Technology: AI and the Spectre of AutomationPrint | August 16, 2016
"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..."
Financial Engineering Helps Fight Cancer and Climate ChangePrint | June 20, 2016
"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..."
Alternatives Monthly: Andrew Lo’s StrategyPrint | May 28, 2016
Cambiar a Yellen por un ordenador: ¿y si la política de la Fed la decidiese la inteligencia artificial? (Spanish)Print | May 24, 2016
"Hazte a un lado, Janet Yellen, la automatización del lugar de trabajo está a punto de volverse personal. Imagínese si en vez de confiar en la presidenta de la Reserva Federal (Fed) se usara una computadora para transformar montañas de datos económicos en bruto en proyecciones fidedignas de desempleo, inflación y producto interno bruto. ¿Cuál es el mejor nivel para la tasa de fondos federales? Presione..."
Quest for Robo-Yellen Advances as Computers Gain on Rate SettersPrint | May 24, 2016
"Move over Janet Yellen, automation in the workplace is about to get personal.
"Instead of relying on the Federal Reserve chair, imagine using a computer to transform mountains of raw economic data into reliable predictions for unemployment, inflation and gross domestic product. What’s the best level for the federal funds rate? Press
“'The capability is here,' says Andrew Lo, director of the Laboratory for Financial Engineering at the Massachusetts Institute of Technology, near Boston. 'The biggest hurdle is the cultural barrier. You’ve got a lot of central bankers who are not as open to technology.'"
More Investment Needed to Help Cure CancerPrint | May 20, 2016
London Business School
London Business School
"Uncertainty around how long it will take to find a cure for different forms of cancer is forcing investors to reconsider pumping hundreds of millions of dollars into pharmaceuticals.
"But offering long-term debt rather than venture capital can help draw them back, according to Andrew Lo, Professor of Finance at the MIT Sloan School of Management. He was speaking at the Financial Innovations in Healthcare conference, held at London Business School (LBS) and supported by the AQR Asset Management Institute."
Ghosts in the Machine: Artificial Intelligence, Risks and Regulation in Financial MarketsPrint | April 25, 2016
"On the 15th March 2016, an artificially intelligent (AI) software programme called AlphaGo, defeated the world champion of an ancient board game called Go. 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 was emphatic. It also showcased significant advances in AI’s ability to recognise obscure patterns, learn new ones and adapt strategies to changing circumstances.
"Yet, just two weeks after AlphaGo’s impressive victory, a new chatbot called Tay, exposed a darker side to AI. Designed to engage in friendly conversation with people online and assist them with Microsoft services, Tay’s unique design feature was that “she” learns from her online interactions. Upon Tay’s public release a coordinated barrage of abuse and incessant trolling by Twitter users, taught Tay the wrong lessons. The programme was corrupted into spewing racist, sexist and xenophobic comments, revealing the potential for flaws in the design and programming of AI, as well as the uneasy interaction between artificial intelligence and the natural kind..."
Twitter Can Help You Trade Fed MeetingsPrint | April 21, 2016
"In the social media cacophony, some of the noise rises to the level of stock market signal.
"That’s the finding of a working paper overseen by Massachusetts Institute of Technology’s Andrew Lo, which says a trading strategy based on views posted on Twitter prior to Federal Reserve policy meetings regularly turned a profit. A one-standard-deviation increase in tweet sentiment can be exploited to boost Fed-day equity returns by 0.62 percent, it found..."
Venture capital boosts endowmentPrint | April 11, 2016
Yale Daily News
Yale Daily News
"With Yale’s endowment at an all-time high of $25.57 billion, the University’s investment success has been buoyed by startups like Uber, Airbnb and LinkedIn...
"Massachusetts Institute of Technology finance professor Andrew Lo ’80 said Yale’s portfolio has had better returns than other venture capitalists. He speculated that this is due to Yale’s extensive network of contacts, which includes alumni and seasoned portfolio managers."
A Robot Wants Your JobPrint | April 10, 2016
Chief Investment Officer
Chief Investment Officer
"The investor of the future may already be incubating in a computer lab. Time to adapt to survive...
"A few years ago, Lo’s team was asked to explore the benefits of machine-learning tools within a commercial bank’s credit card business. The team’s 'recognition algorithms' processed 10 terabytes of data from half a million customers over five years. 'We were able to identify consumers who were likely to default or be delinquent on their credit card payments much more accurately than traditional tools,' Lo says. 'By addressing those particular hotspots in their credit card business, the bank was able to reduce the risk of the overall business but only by affecting 3% of its customers, as opposed to making broad credit reductions for the entire customer base.'"