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This seminar is co-organised by Centre for Quantitative Finance (CQF) and Risk Management Institute (RMI). |
| Date: 9 Sep 2022 (Friday) |
| Time: 0900hr – 1000hr (Singapore Time Zone, GMT +8) Online via Zoom |
Programme
| 0900hr – 1000hr |
Title: The Adoption of Blockchain-Based Decentralized Exchanges Associate Professor Agostino Capponi (Columbia University) Abstract: Decentralized finance (DeFi) is a competitive marketplace of decentralized financial applications that operate through smart contracts, which currently manages over $57 billion USD. We investigate the market microstructure of Automated Market Makers (AMMs), the most prominent type of pricing functions implemented by DeFi exchanges, and highlight the fundamental differences with centralized limit order books. Through a dynamic game theoretical model we demonstrate that, in equilibrium, arbitrageurs extract gains from liquidity providers for a broad class of convex, twice differentiable, and positively homogeneous pricing functions. We show that pricing curves with higher convexity result in higher price impact, which reduces arbitrage and liquidity freezes, but also decreases trading volume. We provide statistical support for our model implications using transaction-level data of Uniswap and SushiSwap AMMs (joint work with R. Jia). |
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A Short Biography of Speaker
Agostino Capponi is an Associate Professor in the IEOR Department at Columbia University. His research interests are in financial technology, market microstructure, systemic risk, and economic networks. Agostino’s research has been funded by major agencies such as NSF, DARPA, DOE, IBM, GRI, Ripple, and Ethereum. His research has been recognized with the 2018 NSF CAREER award, and a JP Morgan AI Research Faculty award. Agostino is a fellow of the crypto and blockchain economics research forum, and an academic fellow of Alibaba’s Luohan academy. He serves as an editor of Management Science in the Finance Department, co-editor of Mathematics and Financial Economics, and area editor of Operations Research Letters. He also serves as an associate editor of major journals in his field, such as the SIAM Journal on Financial Mathematics, Finance and Stochastics, Stochastic Systems, and Operations Research. Agostino is the former Chair of the SIAG/FME Activity Group and of the INFORMS Finance Section, and the founding director of the Columbia Center for Digital Finance and Technology.
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This seminar is co-organised by Centre for Quantitative Finance (CQF), Risk Management Institute (RMI) and NUS Chongqing Research Institute, NUS.
Join our Session @National University of Singapore |
| Date: 12 Aug 2022 (Friday) |
| Time: 1500hr – 1600hr (Singapore Time Zone, GMT +8) |
Programme
| 1500hr – 1600hr |
Title: Markov Devision Processes under Model Uncertainty Prof. Julian Sester (National University of Singapore)
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For in person attendance:
Venue: NUS S17-04-06
A Short Biography of Speaker
Julian Sester is a Peng Tsu Ann Assistant Professor at the National University of Singapore.
He received his Ph.D. in mathematics in December 2019 under the supervision of Eva Lütkebohmert at the University of Freiburg.
Prior to joining NUS he was a postdoctoral researcher at the Nanyang Technological University, Singapore in the research group of Ariel Neufeld. His research focuses on robust finance, credit risk, and machine learning applications in Finance.
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This seminar is co-organised by Centre for Quantitative Finance (CQF), Risk Management Institute (RMI) and NUS Chongqing Research Institute, NUS.
Join our Webinar Session @National University of Singapore |
| Date: 9 Jun 2022 (Thursday) |
| Time: 1400hr – 1500hr (Singapore Time Zone, GMT +8) |
Programme
| 1400hr – 1300hr |
Title: Coexisting Exchange Platforms: Limit Order Books and Automated Market Makers Prof. Jun AOYAGI (Hong Kong University of Science and Technology)
Co-author: Yuki Ito, University of California, Berkeley |
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A Short Biography of Speaker
Jun AOYAGI is Assistant Professor of Finance at Hong Kong University of Science and Technology and a project scholar at the University of Tokyo, Digital Economy. He received his Ph.D. in Economics from the University of California, Berkeley. His research interest includes Finance, Market Microstructure, FinTech, Information and Economics.
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This seminar is co-organised by Centre for Quantitative Finance (CQF), Risk Management Institute (RMI) and NUS Chongqing Research Institute, NUS.
Join our Webinar Session @National University of Singapore |
| Date: 2 Jun 2022 (Thursday) |
| Time: 1500hr – 1600hr (Singapore Time Zone, GMT +8) |
Programme
| 1500hr – 1600hr |
Title: Distributed inference in extreme value statistics Prof. Chen Zhou (Erasmus University Rotterdam)
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A Short Biography of Speaker
Chen Zhou is Professor of Mathematical Statistics and Risk Management at the Econometrics Institute, Erasmus University Rotterdam. He is also a senior economist at De Nederlandsche Bank (Dutch Central Bank). Chen’s research focuses on extreme value statistics and its applications in quantitative risk management, financial stability and financial regulation. His statistical work has been published in statistical journals such as Annals of Statistics, Journal of Royal Statistical Society (Series B) and Journal of American Statistical Association. His applied work has been published in economic and finance journals such as Journal of Financial and Quantitative Analysis and Journal of Economic Theory. Chen is also the area editor of Extremes in Economics, Finance and Insurance.
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This seminar is co-organised by Centre for Quantitative Finance (CQF), Risk Management Institute (RMI) and NUS Chongqing Research Institute, NUS.
