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SUMMARY:2018 Quantitative Risk Management & Financial Analytics Workshop
DTSTAMP;TZID=America/Toronto:20180510T083000
DTSTART;TZID=America/Toronto:20180510T083000
DTEND;TZID=America/Toronto:20180510T193000
X-ALT-DESC;FMTTYPE=text/html:It is our pleasure to invite you to this workshop event jointly\norganized by the Telfer School of Management and the Department of\nMathematics and Statistics at the University of Ottawa.\n\nThe finance industry has recently been undergoing a major\ntechnological transformation driven by the development of new\nanalytics solutions. In particular\, risk management as the basis of\nany financial activity has shifted to a data-driven regime where the\nuse of quantitative measures has became a standard either for the\npurpose of internal risk control or external risk regulations. The\ncore of these analytical solutions and quantitative methods is the\nnovel design and use of statistical and optimization algorithms\, which\nenable complex datasets to be analyzed in the search for a better\nsolution. New developments along this line can be found across\ndisciplines. The aim of this workshop is to bring together researchers\nworking to improve analytical solutions and practitioners who deal\nwith challenging financial and risk management problems and seek\nbetter solutions.\n\nThe list of topics to be covered during the workshop includes\, but is\nnot limited to\n\n * Quantitative risk management: concepts\, techniques\, and tools\,\n * Optimization in finance and risk management\,\n * Statistical (Machine) learning in finance and risk management\,\n * Data analytics in finance and risk management\,\n * Portfolio optimization\n * Risk measurement and hedging\n * Modeling of financial derivatives\, asset management\, capital\nbudgeting\, etc.\n\nThe workshop consists of 1) distinguished lectures by leading academic\nand industrial researchers and practitioners\, 2) contributed talks on\nrecent research advances.\n\nINVITED SPEAKERS\n\n [Coleman] \n\nTHOMAS F. COLEMAN\n\n Ophelia Lazaridis University Research Chair\nProfessor\, Combinatorics and Optimization\, University of Waterloo\nDirector\, Waterloo Research Institute in Insurance\, Securities and\nQuantitative Finance (WatRISQ)\nFellow\, Society for Industrial and Applied Mathematics (SIAM) \n\nTITLE : LEARNING MINIMUM VARIANCE DISCRETE HEDGING DIRECTLY FROM THE\nMARKET.\n\nABSTRACT\n\n Option hedging is a critical risk management problem in finance. In\nthe Black-Scholes model\, it has been recognized that computing hedging\nposition from the sensitivity of the calibrated model option value\nfunction is inadequate in minimizing variance of the option hedge\nrisk\, as it fails to capture the model parameter’s dependence on the\nunderlying price\, see e.g.\, [16\, 37]. In this paper we demonstrate\nthat this issue can exist generally when determining hedging position\nfrom the sensitivity of the option function\, either calibrated from a\nparametric model from current option prices or estimated\nnonparametricaly from historical option prices. Consequently\, the\nsensitivity of the estimated model option function typically does not\nminimize variance of the hedge risk\, even instantaneously. We propose\na data driven approach to directly learn a hedging function from the\nmarket data by minimizing variance of the local hedge risk. Using the\nS&P 500 index daily option data for more than a decade ending in\nAugust 2015\, we show that the proposed method outperforms the\nparametric minimum variance hedging method proposed in [37]\, as well\nas minimum variance hedging corrective techniques based on stochastic\nvolatility or local volatility models. Furthermore\, we show that the\nproposed approach achieves significant gain over the implied BS delta\nhedging for weekly and monthly hedging. \n\nBIOGRAPHY\n\nProfessor Thomas F. Coleman holds the Ophelia Lazaridis University\nResearch Chair at the University of Waterloo. The focus of this chair\nis on the design of efficient optimization methodologies targeted to a\nvariety of scientific and industrial applications.\n\nProfessor Coleman also heads the research effort at the Global Risk\nInstitute. In 2010-2011 Coleman served on the “oversight\ncommittee” to establish the new Canadian national institute\, the\nGlobal Risk Institute in Financial Services (GRI)\, a not-for-profit\nprivate/public organization. He chaired the GRI subcommittee\, the\nResearch Structure Committee\, to establish the research\nmandate/framework for GRI.