2017 Symposium

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Our conference series explores innovation in data science, highlighting applications to risk management. This year’s topics are Impact Investing and Fintech, and confirmed speakers include Kay Giesecke, Adair Morse, Alex Papanicolaou, Alex Shkolnik, Philip Stark, and Kewei Tang.

The third annual CDAR Symposium, presented in partnership with State Street, will convene on October 27, 2017 from 8:45am to 5:30pm at UC Berkeley’s Memorial Stadium.

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, and the Berkeley Institute for Data Science (BIDS). This year, CDAR welcomes a new founding member, the Southwestern University of Finance and Economics (SWUFE) based in Chengdu, China! 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.

Please send inquiries to soum@berkeley.edu.

Agenda

The 2017 Symposium will take place on Friday, October 27th, 2017 from 8:30am to 6:30pm. *Subject to change

8:30 – 9:00 a.m. Registration & Breakfast
9:00 – 9:10 a.m. Welcome
9:10 – 9:40 a.m. CDAR Year 3: Growth and Expansion

    Lisa Goldberg, co-Director, CDAR
    Jingmei Zhao, Dean, School of Finance, SWUFE
9:40 – 10:30 a.m. “Impact Investing”
Adair Morse, Haas School of Business, UC Berkeley
Talk abstract: Impact funds, defined as venture or growth equity funds with dual objectives of generating financial returns and positive externalities, perform 7.8% below traditional VC funds in univariate statistics, or 3-4% lower returns in a willingness-to-pay (WTP) utility framework adjusting for investor choice covariates. These results need to be cast in the broader spectrum of understanding the landscape of opportunities and incentives for responsible investing. Development organizations, banks, and public pension funds have the greatest WTP, while endowments and private pensions have negative WTP. Mapping WTP to investor tastes and hindrances which could affect utility for impact, we find that Europeans, mission-oriented investors, and investors facing political pressure (often for local investing) have greater WTP for impact while legal restrictions (e.g. ERISA) lower investor WTP for impact.
10:30 – 10:50 a.m. Break
10:50 – 11:40 a.m. “Web Media and Stock Markets : A Survey and Future Directions from a Big Data Perspective”
Qing Li, School of Economic Information Engineering, SWUFE
Talk abstract: Stock market volatility is influenced by information release, and public acceptance. With the increasing volume and speed of social media, the effects of Web information on stock markets are becoming increasingly salient. However, studies of the effects of Web media on stock markets lack both depth and breadth due to the challenges in automatically acquiring and analyzing massive amounts of relevant information. In this study, we systematically reviewed 229 research articles on quantifying the interplay between Web media and stock markets from the fields of Finance, Management Information Systems and Computer Science. In particular, we first categorized the representative works in terms of media type and then summarized the core techniques for converting textual information into machine-friendly forms. Finally, we compared the analysis models used to capture the hidden relationships between Web media and stock movements. Our goal is to clarify current cutting-edge research and its possible future directions to fully understand the mechanisms of Web information percolation and its impact on stock markets from the perspectives of investors’ cognitive behaviors, corporate governance, and stock market regulation.
11:40 – 12:30 p.m. The Dispersion Bias: Correcting a Large Source of Error in Minimum Variance Portfolios

    Alex Shkolnik, Postdoc, CDAR
    Alex Papanicolaou, Postdoc, CDAR

Abstract: Estimation error has plagued quantitative finance since Markowitz launched modern portfolio theory in 1952. Using random matrix theory, we characterize a source of bias in the sample eigenvectors of financial covariance matrices. Unchecked, the bias distorts weights of minimum variance portfolios and leads to risk forecasts that are severely biased downward. To address these issues, we develop an eigenvector bias correction. Our approach is distinct from the regularization and eigenvalue shrinkage methods found in the literature. We provide theoretical guarantees on the improvement our correction provides as well as estimation methods for computing the optimal correction from data.

