The fourth annual CDAR Symposium, presented in partnership with State Street, will convene on October 19, 2018, from 8:30 am to 6:30 pm at UC Berkeley’s Memorial Stadium. Our conference will feature new developments in data science, highlighting applications to finance and risk management. Confirmed speakers include Jeff Bohn, Olivier Ledoit, Ulrike Malmendier, Steven Kou, Ezra Nahum, Roy Henriksson, Bradley Betts, and Ken Kroner.
The Consortium for Data Analytics in Risk (CDAR) supports research into innovation in data science and its applications to portfolio management and investment risk. Based in the Economics and Statistics Departments at UC Berkeley, CDAR was co-founded with State Street, Stanford, Berkeley Institute for Data Science (BIDS), and Southwestern University of Finance and Economics (SWUFE). This year, CDAR welcomes a new founding member, Swiss Re based in Switzerland, and a new industry partner, AXA Rosenberg. CDAR organizes conferences, workshops, and research programs, bringing together academic researchers from the physical and social sciences, and industry researchers from financial management firms and technology development companies large and small.
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|8:30 – 9:00 a.m.||Registration & Breakfast|
|9:00 – 9:10 a.m.||Welcome
|9:10 – 9:30 a.m.||CDAR Year 4: Growth and Expansion
|9:30 – 10:20 a.m.||“Analytical Nonlinear Shrinkage of Large-Dimensional Covariance Matrices”
Olivier Ledoit, Department of Economics, University of ZurichTalk Abstract: This paper introduces a nonlinear shrinkage estimator of the covariance matrix that does not require recovering the population eigenvalues first. We estimate the sample spectral density and its Hilbert transform directly by smoothing the sample eigenvalues with a variable-bandwidth kernel. Relative to numerically inverting the so-called QuEST function, the main advantages of direct kernel estimation are: (1) it is much easier to comprehend because it is analogous to kernel density estimation; (2) it is only twenty lines of code in Matlab — as opposed to thousands — which makes it more verifiable and customizable; (3) it is 200 times faster without significant loss of accuracy; and (4) it can handle matrices of a dimension larger by a factor of ten. Even for dimension 10,000, the code runs in less than two minutes on a desktop computer; this makes the power of nonlinear shrinkage as accessible to applied statisticians as the one of linear shrinkage.
|10:20 – 10:40 a.m.||Break|
|10:40 – 11:30 a.m.||“The Long-lasting Effects of Experiencing Communism on Financial Risk-Taking”
Ulrike Malmendier, Department of Economics, UC BerkeleyTalk Abstract: We analyze the long-term effects of living under communism and its political propaganda in East Germany (former GDR) for nancial risk-taking. Utilizing comprehensive German brokerage data, we show that, decades after reunification, East Germans still invest significantly less in the stock market. Consistent with communist friends-and-foes propaganda, they are more likely to hold stocks of companies in communist countries (China, Russia, Vietnam), and are particularly unlikely to invest in American companies or the financial industry. Effects are stronger for individuals for whom we expect stronger emotional tagging, for example those living in communist “showcase cities” or cities of Olympic gold medalists. In contrast, East Germans with negative experiences invest more in the stock market today, e. g., those experiencing environmental pollution and suppression of religious beliefs and those without access to (Western) TV entertainment. Election years appear to have trigger effects inducing East Germans to reduce their stock-market investment further. We also provide evidence of negative welfare consequences, as indicated by investment in more expensive actively managed funds, less diversied portfolios, and lower risk-adjusted returns.
|11:30 – 11:50 a.m.||Comments by
Qizhi Tao, Southwestern University of Finance and Economics (SWUFE)
|11:50 – 1:10 p.m.||Lunch|
|1:10 – 2:00 p.m.||“Designing Stable Coins”
Steven Kou, Questrom School of Business, Boston UniversityTalk Abstract: Stable coins, which are cryptocurrencies pegged to other stable financial assets such as U.S. dollar, are desirable for blockchain networks to be used as public accounting ledgers for payment transactions and as crypto money market accounts for asset allocation involving cryptocurrencies, whereby being often called the Holy Grail of cryptocurrency.” However, existing cryptocurrencies are too volatile for these purposes. By using the option pricing theory, we design several dual-class structures that offer either fixed income stable coins (class A coins) pegged to a traditional currency or leveraged investment instruments (class B coins). We show that the class A coin has a volatility comparable to that of the average exchange rate of world currencies against U.S. dollar, and the class A’ coin is essentially pegged to U.S. dollar.
|2:00 – 2:30 p.m.||Break|
|2:30 – 3:20 p.m.||“Evolving machine intelligence and its influence on risk landscapes & analyses“
Jeff Bohn, Head of Swiss Re InstituteTalk Abstract: In a general sense (modifying a famous quote from the biologist, Theodosius Dobzhansky), nothing in a digitizing society makes sense except in light of the evolution of machine intelligence. This broad concept encompasses its most familiar instance, artificial intelligence (AI), and also a range of other algorithms embedded in networked systems such as augmented intelligence, expert systems, and robotic process automation. In this presentation, I will explore themes and trends arising from how evolving machine intelligence(s) impact models and analyses related to risk markets and emerging risk categories.
|3:20 – 6:00 p.m.||Reception (Stadium Club)|
|3:50 – 4:50 p.m.||“The Future of Finance: Wall Street or Silicon Valley?”