Join our Webinar Session @National University of Singapore |
| Date: 26 May 2022 (Thursday) |
| Time: 0900hr – 1000hr (Singapore Time Zone, GMT +8) |
Programme
| 0900hr – 1000hr |
Title: On the Aggregation of Probability Assessments: Regularized Mixtures of Predictive Densities for Eurozone Inflation and Real Interest Rates
We propose methods for constructing regularized mixtures of density forecasts. We explore a variety of objectives and regularization penalties, and we use them in a substantive exploration of Eurozone inflation and real interest rate density forecasts. All individual inflation forecasters (even the ex post best forecaster) are outperformed by our regularized mixtures. From the Great Recession onward, the optimal regularization tends to move density forecasts’ probability mass from the centers to the tails, correcting for overconfidence. arXiv:2012.11649 |
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A Short Biography of Speaker
Francis X. Diebold is Paul F. Miller, Jr. and E. Warren Shafer Miller Professor of Social Sciences, and Professor of Economics, Finance, and Statistics, University of Pennsylvania. He has held visiting appointments at Princeton, Chicago, Johns Hopkins, and NYU. His research focuses on predictive modeling of financial asset markets, macroeconomic fundamentals, and the interface. He has made well-known contributions to the measurement and modeling of asset-return volatility, business cycles, yield curves, and network connectedness. He has published more than 150 scientific papers and 8 books, and he is regularly ranked among globally most-cited economists. He is Founding Fellow and Past President, Society for Financial Econometrics; NBER Faculty Research Associate; Fellow, Econometric Society, American Statistical Association, Guggenheim Foundation, Sloan Foundation, Humboldt Foundation, Journal of Econometrics; Founding Fellow, International Association for Applied Econometrics, Society for Economic Measurement; Honorary Fellow, International Institute of Forecasters; and Past Editorial Board Member, Econometrica, Review of Economics and Statistics, and International Economic Review. His academic “family” includes more than 75 Ph.D. students.
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This seminar is co-organised by Centre for Quantitative Finance (CQF), Risk Management Institute (RMI) and NUS Chongqing Research Institute, NUS.
Join our Webinar Session @National University of Singapore |
| Date: 24 November 2021 (Wednesday) |
| Time: 2000hr – 2100hr (Singapore Time Zone, GMT +8) |
Programme
| 2000hr – 2100hr |
Title: What Is Absence of Arbitrage in a General Setting?
In recent years, there have been several criticisms concerning classical arbitrage theory in the spirit of Delbaen and Schachermayer, and some new approaches with different goals and ideas have emerged. We re-examine the classical theory with a particular focus on making it as robust to changes of numeraire as possible in as general a setting as possible. This requires to develop a new (and more general) concept of absence of arbitrage, which we then characterise in a dual manner by martingale properties of the given financial market. As a teaser, we invite you to think about the following question: When exactly is the Black-Scholes model, consisting of a stock given by a geometric Brownian motion and a bank account with a deterministic interest rate, arbitrage-free on an infinite horizon? The talk is based on joint work with Daniel Balint. |
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A Short Biography of Speaker
Martin Schweizer is professor of mathematics at ETH Zurich. His research interests include mathematical finance and its connections to probability theory and stochastic processes. He has worked on many different topics including hedging in incomplete markets, stochastic control, insider information, arbitrage theory etc. He is also Editor of the Springer journal “Finance and Stochastics”.
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This seminar is co-organised by Centre for Quantitative Finance (CQF), Risk Management Institute (RMI) and NUS Chongqing Research Institute, NUS.
Join our Webinar Session @National University of Singapore |
| Date: 10 November 2021 (Wednesday) |
| Time: 2000hr – 2100hr (Singapore Time Zone, GMT +8) |
Programme
| 2000hr – 2100hr | Title: Optimal Bidding Strategy for Targeted Advertising Prof. Huyen Pham (University Paris Diderot) Abstract: We introduce and study several optimal control models of targeted advertising with auctions. Each model focuses on a different type of advertising, namely, commercial advertising for triggering purchases or subscriptions, and social marketing for raising public awareness about unhealthy behaviors (anti-drug, road-safety campaigns). All our models are based on a common framework encoding people’s online behaviours and the targeted advertising auction mechanism widely used on Internet. Our main results are to provide semi-explicit formulas for the optimal value and bidding policy for each of these problems. By means of these formulas, we are able to analyze and interpret how phenomenons like people’s online behaviors and social interactions affect the optimal bid for targeted advertising auctions. We also study how to efficiently combine targeted advertising and non-targeted advertising mechanism. We conclude by providing some classes of examples with fully explicit formulas.
Joint work with Médéric Motte (Université de Paris)
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A Short Biography of Speaker
Huyên PHAM is Distinguished Professor of Mathematics at Université de Paris, and adjunct Professor at ENSAE. He leads research in quantitative finance, stochastic analysis and control, machine learning techniques for numerical probabilities, and is the author of more than 100 publications, including the monograph Continuous time Stochastic Control and Optimization with Financial Applications. He serves on the editorial boards of several international journals, and is the co-editor in chief of the journal Applied Mathematics and Optimization. Prof. Pham was appointed member of the Institut Universitaire de France in 2006, awarded the Louis Bachelier prize by the French Academy of Sciences in 2007, and was a plenary speaker at the 9th World congress of the Bachelier Finance Society in 2016, and at the 6th Asian Quantitative Finance Conference in 2018.
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This seminar is co-organised by Centre for Quantitative Finance (CQF), Risk Management Institute (RMI) and NUS Chongqing Research Institute, NUS.
