The Rise of Machine Learning in Asset Management
Friday, Oct 5 2018 at 8:00 am - 6:00 pm EDT
165 Whitney Avenue
New Haven, CT 06511
About the Event
The goal of this conference is to bring together professional asset managers and academics to understand and discuss the role of artificial intelligence, machine learning, and data science in the finance industry. We will explore the new challenges and concomitant opportunities of new data and new methods for investments and delegated asset management. Speakers will include quantitative managers working at the cutting edge intersection of machine learning and portfolio choice, as well as academic researchers working on their intellectual frontier.
Bryan KellyYale University & AQR Capital Management, LLC.
Bryan Kelly is Professor of Finance at the Yale School of Management, a Research Fellow at the National Bureau of Economic Research, Associate Director of SOM’s International Center for Finance, and a consultant for AQR Capital Management, LLC. Professor Kelly’s primary research fields are asset pricing and financial econometrics. He is interested in issues related to volatility, tail, and correlation risk in financial markets, predictive methods in high dimensional systems, banking sector systemic risk, financial intermediation, and financial networks. His papers in these areas have been published in the American Economic Review, the Quarterly Journal of Economics, the Journal of Finance, the Journal of Financial Economics, and the Review of Financial Studies, among others. He is an associate editor at the Journal of Finance and the Journal of Business and Economic Statistics. Before joining Yale, Kelly was a professor of finance at the University of Chicago Booth School of Business. He earned a bachelor’s degree in economics from the University of Chicago, a master’s degree in economics from University of California San Diego, and a PhD in finance from the New York University’s Stern School of Business. Kelly worked in investment banking at Morgan Stanley prior to pursuing his PhD.
Igor Tulchinsky is Founder, Chairman and CEO of WorldQuant, a global quantitative asset management firm with over $7 billion in assets under management, more than 25 offices in 15 countries and over 700 employees and 1,000 consultants. Prior to founding WorldQuant in 2007, Igor spent 12 years as a statistical arbitrage portfolio manager at Millennium Management. Igor is the Founder of WorldQuant University, a not-for-profit that offers both an online master’s degree in financial engineering and a data science module tuition-free. He also founded WorldQuant Ventures, an early stage investment firm focused on disruptive companies in technology. Igor previously worked as a venture capitalist, scientist at AT&T Bell Laboratories, video game programmer and author. Igor holds an M.A. in computer science from the University of Texas, completed in a record nine months, and an M.B.A. in finance and entrepreneurship from the Wharton School.
Afsheen AfsharCerberus (former)
Afsheen Afshar is a senior business executive and deep AI expert who has led large-scale technological transformation across a variety of industries and enterprises, generating hundreds of millions in value. He regularly advises start-ups, universities, investors, enterprises, and others across the globe on how to best leverage modern technology. Most recently, he was the Chief Artificial Intelligence Officer and a Senior Managing Director at Cerberus, where his role was to start and lead the development of a proprietary data and advanced analytics platform, the goal of which was to empower Cerberus‘s portfolio companies and trading desks across the asset management and operate companies with actionable insights that extract measurable value out of raw data. During his tenure, he was seconded to Albertsons Companies as an Executive Vice President and the interim Chief Data and Analytics Officer, where he led the standing up a modern analytics and data function, inclusive of its strategy, organization, and infrastructure. Applications ranged from personalized product recommendation systems to store labor optimization. Prior to joining Cerberus, Afsheen was the Chief Data Science Officer and a Managing Director of JPMorgan Chase’s Corporate and Investment Bank (>$40B in revenue), responsible for data science efforts across every business and supporting function of that part of the firm. Prior to that, he was a Managing Director at Goldman Sachs, where he led the data science, engineering, and machine learning teams that worked across multiple businesses. His teams have created products ranging from improved management of operations risk to assisting investment bankers on prioritizing deal flow. Afsheen holds dual-doctorate degrees (MD and PhD) from Stanford University. His PhD is in Electrical Engineering with a focus on AI/machine learning and neuroscience (advisor: Krishna Shenoy; co-advisor: Andrew Ng). He also holds a Masters in Electrical Engineering from Stanford, and a Bachelors in Electrical Engineering from Princeton University.
