"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..."
"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.'"
"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."
"With the advent of social media, there has been an explosion of interest in how information shared online can be used to profit in the stock market.
"Twitter, the social media monster that allows users to share their thoughts on anything–as long as those thoughts are 140 characters or less–is emerging as a favorite dataset for financial researchers..."
"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..."
"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..."
"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."
"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.'"
"The MIT study looked at English-language tweets in 2007-14 about the Fed, measuring sentiment and adjusting for the reach of the tweeter.
"'We exploit a new dataset of tweets referencing the Federal Reserve and show that the content of tweets can be used to predict future returns, even after controlling for common asset pricing factors,' the authors, Andrew Lo, a professor at MIT, and Pablo Azar, a PhD student there, write."
"Has the investment industry’s marketing push outsmarted itself? For several years, huge effort has gone in to selling “smart beta” funds. It has worked, creating great excitement. Now, not at all surprisingly, the backlash has begun..."