12:30 – 1:50 p.m. Lunch
1:50 – 2:40 p.m. “Don’t Bet on Your Random Number Generator”
Philip Stark, Department of Statistics, UC Berkeley
Talk abstract: Pseudo-random numbers are used in countless contexts, including jury selection, electronic casino games, physical and chemical simulations, bank stress tests, portfolio risk simulation, numerical integration, random sampling, Monte Carlo methods, stochastic optimization, and cryptography. They are used in scientific fields from finance to particle physics to sociology. It’s tempting to think that the pseudo-random number generators (PRNGs) in common software packages and general-purpose programming languages in are “good enough” for most purposes. However, pigeonhole arguments and empirical results show that those PRNGs are not adequate even for basic statistical purposes such as random sampling, generating random permutations, and the bootstrap – even for relatively small data sets. Cryptographers have developed cryptographically secure pseudo-random number generators (CS-PRNGs), which provide a far better approximation to truly random numbers, as manufacturers of gambling machines are well aware. For most purposes, the incremental computational cost of using a CS-PRNG is negligible. Statistical packages and general-purpose programming languages should use CS-PRNGs by default.
2:40 – 3:30 p.m. Fintech Speaker: “Internet Techniques and Big Data in China’s Financial Industry: Practices in Ant Financial”
Kewei Tang, CEO, Fulin Tech
Talk abstract: In China, internet techniques continue to improve efficiency, increase capability and expand boundaries for China’s financial industry, including banking, wealth management, mobile payments and insurance. Ant Financial, as the world-leading Fintech Giant, has built several strong internet-only business arms that are largely data-driven financial services. In its first decade, with only 7000 employees, it serves 500M customers domestically and 1.2B globally. This presentation shows how internet techniques and big data are helping to reshape China’s financial industry, with Ant Financial as a good example.
3:30 – 6:00 p.m. Reception
4:00 – 4:50 p.m. Financial Technology Panel
Moderator: Kay Giesecke, Professor, Stanford University
Panelists:
John Arabadjis, Head of GX Labs, State Street
Jeffrey Bohn, Head of the Swiss Re Institute
Warren Pennington, Principal, Vanguard
Robert Sears, Executive Vice President, BBVA

This panel will discuss recent developments in the area of financial technologies. Topics include data and AI, online and mobile payments, blockchain, cryptocurrencies, and roboadvisory.

4:50 – 5:00 p.m. Closing Remarks

Robert Anderson, co-Director, CDAR

 

Featured Speakers

Adair Morse, Haas School of Business, UC Berkeley

Adair Morse is Associate Professor at the Haas School of Business at the University of California at Berkeley, where she teaches New Venture Finance. She is on the Expert Panel (for oversight of the Oil Fund) to the Ministry of Finance of Norway, the board of the Haas Impact Investing Network, the faculty advisor to Haas FinTech Club, faculty mentor to Gender Equity Initiative, and faculty co-director of the Haas Impact Research Prize. She holds a Ph.D. in finance from the University of Michigan. Adair’s research spans three areas of finance: household finance, corruption, and asset management, with the unifying theme that she tries to choose topics useful for leveling economic playing fields. She has won a number of top finance research prizes, and her various works have been directly implemented into policy via U.S. Congress Acts, U.S. and Canadian state banking regulations, and Greek Parliament tax reform. Adair’s work on asset management includes work on factor investing of delegated asset managers, objectives of sovereign wealth funds, and impact investing. Her recent work studies many aspects of fintech on the lending and equity investing sides, and she has been invited to give a number of keynote addresses on the future of FinTech for consumers and investors.

“Impact Investing”
Talk abstract: Impact funds, defined as venture or growth equity funds with dual objectives of generating financial returns and positive externalities, perform 7.8% below traditional VC funds in univariate statistics, or 3-4% lower returns in a willingness-to-pay (WTP) utility framework adjusting for investor choice covariates. These results need to be cast in the broader spectrum of understanding the landscape of opportunities and incentives for responsible investing. Development organizations, banks, and public pension funds have the greatest WTP, while endowments and private pensions have negative WTP. Mapping WTP to investor tastes and hindrances which could affect utility for impact, we find that Europeans, mission-oriented investors, and investors facing political pressure (often for local investing) have greater WTP for impact while legal restrictions (e.g. ERISA) lower investor WTP for impact.

Qing Li, School of Economic Information Engineering, SWUFE

Qing Li, associate dean of Information School at Southwestern University of Finance and Economics (SWUFE). He is a professor at SWUFE and an adjunct professor at University of Arizona. Prior to that, he worked at the Eller business school at university of Arizona, computer department of Arizona state university, and information school at Korea Advanced Institute of Science and Technology (KAIST). Li’s research interests lie primarily in financial intelligence which studies the advanced intelligent information processing techniques to solve the challenges in finance. He served on the editorial board of Electronic Commerce Research and Applications, Journal of Database Management, and Journal of Global Information Management, and the program committees or co-chairs of various international conferences including PACIS, SIGIR, CIKM, ACL. He is also the co-founder of HealthDirect – one-hour fresh food delivery e-platform (www.kuaijiankang.com).

