Sponsored by the Policy Studies Organization in cooperation with the American Public University
The recent past has seen the complete transformation of financial exchanges from paper to electronics, and from largely human initiated trades to trades initiated by the automated operation of predictive models on variegated market data. It has also seen the integration of trading systems across national and other legal boundaries into a global, non-stop financial trading web. A substantial and growing volume of worldwide trading activity now is determined by Quantitative Finance (“QF”), which incentivizes the modeling of human group behavior to efficiently allocate capital. The distributed computation and communication capabilities of QF have become an integral part of the trading web and constitute a likely field for the emergence of artificial intelligence on a par in many respects with that of humans. This talk will discuss the brief history of electronic trading and Quantitative Finance, discuss the current architectures of the worldwide trading web, and explore the potential role of high-frequency financial trading as a catalyst for the emergence of computational intelligence that not only is faster than human minds but also, physically, orders of magnitude larger (i.e., spanning the entire planet).
Dr. Alexander D. Wissner-Gross is a Research Affiliate at the MIT Media Laboratory. He has received 102 major distinctions, authored 14 publications, is an inventor in 9 issued, pending, and provisional patents and patent applications and founded, managed, and advised 5 technology companies. In 1998, he won the U.S.A. Computer Olympiad and represented the U.S. at the International Olympiad in Informatics. In 2003, he became the last person in MIT history to receive a triple major, with bachelors in Physics, Electrical Science and Engineering, and Mathematics, while graduating first in his class from the MIT School of Engineering. In 2007, he completed his Ph.D. in Physics at Harvard University, where his research on smart matter, pervasive computing, and machine learning was awarded the Hertz Doctoral Thesis Prize. Following his Ph.D. he was named a Ziff Fellow in Computer Science at Harvard University. His work has been featured in Technology Review, Business Week, Scientific American, The New York Times, and The Wall Street Journal. Further information is available at www.alexwg.org.
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