\n\nFrom 2005 to 2010 Coleman served as the dean of the Faculty of\nMathematics at the University of Waterloo. This Faculty of five\ndepartmental units consists of 200 faculty members\, 5000\nundergraduates\, close to 1000 graduate students. During Coleman’s\ntenure as dean\, the Faculty of Mathematics acquired funds for\, and\nbegan the construction of a new Faculty building (Math 3)\, became a\nfounding member of a new UW campus in the UAE\, established outreach\noffices in Toronto and Shanghai\, developed numerous international\npartnerships\, and\, with the support of the Bill and Melinda Gates\nFoundation ($12.5M)\, greatly expanded the high school reach of the\nCentre for Education in Mathematics and Computing.\n\nPrior to 2005 Coleman was a professor of computer science at Cornell\nUniversity\; he was a faculty member in the Computer Science Department\nat Cornell University for 24 years\, 1981-2005. In the period 1998-2005\nhe was also the director of the Cornell Theory Center (CTC – a\nsupercomputer applications center) which received major support from\nnumerous technology companies\, primarily Microsoft. He was chair of\nthe SIAM Activity Group on Optimization (1998-2001). During his tenure\nas CTC director\, Coleman founded and directed CTC-Manhattan\, a\ncomputational finance academic-industry-government venture located at\n55 Broad Street in New York.\n\nColeman is the author of four books on computational mathematics\, the\neditor of six proceedings\, and has published over one hundred journal\narticles in the areas of optimization\, automatic differentiation\,\nparallel computing\, computational finance\, and optimization\napplications. Coleman is currently on the editorial board of several\nprofessional journals. Coleman had developed\, with colleagues\, both\nfreely-available and commercial software for optimization use and\napplication. In 2016 Coleman became a fellow of the Society for\nIndustrial and Applied Mathematics.\n\nColeman also heads a boutique consulting/solutions company\, Cayuga\nResearch Inc.\, working with industry clients on predictive\noptimization applications (application areas include: health and\nmedicine\, climate change\, logistics and shipping\, finance and banking\,\ninsurance fraud detection).\n\n [Davinson] \n\nMATT DAVINSON\n\n Professor\, Statistical and Actuarial Sciences\, Western University\nDirector – School of Mathematical & Statistical Sciences\nFields Institute Fellow \n\nTITLE: WHERE DATA SCIENCE MEETS THE DISMAL SCIENCE\n\nABSTRACT\n\n Banks and other financial institutions grant “Small” loans (up to\nand including half million dollar mortgages) are typically granted to\napplicants as the result of an automatic process in which the\nresponses to a set of questions (about income\, other assets debts\,\netc) are combined into a score which is then compared to a threshold.\nApplicants with a score better than a certain threshold are granted a\nloan with a given set of terms. Exactly how the scoring algorithm\nworks is\, of course\, to some degree confidential\, but incentives to\n“game” the loan granting system nonetheless remain. In this talk I\ngive an introduction to modern data-driven retail credit and discuss\nan iterated game in which some borrowers (or their agents)\ndeliberately falsifies aspect of her application\, while other\nborrowers do not. The third player here is the bank. High level\nstrategy and policy conclusions are drawn. (Joint with Cristian Bravo\nand Mimi Chong) \n\nBIOGRAPHY\n\n Formerly (2006-2016) Tier 2 Canada Research Chair in Quantitative\nFinance\, Matt Davison is the director of the new School of\nMathematical & Statistical Sciences at Western University in London\nOntario. He has co-authored 67 papers\, 9 book chapters\, 13 refereed\nconference proceedings\, and a patent\, and is the author of the\nfinancial mathematics textbook Quantitative Finance: A\nSimulation-based introduction using Excel. Matt works in the areas of\ncommodities trading\, green energy finance\, financial risk management\,\nand industrial mathematics\, and draws upon techniques and insights\nfrom business\, economics\, engineering\, mathematics\, and statistics. \n [Lam] \n\nHENRY LAM\n\n Associate Professor\, Department of Industrial Engineering and\nOperations Research\,\nColumbia University \n\nTITLE: ROBUST EXTREME RISK ANALYSIS\n\nABSTRACT\n\n Understanding extremal risks is central to financial and insurance\nmanagement. One bottleneck in analyzing extreme events is that\, by its\nown definition\, tail data is often scarce. Conventional approaches fit\ndata using justified parametric distributions\, but the inherent\nbias-variance tradeoff in the parametric fitting can hinder the\nestimation reliability. We discuss approaches using robust\noptimization as a nonparametric