Join our Webinar Session @National University of Singapore |
| Date: 6 October 2021 (Wednesday) |
| Time: 2000hr – 2100hr (Singapore Time Zone, GMT +8) |
Programme
| 2000hr – 2100hr | Title: Rogue Traders Prof. Paolo Guasoni (Dublin City University) Abstract: Investing on behalf of a firm, a trader can feign personal skill by committing fraud that with high probability remains undetected and generates small gains, but that with low probability bankrupts the firm, offsetting ostensible gains. Honesty requires enough skin in the game: if two traders with isoelastic preferences operate in continuous-time and one of them is honest, the other is honest as long as the respective fraction of capital is above an endogenous fraud threshold that depends on the trader’s preferences and skill. If both traders can cheat, they reach a Nash equilibrium in which the fraud threshold of each of them is lower than if the other one were honest. More skill, higher risk aversion, longer horizons, and greater volatility all lead to honesty on a wider range of capital allocations between the traders. |
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A Short Biography of Speaker
Paolo Guasoni holds the Stokes Chair in Financial Mathematics at Dublin City University since 2009 and specializes in Mathematical Finance, focusing on the effects of market frictions, incentives, and preferences in portfolio choice and asset pricing. Guasoni has published in the Annals of Applied Probability, Finance and Stochastics, Journal of Financial Economics, Mathematical Finance, and the SIAM Journal on Financial Mathematics, and has attracted funding by the European Research Council, the National Science Foundation, Science Foundation Ireland, and the European Commission. Guasoni serves as Coeditor for Finance and Stochastics and as Associate Editor Mathematical Finance, SIAM Journal in Financial Mathematics, Applied Mathematical Finance, and the European Journal of Finance.
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This seminar is co-organised by Centre for Quantitative Finance (CQF), Risk Management Institute (RMI) and NUS Chongqing Research Institute, NUS. Join our Webinar Session @National University of Singapore |
| Date: 21 September 2021 (Tuesday) |
| Time: 1600hr – 1700hr (Singapore Time Zone, GMT +8) |
Programme
| 1600hr – 1700hr | Title: Peer Prediction Markets to Elicit Unverifiable Information Prof. Aurélien Baillon (Erasmus University Rotterdam)Abstract: Prediction markets reward ex-post accuracy to incentivize agents to seek and reveal information. Some private signals, such as individual experiences or very long-run predictions, do not concern verifiable outcomes. In such cases, outcome-based rewards are not feasible. This paper presents peer prediction markets to elicit subjective judgments in binary questions of unverifiable information. Agents choose whether they receive a costly signal, which lead them to endorse either `yes’ or `no’ as an answer. Then, they either buy or sell a single unit of an asset at a price whose price is determined by endorsement rate of `yes’. The price of the asset is set at the prior expectation of the endorsement rate. We obtain a separating equilibrium, where agents buy or sell the asset as a function of their signal. Evidence from two experimental studies demonstrate that peer prediction markets motivate agents to seek costly information and reveal it. |
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A Short Biography of Speaker
Aurélien Baillon is Professor of Economics of Uncertainty and Head of the Behavioral Economics group, at Erasmus University Rotterdam. His work focuses on individual decision making under risk and ambiguity, and the elicitation of private information. Through both empirical and theoretical studies, his research addresses issues in subjective probability elicitation, models of attitude towards risk and ambiguity, and aggregation of expert opinions. He is also associate editor at Management Science, coordinating editor at Theory and Decision, and has published in prestigious journals such as Econometrica, The American Economic Review, PNAS, and Psychological Science.
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This seminar is co-organised by Centre for Quantitative Finance (CQF), Risk Management Institute (RMI) and NUS Chongqing Research Institute, NUS.
Join our Webinar Session @National University of Singapore |
| Date: 17 September 2021 (Friday) |
| Time: 1600hr – 1700hr (Singapore Time Zone, GMT +8) |
Programme
| 1600hr – 1700hr | Title: From If to What If — EVT revisited as a QRM tool Prof. Paul Embrechts (ETH Zurich) Abstract: Extreme Value Theory (EVT) has been recognized as an important tool for the analysis of financial data. In particular within Quantitative Risk Management, EVT allows for a model view beyond the Gaussian paradigm. In this talk I will recall some of the main results from EVT and highlight several applications. From a QRM point of view, an If-world is mainly frequency oriented (think e.g. of Value-at-Risk), on the other hand, a What If view is more concerned with severity (e.g. Expected Shortfall). In a forthcoming book with Marius Hofert and Valerie Chavez, with as title “Risk, Told: Cautionary Tales, Understanding and Communication“, we highlight this distinction in several ways. |
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A Short Biography of Speaker
From 1989 till 2018, Paul Embrechts was Professor of (Insurance) Mathematics at the ETH Zurich. He became emeritus professor in 2018 and currently is associated with ETH’s RiskLab and Risk Center. Besides numerous academic distinctions, he holds an Honorary Doctorate from the Universities of Waterloo, Heriot-Watt, Louvain, and City, the University of London. Previous academic positions were KU Leuven, the University of Limburg, Imperial College London and the London School of Economics. Dr Embrechts served as an independent director on the boards of companies in banking and insurance and co-authored the influential books “Modelling Extremal Events for Insurance and Finance”, Springer, 1997, and “Quantitative Risk Management: Concepts, Techniques and Tools”, Princeton University Press, 2005/2015. His extensive research of over 200 scientific papers has been published in leading international scientific journals.
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This seminar is co-organised by Centre for Quantitative Finance (CQF), Risk Management Institute (RMI) and NUS Chongqing Research Institute, NUS.
Join our Webinar Session @National University of Singapore |
| Date: 8 September 2021 (Wednesday) |
| Time: 2000hr – 2100hr (Singapore Time Zone, GMT +8) |
Programme
| 2000hr – 2100hr | Title: Asset Pricing with Liquidity Risk Prof. Muhle-Karbe Johannes (Imperial College London) Abstract: We study how equilibrium asset prices depend on liquidity, that is, the ease with which the assets can be traded. In particular, we disentangle the impact of liquidity levels and liquidity risk.Mathematically, this leads to multidimensional, nonlinear and fully coupled systems of forward-backward stochastic differential equations, which admit tractable asymptotic expansions in the small-cost limit.(Joint work in progress with Agostino Capponi and Xiaofei Shi.) |
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A Short Biography of Speaker
Johannes Muhle-Karbe is the Head of the Mathematical Finance Section at Imperial College London and the Director of the CFM-Imperial Institute of Quantitative Finance. Before joining Imperial, he held faculty positions at Carnegie Mellon University, the University of Michigan and ETH Zurich. Johannes’ research focuses on “frictions” such as transaction costs, price impact, or asymmetric information, and how these affect optimal trading strategies, risk management, and asset prices.