“Web Media and Stock Markets : A Survey and Future Directions from a Big Data Perspective”
Talk abstract: Stock market volatility is influenced by information release, and public acceptance. With the increasing volume and speed of social media, the effects of Web information on stock markets are becoming increasingly salient. However, studies of the effects of Web media on stock markets lack both depth and breadth due to the challenges in automatically acquiring and analyzing massive amounts of relevant information. In this study, we systematically reviewed 229 research articles on quantifying the interplay between Web media and stock markets from the fields of Finance, Management Information Systems and Computer Science. In particular, we first categorized the representative works in terms of media type and then summarized the core techniques for converting textual information into machine-friendly forms. Finally, we compared the analysis models used to capture the hidden relationships between Web media and stock movements. Our goal is to clarify current cutting-edge research and its possible future directions to fully understand the mechanisms of Web information percolation and its impact on stock markets from the perspectives of investors’ cognitive behaviors, corporate governance, and stock market regulation.

Philip Stark, Department of Statistics, UC Berkeley
Philip Stark’s research centers on inference (inverse) problems, especially confidence procedures tailored for specific goals. Applications include the Big Bang, causal inference, the U.S. census, climate modeling, earthquake prediction and seismic hazard analysis, election auditing, endangered species stressors, evaluating and improving teaching and educational technology, food web models, health effects of sodium, the geomagnetic field, geriatric hearing loss, information retrieval, Internet content filters, nonparametrics (constrained confidence sets for functions and probability densities), risk assessment, the seismic structure of Sun and Earth, spectroscopy, spectrum estimation, and uncertainty quantification for computational models of complex systems. He developed methods for auditing elections that have been incorporated into laws in California and Colorado. Methods he developed or co-developed for data reduction and spectrum estimation are part of the Øersted geomagnetic satellite data pipeline and the Global Oscillations Network Group (GONG) helioseismic telescope network data pipeline. Read his full bio »

“Don’t Bet on Your Random Number Generator”
Talk abstract: Pseudo-random numbers are used in countless contexts, including jury selection, electronic casino games, physical and chemical simulations, bank stress tests, portfolio risk simulation, numerical integration, random sampling, Monte Carlo methods, stochastic optimization, and cryptography. They are used in scientific fields from finance to particle physics to sociology. It’s tempting to think that the pseudo-random number generators (PRNGs) in common software packages and general-purpose programming languages in are “good enough” for most purposes. However, pigeonhole arguments and empirical results show that those PRNGs are not adequate even for basic statistical purposes such as random sampling, generating random permutations, and the bootstrap – even for relatively small data sets. Cryptographers have developed cryptographically secure pseudo-random number generators (CS-PRNGs), which provide a far better approximation to truly random numbers, as manufacturers of gambling machines are well aware. For most purposes, the incremental computational cost of using a CS-PRNG is negligible. Statistical packages and general-purpose programming languages should use CS-PRNGs by default.

 

Kewei Tang, CEO, Fulin Tech

Prior to his current position, Kewei served as Managing Director of platform risk management at Mybank, Ant Financial. His major responsibilities included applying cutting edge machine learning techniques to an online lending portfolio serving subprime customer or customers with no credit history. He is also an adjunct professor at Southwestern University of Finance and Economics in Chengdu, China. He has served as an adviser to several Chinese government committees and as a Director of the Sino-European Finance Association, London. His work has been published in several top domain journals and he presents frequently in China’s top risk management forums.

Kewei obtained his PhD from Nottingham University, England, focusing on applying artificial intelligence techniques to financial risk management. He has also worked as a quant risk executive at RBS and Barclays. During that period he played a leading roles in a few large risk management activities, organized by IMF and ECB, involving top banks.

“Internet Techniques and Big Data in China’s Financial Industry: Practices in Ant Financial”
Talk abstract: In China, internet techniques continue to improve efficiency, increase capability and expand boundaries for China’s financial industry, including banking, wealth management, mobile payments and insurance. Ant Financial, as the world-leading Fintech Giant, has built several strong internet-only business arms that are largely data-driven financial services. In its first decade, with only 7000 employees, it serves 500M customers domestically and 1.2B globally. This presentation shows how internet techniques and big data are helping to reshape China’s financial industry, with Ant Financial as a good example.

