Our New York City talks began in 2011, marking our first move outside Britain. Harvey Stein and Matthew Dixon organise our New York talks. We have also started to run joint IAQF/Thalesians talks in NYC.
Next New York events
IAQF-Thalesians Seminar (New York) — Dr. Agostino Capponi — Arbitrage-Free Pricing of XVA
Monday, September 21, 2015:
NYU Kimmel Center, Room 914, Kimmel Center, 60 Washington Square South, NY 10012, NY
The recent financial crisis has highlighted the importance to account for counterparty risk and funding costs in the valuation of over-the-counter portfolios of derivatives. When managing their portfolios, traders face costs for maintaining the hedge of the position, posting collateral resources, and servicing their collateral requests. Due to the interdependencies between these operations, such costs cannot be separated and attributed to different business units (CVA, DVA and FVA desks).
In this talk, we introduce a unified framework for computing the total costs, referred to as XVA, of an European style derivative transaction traded between two risky counterparties. We use no-arbitrage arguments to derive the nonlinear backward stochastic differential equations (BSDEs) associated with the portfolios which replicate long and short positions in the claim.
This leads to defining buyer's and seller’s XVAs which in turn identify a no-arbitrage band. When borrowing and lending rates coincide, our framework recovers a generalized version of Piterbarg's model. In this case, we provide a fully explicit expression for the uniquely determined price of XVA. When they differ, we derive the semi-linear partial differential equations (PDEs) associated with the non-linear BSDEs and show that they admit a unique classical solution. We use these solutions to conduct a numerical analysis showing high sensitivity of the no-arbitrage band and replicating strategies to funding spreads and collateral levels.
Agostino Capponi is an assistant professor in the IEOR Department at Columbia University, where he is also a member of the Institute for Data Science and Engineering. Agostino received his Master and Ph.D. Degree in Computer Science and Applied and Computational Mathematics from the California Institute of Technology, respectively in 2006 and 2009.
His main research interests are in the area of networks, with a special focus on systemic risk, contagion, and control. In the context of financial networks, the outcome of his research contributes to a better understanding of risk management practices, and to assess the impact of regulatory policies aimed at controlling financial markets. He has been awarded a grant from the Institute for New Economic Thinking for his research on dynamic contagion mechanisms. His work on systemic risk dynamics under central clearing done in collaboration with the Department of Treasury has obtained press coverage from major organizations such as Bloomberg and Reuters. His research has been published in top-tier journals of Financial Mathematics, Operations Research, and Engineering. His work has also been published in leading practitioner journals and invited book chapters. Agostino holds a world patent for a target tracking methodology in military networks.
The IAQF-Thalesians Seminar Series is a joint effort on the part of the IAQF (formerly IAFE) and the Thalesians. The goal of the series is to provide a forum for the exchange of new ideas and results related to the field of quantitative finance. This goal is accomplished by hosting seminars where leading practitioners and academics present new work, and following the seminars with a reception to facilitate further interaction and discussion. The seminar series is limited to IAQF and Thalesians members only.
NYU Kimmel Center
Room 914, 60 Washington Square South
NY 10012, NY
Lower Level Conference Room 014/015
New York Public Library: Science Industry and Business Library
188 Madison Avenue, New York, NY
New York Leader
Harvey Stein (New York City Leader)
Harvey J. Stein is Head of the Quantitative Risk Analytics Group at Bloomberg, responsible for all quantitative aspects of Bloomberg's risk analysis products. Dr. Stein graduated from Worcester Polytechnic Institute in 1982 with a Bachelor's degree in mathematics. After working at Bolt, Beranek and Newman for three years on developing and designing the precursor to the Internet, Dr. Stein went to graduate school at the University of California, Berkeley, where he studied arithmetical geometry while working at Wells Fargo Investment Advisors. He received his PhD in mathematics from Berkeley in 1991.
For the last twenty-three years, Dr. Stein has worked at Bloomberg LP. He built one of the top quantitative finance research and development groups in the industry. His group supplied derivative valuation models for interest rate derivatives, mortgage backed securities, foreign exchange, credit, equities, and commodities, and built Linux clusters to supply these valuations to Bloomberg's customers.
Dr. Stein is well known in the industry, having published and lectured on mortgage backed security valuation mortgage backed security valuation, CVA calculations, interest rate modeling, credit exposure calculations, and other subjects. Dr. Stein built Bloomberg's business in the area of counterparty credit risk modeling and is currently focusing on regulation and risk modeling. He is also a member of the advisory board of the IAQF, an adjunct professor at Columbia University, and a board member of the Rutgers University Mathematical Finance program and of the NYU Enterprise Learning program.
Matthew Dixon is a Managing Director and Head of Americas at Thalesians Ltd.
He is also an Assistant Professor of Finance in the Stuart Business School at the Illinois Institute of Technology. His research focuses on the application of advanced computational techniques to financial modeling and data analysis especially where high performance and scalability are critical for practical application. Matthew's research is currently funded by Intel Corporation. He has contributed to the R package repository and published around twenty peer-reviewed technical articles. He has taught financial econometrics, derivatives, machine learning and text mining at the University of San Francisco and held visiting appointments in CS/Math at Stanford University and UC Davis.
Prior to joining academia, he has held industry appointments as a quant at banks such as Lehman Brothers, the Bank for International Settlements and Barclays Capital. He chairs the workshop on computational finance at the annual SuperComputing conference and serves on the program committee of HPC and on the editorial board of the Journal of Financial Innovation. Matthew holds a MEng in Civil Engineering from Imperial College London, a MSc in Parallel and Scientific Computation (with distinction) from the University of Reading, and a PhD in Applied Math from Imperial College London. He became a chartered financial risk manager in 2014.
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