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This seminar is co-organised by Centre for Quantitative Finance (CQF), Risk Management Institute (RMI) and NUS Chongqing Research Institute, NUS.
Join our Webinar Session @National University of Singapore |
| Date: 27 August 2021 (Friday) |
| Time: 2100hr – 2200hr (Singapore Time Zone, GMT +8) |
Programme
| 2100hr – 2200hr | Title: Projects in Financial Machine Learning Prof. Bryan Kelly (Yale School of Management) Abstract: The presentation gives an overview of financial machine learning models and applications including ML factor models, textual analysis, and image analysis based on the papers: “Characteristics are Covariances,” “Instrumented Principal Components Analysis,” “Autoencoder Asset Pricing Models,” “The Structure of Economic News,” “Predicting Returns With Text Data,” “Principal Portfolios,” and “Re-imagining Price Trends.” |
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A Short Biography of Speaker
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 is the head of machine learning at AQR Capital Management. Professor Kelly’s primary research fields are asset pricing and financial econometrics. He is interested in issues related to financial machine learning; volatility, tail risk, and correlation modeling in financial markets; banking sector systemic risk; financial intermediation; and financial networks. He has served as co-editor of the Journal of Financial Econometrics and associate editor of Journal of Finance and Journal of Financial Economics. Before joining Yale, Kelly was a tenured professor of finance at the University of Chicago Booth School of Business. He earned a bachelor’s degree in economics from University of Chicago, a master’s degree in economics from University of California San Diego, and a PhD in finance from New York University’s Stern School of Business. Kelly worked in investment banking at Morgan Stanley prior to his PhD.
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This seminar is co-organised by Centre for Quantitative Finance (CQF), Risk Management Institute (RMI) and NUS Chongqing Research Institute, NUS.
Join our Webinar Session @National University of Singapore |
| Date: 14 May 2021 (Friday) |
| Time: 1600hr – 1700hr (Singapore Time Zone, GMT +8) |
Programme
| 1600hr – 1700hr | Title: Becker Meets Kyle: Legal Risk and Insider Trading Dr. Emiliano Pagnotta (Imperial College London) Abstract: Do illegal insiders internalize legal risk? We address this question with hand-collected data from 530 SEC investigations. Using two plausibly exogenous shocks to expected penalties, we show that insiders trade less aggressively and earlier and concentrate on tips of greater value when facing higher risk. The results match the predictions of a model where an insider internalizes the impact of trades on prices and the likelihood of prosecution and anticipates penalties in proportion to trade profits. Our findings lend support to the effectiveness of U.S. regulations’ deterrence and the long-standing hypothesis that insider trading enforcement can hamper price informativeness. |
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A Short Biography of Speaker
Dr. Emiliano Pagnotta is an Assistant Professor of Finance at Imperial College Business School. His research focuses on the exchange and valuation of financial assets and the organization and evolution of the markets where those assets trade in. Recent work by Dr. Pagnotta analyzes the consequences of speed and fragmentation in financial markets, the identification of private information in stock and derivatives markets, and the valuation of Bitcoin and other blockchain assets. His research is regularly presented in leading academic and professional conferences and published in academic journals such as Econometrica and The Review of Financial Studies.
Before joining Imperial College, Emiliano Pagnotta was at the New York University Stern School of Business. He holds a BA in Economics from the University of Buenos Aires, an MA in Economics from Universidad de San Andrés, Argentina, and a Ph.D. in Economics from Northwestern University.
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This seminar is co-organised by Centre for Quantitative Finance (CQF), Risk Management Institute (RMI) and NUS Chongqing Research Institute, NUS.
Join our Webinar Session @National University of Singapore |
| Date: 22 April 2021 (Thursday) |
| Time: 1600hr – 1700hr (Singapore Time Zone, GMT +8) |
Programme
| 1600hr – 1700hr | Title: Revisiting the Anticompetitive Effects of Common Ownership Associate Professor José Azar (University of Navarra) Abstract: We use data from the U.S. airline industry to test the hypothesis, consistent with the general equilibrium oligopoly model of Azar and Vives (forthcoming), that inter-industry common ownership should be associated with lower prices in product markets. We find that, as the model predicts, increases over time in intra-industry common ownership are associated with higher prices, while increases in inter-industry common ownership are associated with lower prices. We also find that common ownership by the ”Big Three” (BlackRock, Vanguard and State Street) is associated with lower airline prices, while common ownership by shareholders other than the Big Three is associated with higher prices. The results highlight the limitations of partial equilibrium oligopoly theory in the context of common ownership, and the need to consider a general equilibrium perspective. |
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A Short Biography of Speaker
José Azar is an economist specializing in antitrust and corporate governance. His work studies the implications for competition of the rise of common ownership of companies by large and diversified asset managers. More recently, he has done research on labor market concentration and power. He is a member of Economics for Inclusive Prosperity (EfIP). Before joining IESE, he worked at Charles River Associates in the Antitrust and Competition Practice. He received his BA from Universidad Torcuato Di Tella in Argentina, and his PhD from Princeton University.
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This seminar is co-organised by Centre for Quantitative Finance (CQF), Risk Management Institute (RMI) and NUS Chongqing Research Institute, NUS.
