Consortium for Data Analytics in Risk

Welcome

John Arabadjis, State Street

CDAR Year 4: Growth and Expansion

Lisa Goldberg, co-Director, CDAR

"Analytical Nonlinear Shrinkage of Large-Dimensional Covariance Matrices"
Olivier Ledoit, Department of Economics, University of Zurich

Talk 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.

"The Long-lasting Effects of Experiencing Communism on Financial Risk-Taking" 
Ulrike Malmendier, Department of Economics, UC Berkeley

Talk Abstract: We analyze the long-term effects of living under communism and its political propaganda in East Germany (former GDR) for financial 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 diversified portfolios, and lower risk-adjusted returns.

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Qizhi Tao, Southwestern University of Finance and Economics (SWUFE)

“Designing Stable Coins”
Steven Kou, Questrom School of Business, Boston University

Talk 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.

“Evolving machine intelligence and its influence on risk landscapes & analyses)”
Jeff Bohn, Head of Swiss Re Institute

Talk 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.

"The Future of Finance: Wall Street or Silicon Valley?"
Moderator: Ken Kroner, CEO, Pluribus Labs
Panelists:
Ezra Nahum, Partner at Goldman Sachs
Roy Henriksson, CIO, QMA
Bradley Betts, Managing Director, Blackrock

Abstract: 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.

Closing Remarks

Robert Anderson, co-Director, CDAR