alternative that\, through a different\nconservativeness-variance tradeoff\, can mitigate some of the\nstatistical challenges in estimating tails. Our framework uses\noptimization imposed over probability distributions to compute\nconfidence bounds on extremal performance measures\, under constraints\nthat capture tail geometries and other obtainable information. We\ndiscuss the solution approaches and statistical performances compared\nto the conventional methods\, and present some extensions such as\napplications in rare-event simulation. \n\nBIOGRAPHY\n\n Henry Lam is an Associate Professor in the Department of Industrial\nEngineering and Operations Research in Columbia University. He\nreceived his Ph.D. in statistics from Harvard University in 2011\, and\nwas on the faculty of Boston University and the University of Michigan\nbefore joining Columbia in 2017. Henry’s research interests include\nMonte Carlo simulation\, risk analysis\, and stochastic and\nsimulation-based optimization. His work has been recognized by several\nvenues such as the NSF Career Award (2017)\, the INFORMS JFIG\nCompetition Second Prize (2016) and the Adobe Faculty Research Award\n(2016). He serves on the editorial boards of Operations Research and\nINFORMS Journal on Computing. \n [Luis] \n\nLUIS SECO\n\n Professor\, Department of Mathematics\, University of Toronto\nDirector\, Mathematical Finance Program\nDirector of RiskLab Toronto\nPresident and CEO Sigma Analysis and Management \n\nTITLE: POSTMODERNISM IN FINANCE: THE MATHEMATICS OF MANAGEMENT FEES\n\nABSTRACT\n\n Low negative rates and the low performance environment are putting\npressure on the investment business. In this talk we will analyze the\nvaluations of fee structures\, and propose frameworks where the Black-\nScholes valuation of new fee structures delivers value to managers and\ninvestors alike. \n\nBIOGRAPHY\n\n Luis Seco is Professor of Mathematics at the University of Toronto\,\nwhere he also directs the Mathematical Finance program and the\nRiskLab\, a research laboratory in financial risk management. He is\nalso the President and CEO of Sigma Analysis & Management\, an asset\nmanagement firm that specializes in hedge fund investments for\ninstitutional investors. He obtained his PhD at Princeton University\nand worked at Caltech. \n\nCONFERENCE PROGRAM\n\n8:30 AM – 8:50 AM – On site registration and coffee\n\n8:50 AM – 9:00 AM – Welcome and Introduction\n\n9:00 AM – 9:50 AM – Keynote Speaker (THOMAS F. COLEMAN)\n\n10:00 AM -11:15 AM – Contributed sessions (25 minutes each)\n\n * SPEAKER: XIANGJIN SHEN (Senior Economist\, Financial Institutions\nDivision\, Financial Stability\, Bank of Canada)\nTITLE: Joint tail risk analysis by the Vine Copula\n * SPEAKER: JUN CAI (Department of Statistics and Actuarial Science\,\nUniversity of Waterloo)\nTITLE: Risk measures based on the behavioural economics theory\n * SPEAKER: MARCOS ESCOBAR-ANEL (Department of Statistical and\nActuarial Sciences\, Western University)\nTITLE: Robust Portfolio Choice with Derivative Trading\nin Continuous Time.\n\n11:15 AM – 11:40 AM – Coffee break\n\n11:40 AM – 12:30 PM – Keynote Speaker (MATT DAVISON)\n\n12:30 PM – 2:00 PM – Lunch break\n\n2:00 PM – 3:15 PM – Contributed sessions (25 minutes each)\n\n * SPEAKER: JORGE CRUZ LOPEZ (Principal Researcher\, Funds Management\nand Banking Department\, Bank of Canada)\nTITLE: Residual Risk and Default Waterfalls in Central Counterparties\n * SPEAKER: MAARTEN VAN OORDT (Senior Analyst\, Financial Stability\nDepartment\, Bank of Canada)\nTITLE: Systemic Risk and Bank Business Models\n * SPEAKER: GARETH WITTEN (Executive-in-Residence\, Global Risk\nInstitute\, Toronto. Professor. Sugnet Lubbe\, Department of Statistics\nand Actuarial Science\, University of Stellenbosch\, South Africa.)\nTITLE: Visualizing variables in Covariance Analysis with biplots:\napplications in risk management\n\n3:15 PM – 4:05 PM – Keynote Speaker (HENRY LAM)\n\n4:05 PM -4 :30 PM – Coffee break\n\n4:30 PM – 5:20 PM – Keynote Speaker (LUIS SECO)\n\n5:30 PM – 7:30 PM – Networking Reception – 12th Floor\, DMS 12102\n\nORGANIZING COMITEE\n\nRAFAL KULIK\n[https://www.uottawa.ca/faculty-science/professors/rafal-kulik]\,\nDepartment of Mathematics and Statistics\, University of Ottawa\n\nJONATHAN YU-MENG LI\n[https://telfer.uottawa.ca/en/directory/jonathan-yumeng-li/]\, Telfer\nSchool of Management\, University of Ottawa\n\nSPONSORS\n\n[Fields logo]\n\n[Uottawa logo]\n\n[Canssi logo]\n
LOCATION:Telfer School of Management\, Desmarais Building\, Camille Villeneuve Room (DMS4101)\, 55 Laurier Avenue East\, Ottawa\, Ontario K1N 6N5
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