Join our Webinar Session @National University of Singapore |
| Date: 26 March 2021 (Friday) |
| Time: 1600hr – 1700hr (Singapore Time Zone, GMT +8) |
Programme
| 1600hr – 1700hr |
Title: Towards Quantum Advantage in the Financial Service Sector Dr Stefan Woerner (IBM Research Zurich) Abstract: Quantum computing promises speed-ups for several applications relevant in the financial service sector. In this talk, we will discuss some quantum algorithms to speed up Monte Carlo simulation as well as quantum heuristics for combinatorial optimization and machine learning. Applications in pricing & risk analysis, portfolio optimization, and fraud detection will be analyzed with respect to the potential quantum advantages as well as expected requirements to realize it.
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A Short Biography of Speaker
Dr. Stefan Woerner is the Global Lead for Quantum Applications Research & Software in IBM Quantum and a Research Staff Member in the Quantum Technologies group at IBM Research – Zurich. He received a Master of Science in Applied Mathematics from ETH Zurich in 2010, and a Doctor of Sciences in Operations Management from ETH Zurich in 2013 for his thesis on Convex Optimization in Supply Chain Management. The focus of his research is the development and analysis of quantum algorithms for optimization, simulation, and machine learning as well as their practical applications.
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This seminar is co-organised by Centre for Quantitative Finance (CQF), Risk Management Institute (RMI) and NUS Chongqing Research Institute, NUS.
Join our Webinar Session @National University of Singapore |
| Date: 18 March 2021 (Thursday) |
| Time: 2000hr – 2100hr (Singapore Time Zone, GMT +8) |
Programme
| 2000hr – 2100hr |
Title: Fundamental Pricing of Utility Tokens Prof Julien Prat (CREST, Paris, France) Abstract: We propose a framework for the fundamental valuation of utility tokens. Our model endogenizes the velocity of circulation of tokens and yields a pricing formula that is fully microfounded. According to our model, tokens are valuable because they have to be immediately accessible when the services are needed, a requirement that is reminiscent of the cash-in-advance constraint. The equilibrium price paths of successful projects go through two successive phases: A speculative phase where marginal holders are investors that do not intend to use the services and, later on, a user phase where all tokens are held by clients. Calibrating the model, we find that it helps rationalizing the extreme volatility and significant valuation of tokens early on during the adoption stage.
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A Short Biography of Speaker
Prof Julien Prat is an economist working on Blockchains, contract theory, macroeconomics and labor economics. He is a 2004 Ph.D. graduate from the economics department of the European University Institute. He is currently working as a CNRS director of research at CREST, and an associate professor at the Ecole Polytechnique. Previously, he held assistant professorship positions at the University of Vienna and at the Institute for Economic Analysis (CSIC) in Barcelona.
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This seminar is co-organised by Centre for Quantitative Finance (CQF), Risk Management Institute (RMI) and NUS Chongqing Research Institute, NUS.
Join our Webinar Session @National University of Singapore |
| Date: 26 February 2021 (Friday) |
| Time: 0900hr – 1000hr (Singapore Time Zone, GMT +8) |
Programme
| 0900hr – 1000hr | Title: Expected and Realized Returns on Volatility Prof. Kris Jacobs (University of Houston)Abstract: Expected returns on market volatility, which can be obtained from VIX futures in closed form using standard models, predict subsequent multiperiod realized volatility returns. Multiperiod realized volatility returns are more negative following increases in volatility. Expected volatility returns are always negative. They also become more negative when volatility increases because of differences in mean reversion between the VIX and the risk-neutral VIX. Expected volatility returns negatively predict index returns, because realized volatility returns are negatively correlated with index returns. The results are robust to a wide range of variations in the empirical setup and the inclusion of existing predictors. |
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A Short Biography of Speaker
Prof. Kris Jacobs is the Bauer Chair in Finance at the Bauer College of Business, University of Houston. His research focuses on empirical asset pricing, investments and derivative securities, and he teaches courses in Investments, Capital Markets and Portfolio Management at the Ph.D. and Master’s levels. He obtained his Ph.D. from the University of Pittsburgh and his Master’s and undergraduate degrees from the Katholieke Universiteit Leuven in his native Belgium. He has previously held appointments at McGill University and Tilburg University (visiting).
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This seminar is co-organised by Centre for Quantitative Finance (CQF), Risk Management Institute (RMI) and NUS Chongqing Research Institute, NUS.
Join our Webinar Session @National University of Singapore |
| Date: 25 February 2021 (Thursday) |
| Time: 2000hr – 2100hr (Singapore Time Zone, GMT +8) |
Programme
| 2000hr – 2100hr |
Title: Dynamic programming for mean field optimal stopping Prof Nizar Touzi (Ecole Polytechnique) Abstract: We study the problem of optimal stopping of a population of mean field interacting McKean-Vlasov diffusions. The objective function depends on the distribution of the stopped process. We derive the dynamic programming equation for this problem as an obstacle equation on the Wasserstein space, and we characterize the nature of the optimal stopping rule. |
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A Short Biography of Speaker
Nizar Touzi is Professor of Applied Mathematics at Ecole Polytechnique since 2006. He was previously Chair Professor at Imperial College London. He was an invited session speaker at the International Congress of Mathematicians (Hyderabad 2010). He received the Louis Bachelier prize of the French Academy of Sciences in 2012, and the Paris Europlace prize of Best Young Researcher in Finance in 2007. In 2010, he held the University of Toronto Dean’s Distinguished Chair position. He is Co-editor and Associate Editor in various international journals in the fields of financial mathematics, applied probability, and control theory.
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This seminar is co-organised by Centre for Quantitative Finance (CQF), Risk Management Institute (RMI) and NUS Chongqing Research Institute, NUS.
