and the MIT Laboratory for Financial Engineering hosted the Macro Financial Modeling Summer Session for Young Scholars. For the third year, the camp brought together the next generation of economists and industry leaders to learn, discuss, collaborate, and find connections between macroeconomics and finance. Together, the “campers” explored the frontiers of this essential work, and provoked many stimulating discussions and new ideas.