Machine Learning in Finance Workshop

The workshop is organized by:

Speaker Biographies

Scott Bauguess (Division of Economics and Risk Analysis at the SEC)

Deputy Chief Economist, U.S. Securities and Exchange Commission and Deputy Director of the Division of Economic and Risk Analysis

Dr. Bauguess oversees the Commission’s economic analyses in rulemakings related to corporate disclosure and governance, accounting standards, structured finance, and OTC derivatives. He is also responsible for the Division’s risk assessment programs related to corporate issuers, broker dealers, and asset managers, and oversees the business management of the Agency’s Tips, Complaints, and Referral (TCR) system, which was launched in 2010 to accelerate the detection of market misconduct. Dr. Bauguess joined the SEC in 2007 from Texas Tech University where he was on faculty in the College of Business, and continues to teach graduate courses corporate financial policy at George Washington University.

Dr. Bauguess received his Ph.D. in Finance from Arizona State University in 2004. He also holds a B.S. and M.S. in Electrical Engineering and prior to his doctoral studies spent six years working as an engineer in the high tech industry.

Terrence Hendershott (Haas School of Business, UC Berkeley)

Terrence Hendershott currently holds the Cheryl and Christian Valentine Chair as a professor at the Haas School of Business at the University of California, Berkeley. He completed his Ph.D. at the Graduate School of Business at Stanford University. Terry’s current research interests include information technology’s impact and role in financial markets, the structure and regulation of financial markets, and the interaction between trading and asset price dynamics. His writing has appeared in the Financial Times and The Wall Street Journal and his research has been written about in The New York Times, The Wall Street Journal, and other national newspapers and magazines. His academic work has been published in the Journal of Finance, the Review of Financial Studies, the American Economic Review, the Review of Economic Studies, and other scholarly journals. He edited Elsevier’s Handbook of Economics and Information System. He has received a National Science Foundation CAREER award for his research on electronic trading in financial markets. He was the visiting economist at the New York Stock Exchange in 2006 to 2007. He was a member of the Nasdaq Economic Advisory Board from 2004 to 2007 and Chair in 2007. He has consulted for various financial markets and investment firms.

Shawn Mankad (Robert H. Smith School of Business, University of Maryland)

Shawn Mankad joined the University of Maryland's Smith School of Business as an Assistant Professor in Fall 2013 after obtaining a PhD in Statistics from the University of Michigan. His research aims to use data mining, machine learning, and visualization for economic modeling with unstructured and complex structured data. His work has been featured in journals and media outlets, such as the Wall Street Journal and Chicago Tribune, and he has consulted with the U.S. Commodity Futures Trading Commission and worked at the Federal Reserve Board on characterizing market activity with visual analytic tools.

William Morokoff (Standard and Poors)

William Morokoff is a managing director at Standard & Poor’s and heads the Quantitative Analytics and Research Group. In this role, Bill is responsible for leading the research, development and application of quantitative methodologies, as well as for quantitative support for ratings criteria and credit assessment products and services at Standard & Poor’s. Bill has worked extensively in credit and market risk modeling, with a research focus on numerical analysis for portfolio risk management problems.

Prior to joining S&P, Bill was a senior member of the credit research group at Moody’s KMV, leading the new product research group and ultimately heading the research team. Before that, he worked in quantitative market risk management as a vice president at Goldman Sachs.

Bill holds a Ph.D. in mathematics from the Courant Institute at New York University, where he specialized in Monte Carlo methods and numerical analysis. He also received a B.S. in chemical engineering from Purdue University.

Stefano Pasquali (Enterprise Solutions, Bloomberg)

Stefano Pasquali oversees product development and research for Bloomberg's liquidity and systemic risk solution. His team designs and implements risk models that use Bloomberg's comprehensive market data library and machine-learning techniques to estimate liquidity and risk across different asset classes, with particular focus on OTC markets.

Stefano joined Bloomberg in 2009 as a quantitative analyst in Bloomberg's Valuation Services (BVAL) business, which provides estimated market valuations for thinly traded or OTC securities. In 2010, Stefano became the head of the liquidity research team, which studies the parameters of the fixed income market place and calibrates financial models for measuring risk and market impact. The research is now extended to other asset classes.

Stefano brings more than 20 years of experience examining and implementing innovative approaches to calculating risk and market impact. His approach to risk and liquidity evaluation is strongly influenced by two decades of research and in supporting portfolio managers, chief investment officers in particular leveraging advanced models, big data, data mining, machine learning and database management.

Prior to joining Bloomberg, Stefano held senior positions at several European banks and asset management firms where he oversaw risk management, portfolio risk analysis, model development and risk management committees. Stefano built a risk management process for a global asset management firm with more than $100 billion under management, which involved data acquisition and normalization as well as model development and portfolio management support.

Before his career in financial services, Stefano studied theoretical and computational physics (specifically, Monte Carlo Simulation, solid state physics, environment science, acoustic optimization). Originally from Carrara, Italy, Stefano earned his master degree in theoretical physics from Parma University. He also held research fellowships in computational physics at Parma University and Reading University in the United Kingdom.

Tobias Preis (Warwick Business School)

Dr. Tobias Preis is an Associate Professor of Behavioural Science and Finance at the University of Warwick. Together with his colleague Dr. Suzy Moat, he directs the Data Science Lab at Warwick Business School. His recent research has aimed to analyse and predict real world behaviour with the volumes of data being generated by our interactions with technology, using data from Google, Wikipedia, Flickr and other sources. His research is frequently featured in the news, by outlets including the BBC, the New York Times, the Financial Times, Science, Nature, Time Magazine, New Scientist and the Guardian. He has given a range of public talks including presentations at TEDx events in the UK and in Switzerland. More details can be found on his website http://www.tobiaspreis.de.

Stephen Purpura (Context Relevant)

Stephen Purpura is the founder and CEO of Context Relevant, a predictive analytics software company in Seattle. He is PhD ABD in Information Science at Cornell University, where he performed analyses on terabyte scale data sets and conducted crowd-sourced experiments to enhance Web search systems. He has over 20 years of experience as a data scientist, an academic, a production software developer, and is a leading expert in artificial intelligence, machine learning, political micro-targeting and predictive analytics. Previously, he held various roles at Microsoft, including the Chief Security Officer of MSFDC, one of the first Internet bill payment systems.

Marti Subrahmanyam (Stern School of Business, NYU)

Marti G. Subrahmanyam is the Charles E. Merrill Professor of Finance and Economics in the Stern School of Business at New York University. He holds a degree in mechanical engineering from the Indian Institute of Technology, Madras, and a post-graduate diploma in business administration from the Indian Institute of Management, Ahmedabad. Both institutions conferred on him their Distinguished Alumnus Award. He earned a doctorate in finance and economics from the Massachusetts Institute of Technology. Professor Subrahmanyam has published about one hundred articles in leading academic journals and several books in the areas of corporate finance, capital markets and international finance. He has been a visiting professor at leading academic institutions around the world.

Professor Subrahmanyam currently serves on the editorial boards of many academic journals and was the founding editor of the Review of Derivatives Research. He has won many teaching awards including New York University’s Distinguished Teaching Medal.

He has served as a consultant to several institutions around the world. He also sits on the boards of several companies, in Asia, Europe and North America, and has served as an advisor to international and government organizations.

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