Join our Webinar Session @National University of Singapore |
| Date: 29 January 2021 (Friday) |
| Time: 2000hr – 2100hr (Singapore Time Zone, GMT +8) |
Programme
| 2000hr – 2100hr |
Title: Portfolio Liquidation Games with Self-Exciting Order Flow Prof Ulrich Horst (Humboldt-Universitat Zu Berlin) Abstract: We analyze novel portfolio liquidation games with self-exciting order flow. Both the N-player game and the mean-field game are considered. We assume that players’ trading activities have an impact on the dynamics of future market order arrivals thereby generating an additional transient price impact. Given the strategies of her competitors each player solves a mean-field control problem. We characterize open-loop Nash equilibria in both games in terms of a novel mean-field FBSDE system with unknown terminal condition. Under a weak interaction condition we prove that the FBSDE systems have unique solutions. Using a novel sufficient maximum principle that does not require convexity of the cost function we finally prove that the solution of the FBSDE systems do indeed provide existence and uniqueness of open-loop Nash equilibria. The talk is based on joint work with Guanxing Fu (Hong Kong Polytechnic University) and Xiaonyu Xia (HU Berlin).
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A Short Biography of Speaker
Prof Horst is Professor of Applied Financial Mathematics at Humboldt University Berlin (HUB). He received his PhD in Mathematics form HUB in 2000. After his graduation he spent several years teaching in Germany and North America. Before he returned to Berlin in the summer of 2007 he was an Assistant Professor at the Department of Mathematics at the University of British Columbia in Vancouver. Ulrich Horst held visiting positions at various institutions including the Departments Economics and of Operations Research and Financial Engineering at Princeton University, the Institute for Mathematical Economics at Bielefeld University, the Center for Mathematical Modelling at the Universidad de Chile, and the CEREMADE at the Paris Dauphine University. From July 2007 to June 2011 he was Scientific Director of the Deutsche Bank sponsored Quantitative Products Laboratory, and from March to August 2015, he was a Fellow at the Center for Interdisciplinary Research (ZIF) in Bielefeld. He was the Head of HUB’s the Mathematics Department for the last five years.
This seminar is co-organised by Centre for Quantitative Finance (CQF), Risk Management Institute (RMI) and NUS Chongqing Research Institute, NUS.
Join our Webinar Session @National University of Singapore
| Date | : | 15th January 2021 (Friday) |
| Time | : | 2000hr – 2100hr (Singapore Time Zone, GMT +8) |
Programme
| 2000hr – 2100hr |
Title: Stochastic Partial differential equation models for limit order book dynamics Prof Rama Cont (University of Oxford ) Abstract: We propose an analytically tractable class of models for the dynamics of a limit order book, described as the solution of a stochastic partial differential equation (SPDE) with multiplicative noise. We provide conditions under which the model admits a finite dimensional realization driven by a (low-dimensional) Markov process, leading to efficient methods for estimation and computation. We study two examples of parsimonious models in this class: a two-factor model and a model in which the order book depth is mean-reverting. For each model we perform a detailed analysis of the role of different parameters, study the dynamics of the price, order book depth, volume and order imbalance, provide an intuitive financial interpretation of the variables involved and show how the model reproduces statistical properties of price changes, market depth and order flow in limit order markets.
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https://nus-sg.zoom.us/webinar/register/WN_q0bgVksOQAaE6kZxn1YpHg
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A Short Biography of Speaker
Rama Cont is Professor of Mathematics and Chair of Mathematical Finance at the University of Oxford and Director of the EPSRC Centre for Doctoral Training in Mathematics of Random Systems. Rama Cont’s research focuses on stochastic analysis, stochastic processes and mathematical modeling in finance, in particular the modeling of extreme market risks, liquidity risk and systemic risk and pathwise approaches in stochastic analysis. He has co-authored more than 80 research publications,including the widely cited monograph Financial Modelling with Jump Processes (2003). He was the founding director of the Columbia Centre for Financial Engineering and founding director of the CFM-Imperial Institute of Quantitative Finance from 2014 to 2018.Prof. Cont was awarded the Louis Bachelier Prize by the French Academy of Sciences in 2010 for his research on mathematical modeling in finance and the Royal Society Award for Excellence in Interdisciplinary Research in 2017 for his work on systemic risk modelling. He was elected Fellow of the Society for Industrial and Applied Mathematics (SIAM) in 2017 for his ‘contributions to stochastic analysis and mathematical modeling in finance.’
This seminar is co-organised by Centre for Quantitative Finance (CQF), Risk Management Institute (RMI) and NUS Chongqing Research Institute, NUS.
Join our Webinar Session @National University of Singapore
| Date | : | 11th December 2020 (Friday) |
| Time | : | 0900 AM – 1100 AM (Singapore Time Zone, GMT +8) |
https://nus-sg.zoom.us/webinar/register/WN_CIlG6o6PSPufE0lYwOIb-Q
Programme
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0900 AM – 1000 AM |
Title: Toward a Factor Model of Relative Valuation
Prof Liuren Wu
Abstract: The concept of market valuation relative to book cost has been used as the starting point for comparing relative performance, performing bottom-up valuation, and identifying profitable investment opportunities. This paper proposes a statistical factor model to explain the cross-sectional variation of company valuation relative to book cost. The factors are constructed to capture the principal dimensions of firm characteristics that drive the relative value variation. The factor loadings, estimated via cross-sectional regressions of company relative value on the factors at each point in time, represent the market pricing of the valuation factors at that point in time on the company’s relative value. Historical analysis on U.S. publicly traded companies shows that the factor model explains a large proportion of the cross-sectional variation of company relative value across different sample periods and experiences little out-of-sample degeneration. The residual relative value variations unexplained by the factor model represent temporary company misvaluation, and can be exploited by both outside investors as attractive investment opportunities and internal management for market timing financing decisions.
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1000 AM – 1100 AM |
Title: Monotone Additive Statistics
Prof Omer Tamuz (California Institute of Technology) Joint with Profs Xiaosheng Mu, Luciano Pomatto and Philipp Strack
Abstract: A statistic is a mapping from bounded random variables to real numbers. We characterize all statistics that are monotone with respect to first-order stochastic dominance, and are additive for sums of independent random variables. We explore a number of applications, including a representation of dynamically-consistent, monotone time preferences, generalizing Fishburn and Rubinstein (1982), and a characterization of posted prices for risks.