Moderator: Ken Kroner, CEO, Pluribus Labs
Ezra Nahum, Partner at Goldman Sachs
Roy Henriksson, CIO, QMA
Bradley Betts, Managing Director, BlackrockAbstract: Will the future of finance look more like Wall Street or Silicon Valley? This panel pulls together a group of industry experts on the future of finance to discuss the impact of fintech, data sciences, and technology on the future of the financial services industry. Will the developments in Silicon Valley have as big an impact as some tout, or will existing processes and players continue to define the industry’s future? This panel will seek to separate the hype from the reality as we look to the future.
|4:50 – 5:00 p.m.||Closing Remarks
Robert Anderson, co-Director, CDAR
Bradley J. Betts, Ph.D., 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 Ph.D. degrees in electrical engineering from Stanford University.
Kenneth F. Kroner is CEO of Pluribus Labs, a new systematic investment manager that utilizes novel data science applications and a unique exposure-driven investment process to create additive and innovative investment solutions for its clients.
Ken is recently retired from BlackRock. As a Senior Managing Director at BlackRock, he was global head of Multi-Asset Strategies and global head of Scientific Active Equities. These teams were responsible for several hundred billion dollars of active investment strategies. Ken also served as a member of BlackRock’s Global Executive Committee and BlackRock’s Global Operating Committee.
Previously, he oversaw Barclays Global Investors (BGI)’s asset allocation (which included global macro, active currencies, and active commodities), fund of hedge funds and client solutions until BGI was acquired by BlackRock in 2009. Prior to joining BGI in 1994, Ken was an associate professor of economics and finance at the University of Arizona.
Dr. Kroner serves or has served on various academic boards, foundation boards and academic journal editorial boards. His research on forecasting volatility and asset returns has been widely published in both academic and practitioner journals. Dr. Kroner earned a BA degree in mathematics and economics from the University of Alberta and a Ph.D. in economics from the University of California at San Diego.
Roy D. Henriksson, Ph.D., is the Chief Investment Officer of QMA. He has over 20 years of experience combining quantitative research with its practical applications in investment portfolios. Prior to joining QMA, Roy was CIO of Advanced Portfolio Management, where he designed and managed customized, risk-targeted investment portfolios for institutional clients globally. Previously, Roy held a variety of senior positions in research, trading and product development at a number of large investment banks. His broad product experience spans equity, fixed income, hedge funds, currencies and commodity derivatives.
Roy has published numerous articles on market-timing skill, portfolio optimization and asset allocation in leading journals. A recipient of the Graham and Dodd Award from The Financial Analysts Journal, he has held the position of Professor of Finance at the University of California-Berkeley, where he also served as Senior Consultant to Wells Fargo Investment Advisors and as an Advisor to the University of California Endowment.
Roy is currently the Co-Chairman of the Liquidity Risk Committee and Member of the Advisory Board of the International Association for Quantitative Finance (the IAQF). He earned a BS in Economics, an MS in Management, and a Ph.D. in Finance from the Massachusetts Institute of Technology.
Steven Kou is a Questrom Professor in Management and Professor of Finance at Boston University. Previously, he taught at National University of Singapore (from 2013 to 2018), Columbia University (from 1998 to 2014), University of Michigan (1996-1998), and Rutgers University (1995-1996). He teaches courses in FinTech and quantitative finance. Currently he is a co-area-editor for Operations Research and a co-editor for Digital Finance, and has served on editorial boards of many journals, such as Management Science, Mathematics of Operations Research, and Mathematical Finance. He won the Erlang Prize from INFORMS in 2002. Some of his research results have been incorporated into standard MBA textbooks and have implemented in commercial software packages and terminals, e.g. in Bloomberg Terminals.
Ulrike Malmendier received her Ph.D. in Business Economics from Harvard University and her Ph.D. in Law (summa cum laude) from the University of Bonn. In 2006 she joined UC Berkeley Economics department after serving at Stanford as Assistant Professor of Finance. She also is a research associate at NBER, and a faculty research fellow at IZA, and CESifo, CEPR research affiliates. In 2013 Malmendier received the Fischer Black Prize from the American Finance Association for the best researcher in finance under 40. In 2016 she was inducted in the American Academy of Arts and Sciences, and she is also a recipient of the 2017 Guggenheim Fellowship. Her area of focus is the Behavioral Economics and Behavioral Finance.
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