Kay Giesecke, Management Science and Engineering, Stanford

Kay Giesecke is Associate Professor of Management Science & Engineering at Stanford University and the Paul Pigott Faculty Scholar in the School of Engineering. He is the Director of the Advanced Financial Technologies Laboratory and the Quantitative Finance Certificate Program. He is the Co-Chair of the Mathematical and Computational Finance Program. Kay is a member of the Institute for Computational and Mathematical Engineering. He serves on the Governing Board and Scientific Advisory Board of the Consortium for Data Analytics in Risk.

John Arabadjis, Head of GX Labs, State Street

John is a managing director and Head of GX Labs, State Street Corporation’s center for R&D in risk management and data science in San Francisco, where he manages the group’s research program in multi-asset portfolio risk and sustainable investing. Before joining GX Labs he led the behavioral research group at State Street Associates in Cambridge, Massachusetts, developing models of market participant behavior and applying these to quantitative asset management. Prior to joining State Street in 2005 John was an astrophysicist at MIT, and he has also held research and teaching positions at Emmanuel College, the University of Michigan and the University of Massachusetts. He has taught courses in physics, astrophysics, applied mathematics, environmental impact of energy production and climate change, and has authored/coauthored roughly 40 articles in peer-reviewed journals and conference proceedings, including the Journal of Portfolio Management, the Astrophysical Journal, Advances in Space Research, Nuclear Physics B and the Astronomical Journal. His research has been profiled in media outlets including the New York Times, Science, and Discover. John has a PhD in astrophysics from the University of Michigan.

Jeffrey Bohn,
Head of the Swiss Re Institute
Dr. Bohn is the Head of the Swiss Re Institute. Most recently, he served as Chief Science Officer and Head of GX Labs at State Street Global Exchange in San Francisco. Before moving back to California, he established the Portfolio Analytics and Valuation Department within State Street Global Markets Japan in Tokyo. (He is fluent in Japanese.) He previously ran the Risk and Regulatory Financial Services consulting practice at PWC Japan.

Warren Pennington, Principal, Vanguard

Warren Pennington is a principal and global head of Vanguard’s Office of Investment Management Fintech Strategies. The Office of IMFS mission is to actively explore new technologies in ways that could dramatically improve Vanguard’s investment performance, make global capital markets work better for investors, and serve as a catalyst for innovation within the Investment Management Group at Vanguard. IMG manages over $3.6 Trillion of assets globally, across both passive and active strategies in the fixed income, equities, currencies, and derivatives markets. Before joining Vanguard in 2012, Mr. Pennington worked for the Macquarie Group in various senior leadership roles in their Investment Management division. Prior to working for Macquarie, Warren was division controller and ran operations in the consumer lending and corporate trust businesses at Wells Fargo Bank. He earned his B.S. Aerospace Engineering and M.S. Telecommunications degrees from the University of Colorado, Boulder. He is California CPA, and serves on the SIFMA Operations and Technology Steering Committee as well as the Advisory Board of the Ben Franklin Fintech Accelerator program out of Philadelphia.

Robert Sears, Executive Vice President, BBVA

Robert Sears is an experienced high tech executive, entrepreneur and innovator. Since 2008, he has focused on financial services, founding and running a unique consumer payment card company, Red Giant. There, he pioneered services giving consumers direct real time control over their own payment cards, making it safe for parents to give cards to their children and providing entire families with intuitive mobile tools to manage their daily spending.

Prior to Red Giant, Robert was Chief Architect of Multimedia Experiences at Nokia, where he spearheaded the design and creation of mobile services supporting consumers using Nokia handsets. He introduced Design Thinking into Nokia’s product creation approach, drove the development of advanced mobile software architectures and pioneered the creation of global mobile service infrastructures.

Robert is an experienced director and advisor currently working with the d.school and the AFTLab at Stanford University, the World Economic Forum Center for the Fourth Industrial Revolution and a number of startups in Silicon Valley.

He holds a Ph.D. in Physics from the University of Michigan and lives in Palo Alto, California with his wife and daughter, the family dog and two horses.

Directions

The recommended parking lot is the Maxwell Field Stadium Lot.

For assistance with parking, please email Sang Oum.

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