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About the Speakers
Liuren Wu is the Wollman Distinguished Professor of Finance at Zicklin School of Business, Baruch College, City University of New York. Professor Wu’s research interests cover option pricing, credit risk and term structure modeling, market microstructure, and general asset pricing. Professor Wu has published over 50 articles, many of them in top finance journals such as the Journal of Finance, the Journal of Financial Economics, Review of Financial Studies, the Journal of Financial and Quantitative Analysis, Management Science, and Journal of Monetary Economics. Mr. Wu has worked extensively as consultants in the finance industry, including Bloomberg, Morgan Stanley, Royal Bank of Canada, and several fixed income, equity, and equity options hedge funds and market making firms, where he has developed statistical arbitrage trading strategies, risk management procedures, optimal trade execution and market making strategies, and quantitative models for pricing fixed income and equity derivative securities.
Omer Tamuz is a Professor of Economics and Mathematics at Caltech. He is interested in probability, dynamics and group theory, and in their applications to topics in microeconomic theory, including information, risk and uncertainty, and social choice. He got his B.Sc. in computer science and physics from Tel Aviv University, where he participated in the search for extrasolar planets. In 2013 he received his Ph.D. in mathematics from the Weizmann Institute. From 2013 until 2015 he was a Schramm postdoctoral fellow at the MIT math department / Microsoft Research. He has been at Caltech since 2015.
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This seminar is co-organised by Centre for Quantitative Finance (CQF), Risk Management Institute (RMI) and NUS Chongqing Research Institute, NUS.
Join our Webinar Session @National University of Singapore |
| Date: 19 November 2020 (Thursday) |
| Time: 1000hr – 1200hr (Singapore Time Zone, GMT +8) |
Programme
| 1000hr – 1100hr |
Title: How do Machines Learn Finance? Prof Jianqing FAN (Princeton University) Abstract: This talk first gives an overview on the genesis of machine learning and AI and how statistical and computational methods have evolved with big data and become the foundation of modern machine learning and AI. It will also outline how ideas of trading modeling biases and variances have been developed into high-dimensional statistics and machine learning, with focus on deep learning models. We will highlight three applications: portfolio choices with text data via feature screening, predicability of the momentum and duration in high-frequency finance via several statistical machine learning methods, and sparse portfolio allocation and Sharpe ratio estimation.
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| 1100hr – 1200hr |
Title: GANs through MFGs and SDEs approximations Prof Xin GUO (University of California, Berkeley) Abstract: Generative Adversarial Networks (GANs) have celebrated great empirical success, especially in image generation and processing and more recently in simulation of financial time series data. In this talk, we will discuss some of our recent works in mathematical understanding of GANs. The first is the theoretical connection between GANs and mean field games (MFGs) and optimal transport (OT): interpreting MFGs as GANs, on one hand, allows us to devise GANs-based algorithms to solve high dimensional MFGs. Interpreting GANs as MFGs and OT, on the other hand, provides a new and probabilistic foundation for GANs. The second is on approximating GANs training in the form of SDEs. This SDEs approximation provides basic analytical tools to investigate some well-recognized issues (e.g., convergence and explosive gradient) in the machine learning community for GANs training.
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https://nus-sg.zoom.us/webinar/register/WN_z0WTHBh3TDmitLUlqBpX7w
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A Short Biography of Speakers
Jianqing Fan is Frederick L. Moore Professor of Finance, Professor of Statistics, Former Chairman of Department of Operations Research and Financial Engineering and Director of Committee of Statistical Studies at Princeton University, where he directs both financial econometrics and statistics labs. He was the past president of the Institute of Mathematical Statistics and International Chinese Statistical Association. He is co-editing Journal of Business and Economics Statistics, and was the co-editor of The Annals of Statistics, Probability Theory and Related Fields, Journal of Econometrics and Econometrics Journal. After receiving his Ph.D. from the University of California at Berkeley, he has been appointed as assistant, associate, and full professor at the University of North Carolina at Chapel Hill (1989-2003), professor at the University of California at Los Angeles (1997-2000), and professor at the Princeton University (2003–). His published work on statistics, economics, finance, machine learning and computational biology has been recognized by The 2000 COPSS Presidents’ Award, The 2007 Morningside Gold Medal of Applied Mathematics, Guggenheim Fellow in 2009, P.L. Hsu Prize in 2013, Royal Statistical Society Guy medal in silver in 2014, Senior Noether Scholar Award in 2018, and election to Academician of Academia Sinica and follow of American Associations for Advancement of Science, Institute of Mathematical Statistics, American Statistical Association, and Society of Financial Econometrics. His research interest includes high-dimensional statistics, machine learning, financial econometrics, and computational biology.
Professor Xin Guo is the Coleman Fung Chair professor at the IEOR department of UC Berkeley. Prior to Berkeley, she worked at IBM Watson research center (1999-2003) and at Cornell University (2004-2007). Her current research interests include stochastic controls and games, machine learning theory, medical data and financial time series data analysis.