Bradley J. BettsBlackRock
Bradley J. Betts, PhD, Managing Director, is a member of the Global Equity Research team within BlackRock's Systematic Active Equity group. He focuses on the use of machine learning, artificial intelligence, and natural language processing for generating alpha. Dr. Betts' service with the firm dates back to 2008. Prior to joining, Dr. Betts was a Scientist at Quantcast where he developed statistical models using large data sets for behavioral targeting of online advertising. Prior to that, he was a Principal Computer Scientist at NASA's Ames Research Center, a Lecturer and Research Scientist in the School of Medicine at Stanford University, and a Member of the Technical Staff at the MITRE Corporation. Dr. Betts is a member of the ACM, IEEE, AMS, and AAAS. He earned a BASc degree in computer engineering from the University of Waterloo and MS and PhD degrees in electrical engineering from Stanford University.
Jason is COO at Diffeo, an AI startup based in Cambridge building collaborative teammate technology for defense and financial services customers. Jason is leading Diffeo's expansion into financial services. Most recently he led Diffeo’s participation in the Fintech Innovation Lab, where he has been working with top tier financial firms to solve their disparate data challenges. At Diffeo, Jason has also brought together a wide range of partnerships. For example, he led Diffeo in the Salesforce Incubator’s AI Cohort of 2017, where Diffeo was featured in Quip’s keynote presentation at Dreamforce. While studying computer science and military history at Williams College, Jason co-founded Meta Search in 2014 after watching his mom try, and fail, to find files on her computer. Meta launched to thousands of beta users before being acquired by Diffeo in 2016.
Charles ElkanGoldman Sachs
Charles Elkan is a managing director and the global head of machine learning at Goldman Sachs, and also an adjunct professor of computer science at the University of California, San Diego (UCSD). Earlier, he was the first Amazon Fellow, leading a team of over 30 scientists doing research and development in applied machine learning in both e-commerce and cloud computing, with wins totaling over $100M incremental earnings. Before joining Amazon, Dr. Elkan was a tenured professor of computer science at UCSD. His Ph.D. is from Cornell and he was an undergraduate at Cambridge. His students at UCSD have gone on to faculty positions at universities including Columbia, CMU, the University of Washington, and Stanford, and to many leading companies.
Ronald N. KahnBlackRock
Ronald Kahn, Managing Director, is Global Head of Systematic Active Equity Research at BlackRock. His service with the firm dates back to 1998, including his years with Barclays Global Investors (BGI). Prior to joining BGI, he worked as Director of Research at Barra. Ronald Kahn is a well-known expert on quantitative investing. He has published numerous articles on investment management, and, with Richard Grinold, authored Active Portfolio Management. The two of them are the 2013 winners of James R. Vertin award. He is a 2007 winner of the Bernstein Fabozzi/Jacobs Levy award for best article in the Journal of Portfolio Management. He serves on the editorial advisory boards of the Financial Analysts Journal, the Journal of Portfolio Management and the Journal of Investment Consulting. He teaches in UC Berkeley's Master of Financial Engineering Program. He earned an AB degree in physics from Princeton and a PhD in physics from Harvard.
Shaheen is the CEO of firstAI, an AI startup that helps collaboration and information creation in fixed income asset classes like leveraged finance and CMBS. firstAI has its own proprietary machine learning algorithms trained on the domains we specialize in. The company works with leading financial institutions and is an alum of Barclays Techstars and the FinTech Innovation Lab. firstAI was conceptualized during the endless hours and long nights of running comps and reading deal documents during the financial crisis, when the minutiae inside the long contracts made the difference between losing a lot of money or not.
Yves-Laurent Kom SamoPit.AI Technologies
Dr. Yves-Laurent Kom Samo is the Founder and CEO of Pit.AI Technologies, a Silicon Valley tech startup that aims to Solve Intelligence for Investment Management. Pit.AI Technologies is backed by Y Combinator, Refactor Capital, Vy Capital, Renaissance Technologies and First Round Capital co-founder Howard Morgan, and hedge fund manager Jaffray Woodriff, to name but a few. Prior to founding Pit.AI Technologies, Dr. Kom Samo completed a PhD in Machine Learning at the University of Oxford, where he was a full scholar of the Oxford-Man Institute of Quantitative Finance. His PhD research was awarded the prestigious Google PhD Fellowship in Machine Learning in 2016. Prior to his PhD, Dr. Kom Samo worked as a Quant Trader at Goldman Sachs and J.P. Morgan. Dr. Kom Samo was trained as an applied mathematician at Telecom ParisTech in France, before earning a second Master degree in Mathematical Finance from the University of Oxford. He leads the Pit.AI Research Paper Series, which advocates a finance-first approach to machine learning research, and he occasionally writes shorter opinion pieces on the state of AI in finance on medium (https://medium.com/@Dr_YLKS).