| Join our Webinar Session @National University of Singapore |
| Date: 22nd October 2020 (Thursday) |
| Time: 2000hr – 2200hr (Singapore Time Zone, GMT +8) |
Programme
| 2000hr – 2100hr |
Title: AHEAD : Ad-Hoc Electronic Auction Design Prof Mathieu ROSENBAUM (Ecole Polytechnique) Abstract: We introduce a new matching design for financial transactions in an electronic market. In this mechanism, called ad-hoc electronic auction design (AHEAD), market participants can trade between themselves at a fixed price and trigger an auction when they are no longer satisfied with this fixed price. In this context, we prove that a Nash equilibrium is obtained between market participants. Furthermore, we are able to assess quantitatively the relevance of ad-hoc auctions and to compare them with periodic auctions and continuous limit order books. We show that from the investors’ viewpoint, the microstructure of the asset is usually significantly improved when using AHEAD. This is joint work with Joffrey Derchu, Philippe Guillot and Thibaut Mastrolia
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| 2100hr – 2200hr |
Title: Personalized Robo-Advising: Enhancing Investment through Client Interaction A/Prof Agostino CAPPONI (Columbia University) Abstract: Automated investment managers, or robo-advisors, have emerged as an alternative to traditional financial advisors. The viability of robo-advisors crucially depends on their ability to offer personalized financial advice. We introduce a novel human-machine interaction framework, in which the robo-advisor solves an adaptive mean-variance portfolio optimization problem. The risk-return tradeoff dynamically adapts to the client’s risk profile, which depends on idiosyncratic characteristics as well as on market performance and varying economic conditions. We characterize the optimal level of personalization in terms of a tradeoff faced by the robo-advisor between receiving client information in a timely manner and mitigating the effect of behavioral biases in the risk profile communicated by the client. We argue that the optimal portfolio’s Sharpe ratio and return distribution improve if the robo-advisor counters the client’s tendency to reduce portfolio risk during economic contractions, when the market risk-return tradeoff is more favorable.
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Registration via https://nus-sg.zoom.us/webinar/register/WN_zrqXuAgtTIauN_GdMwDExw
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A Short Biography of Speakers
Mathieu ROSENBAUM is a full professor at École Polytechnique, where he holds the chair “Analytics and Models for Regulation” and is co-head of the quantitative finance (El Karoui) master program. His research mainly focuses on statistical finance problems, regulatory issues and risk management of derivatives. He published more than 60 articles on these subjects in the best international journals. He is notably one of the most renowned experts on the quantitative analysis of market microstructure and high frequency trading.
On this topic, he co-organizes every two years in Paris the conference “Market Microstructure, Confronting Many Viewpoints”. He is also at the origin (with Jim Gatheral and Thibault Jaisson) of the development of rough volatility models. Mathieu Rosenbaum has collaborations with various financial institutions (investment banks, hedge funds, regulators, exchanges…), notably BNP-Paribas since 2004. He also has several editorial activities as he is one of the editors in chief of the journal “Market Microstructure and Liquidity“ and is associate editor for 10 other journals. He received the Europlace Award for Best Young Researcher in Finance in 2014, the European Research Council Grant in 2016 and the Louis Bachelier prize in 2020.
Agostino CAPPONI is an Associate Professor in the Department of Operations Research at Columbia University, and a member of the Data Science Institute. He also serves as a consultant at the U.S. Commodity Futures Trading Commission. Agostino‘s research has been recognized with the 2018 NSF CAREER award, the JP Morgan AI Research Faculty award, and several best paper award prizes. Agostino is editor of the Finance Department at Management Science. He also serves as editor of the Financial Engineering Department at Operations Research Letters and at the IESE Transactions. Agostino also serves on the editorial board of Operations Research, SIAM Journal in Financial Mathematics, Finance and Stochastics, Mathematics and Financial Economics, Stochastic Systems, and other journals of his field. Agostino’s research has been funded by NSF, DARPA, the US Department of Energy, Institute for New Economic Thinking, IBM, the Global Risk Institute, and other private agencies. Agostino serves as the chair of the SIAM Activity Group in Financial Engineering, and as the president of the INFORMS Finance Section.
| Join our Webinar Session @National University of Singapore |
| Date: 18 September 2020 (Friday) |
| Time: 2000hr – 2200hr (Singapore Time Zone, GMT +8) |
Programme
| 2000hr – 2100hr |
Title: When will the Covid-19 pandemic peak? Prof Oliver LINTON (University of Cambridge) Abstract: We carry out some analysis of the daily data on the number of new cases and the number of new deaths by (191) countries as reported to the European CDC. We work with a quadratic time trend model applied to the log of new cases for each country. This seems to accurately describe the trajectory of the epidemic in China. We use our model to predict when the peak of the epidemic will arise in terms of new cases or new deaths in other large countries.
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| 2100hr – 2150hr |
Title: A Theory of FinTech Prof Steven KOU (Boston University) Abstract: In this talk I will give a brief overview of current academic research on Fintech by using tools from mathematics and statistics. The topics to be discussed include: (1) Designing stable coins: how to design stable cryptocurrency by using option pricing theory. (2) P2P equity financing: how to design contracts suitable for a P2P equity financing platform with information asymmetry. (3) Data privacy preservation: how to do econometrics based on the encrypted data while still preserving privacy. (4) The wisdom of the crowd and prediction markets: how to use the collective opinion of a group to make predictions. All the above 4 topics are based on my recent papers.
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Registration via https://nus-sg.zoom.us/webinar/register/WN_0-1qbmtERq-Z6_5oxpGFWQ
Upon registration, a confirmation email will send to you with the website link and passcode for you to dial in.
A Short Biography of Speakers
Oliver Linton is a fellow of Trinity College and is Professor of Political Economy at Cambridge University. Formerly, he was Professor of Econometrics at the London School of Economics and Professor of Economics at Yale University. He obtained his PhD in Economics from the University of California at Berkeley in 1991. He has written more than a hundred articles on econometrics, statistics, and empirical finance. In 2015 he was a recipient of the Humboldt Research Award of the Alexander von Humboldt Foundation. He was a Co-editor at the Journal of Econometrics between 2014-2019. He is a Fellow of: the Econometric Society, the Institute of Mathematical Statistics, and the British Academy. He was a lead expert in the U.K. Government Office for Science Foresight project: “The future of Computer Trading in Financial Markets”, which published in 2012. He has acted as an expert witness in two stock market manipulation cases in the UK.
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 on 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 is a fellow of the Institute of Mathematical Statistics and 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.