Marcos López de PradoAQR Capital Management, LLC. & Cornell University
Marcos López de Prado is a Principal and Head of Machine Learning at AQR Capital Management. Before AQR, he founded and led Guggenheim Partners’ Quantitative Investment Strategies (QIS) business, where he developed high-capacity machine learning strategies, receiving up to $13 billion in assets. Concurrently with the management of investments, between 2011 and 2018 Marcos was also a research fellow at Lawrence Berkeley National Laboratory (U.S. Department of Energy, Office of Science). He has published dozens of scientific articles on machine learning and supercomputing in the leading academic journals, and he holds multiple international patent applications on algorithmic trading. SSRN ranks him as one of the most-read authors in Economics. Among several monographs, he is the author of the graduate textbook "Advances in Financial Machine Learning" (Wiley, 2018). Marcos earned a PhD in Financial Economics (2003), a second PhD in Mathematical Finance (2011) from Universidad Complutense de Madrid, and is a recipient of Spain's National Award for Academic Excellence (1999). He completed his post-doctoral research at Harvard University and Cornell University, where he teaches a financial machine learning course at the School of Engineering. Marcos has an Erdős #2 and an Einstein #4 according to the American Mathematical Society.
Marina NiessnerAQR Capital Management, LLC.
Marina Niessner, PhD, is a Vice President on the alternative risk premia team within AQR’s Global Alternative Premia department. In this role, she is responsible for research on asset risk premia, factor research, and part of AQR’s research into statistical models. Prior to joining AQR in August, 2018, she was an Assistant Professor of Finance at the Yale School of Management. Her main research interests are behavioral finance, financial social networks, and social media. In her recent work, she applies methods from linguistic psychology to identify fake news on social media, and to examine their impact on financial markets. In her other work, she studies the market for initial coin offerings, and she also uses opinions from a social network of investors, to develop a new measure of investor disagreement and examine the extent to which different investment philosophies lead to more volatility in the stock market. Her research has been featured in the Financial Times and the Wall Street Journal. She holds a BA in Economics and Statistics and a Ph.D. in Economics from the University of Chicago.
Frida Polli is a Harvard and MIT trained award-winning neuroscientist turned entrepreneur. She is the CEO and co-founder of pymetrics, a company using neuroscience and AI to improve the accuracy, fairness and diversity of hiring. With global clients including Unilever, Accenture and LinkedIn, pymetrics has matched hundreds of thousands of people with their ideal jobs, while removing bias from the hiring process.
Nathan StevensonForwardLane Inc
Nathan Stevenson is CEO and founder of Forwardlane, an entrepreneur with a background in quantitative finance, computer science and machine learning. His expertise combines financial services and technology and spans a number of areas, including digital innovation and transformation in wealth management, asset management, insurance and commercial banking. He was in quantitative research at CQS, a top 5 global hedge fund group, in fixed income credit at BNP Paribas and served as an enterprise architect at the JSE, a $980bn exchange, architecting and deploying transformative trading technologies with NYSE-Euronext, LSE and CME Groups. As an entrepreneur, he has co-founded three startups, in travel technology and entertainment with leading industry executives. He has been featured as speaker and industry expert on the application of AI in financial services for Forbes, Institutional Investor, Euromoney, World Economic Forum, Thomson Reuters, Wealth Management.com and more.
Friday, October 5, 2018 | Yale School of Management, Zhang Auditorium
*Speakers and times may change
Registration and Breakfast
Bryan Kelly, Yale University & AQR Capital Management, LLC.
Ten Financial Applications of Machine Learning
Marcos López de Prado, AQR Capital Management, LLC. & Cornell University
AI in Finance: Present and Future, Hype and Reality
Charles Elkan, Goldman Sachs
The Role of Machine Learning and Artificial Intelligence in Entrepreneurship
Moderator: Marina Niessner, AQR Capital Management, LLC.
Jason Briggs, Diffeo
Shaheen Kanda, firstAI
Frida Polli, pymetrics
Nathan Stevenson, ForwardLane Inc
Big Data, Smart Beta, and the Future of Investing
Bradley J. Betts & Ronald N. Kahn, BlackRock
Current State and Open Challenges for Applying Data Science and AI
Afsheen Afshar, Cerberus (former)
Measuring Diversification in The Machine Learning Age
Yves-Laurent Kom Samo, Pit.AI Technologies
Firseside Chat: Rise of an Algorithm-ocracy
Keynote Speaker: Igor Tulchinsky, WorldQuant LLC
Moderator: Bryan Kelly, Yale University & AQR Capital Management, LLC.
Bryan Kelly, Yale University & AQR Capital Management, LLC.
Questions? Contact: email@example.com