Sebastián Ceria, Axioma
Before founding Axioma,Dr. Sebastián Ceria was an Associate Professor of Decision, Risk and Operations at Columbia Business School from 1993 to 1998. He was honored with the prestigious Career Award for Operations Research from the National Science Foundation, which is given annually to the two best researchers and teachers in the area. While at Columbia he was also recognized as the “best core teacher” by his students and the school. Additionally, Ceria has served as administrator for the Computational Optimization Research Center and as co-principal investigator in two National Science Foundation research projects.
Ceria is the author of many articles and has been featured regularly in a variety of publications including Management Science, Mathematical Programming, Optima and Operations Research. He has also been an editor for Optima, and a regular referee for a number of publications in the area. Past speaking engagements include international corporate and academic conferences.
Date: January 24, 2012
Neil Chriss, Managing Principal at Hutchin Hill Capital
Dr. Neil Chriss is one of the top quants in the world. More information on Dr. Chriss’s career as a hedge fund manager, an academic and financial engineering educator, and a highly successful poker player, can be found at Wikipedia.
Professor Jim Gatheral invited Dr. Neil Chriss to a conversation on how his mathematical training contributed to his success, and how he sees the future for mathematically-trained people.
Date: September 26, 2011
Tim Grant, Benchmark Solutions: Understanding the Difference Between Risk Taking, Risk Management and Risk Control
Understanding the Difference Between Risk Taking, Risk Management and Risk Control
Tim Grant, Benchmark Solutions
Tim Grant spent 10 years at UBS. He was an early member of the UBS Delta group (a portfolio solutions and analytics business within the Fixed Income Sales and Trading Division) from 1999 and ultimately led that business in the Americas. In 2008 he reported directly to the Group Chief Risk Officer and was assigned to the team managing the bank’s portfolio of distressed real estate assets.
With respect to the recent financial crisis was it risk management and quantitative modeling that failed the people? Or was it the people who were supposed to be implementing risk management strategies and leveraging quantitative finance that failed the people? Let’s discuss.
Date: May 06, 2011
Luca Capriotti, Credit Suisse: Algorithmic Differentiation: Adjoint Greeks Made Easy
Algorithmic Differentiation: Adjoint Greeks Made Easy
Luca Capriotti, Director, Credit Suisse
Dr. Luca Capriotti is a Director at Credit Suisse Group, Investment Banking Division, where he works in the Quantitative Strategies Group(formerly known as GMAG) in the New York city office. He is currently focusing on modeling in the areas of Structured Credit, and Counterparty Credit Risk Management. He is also working on developing efficient and general multi-asset Monte Carlo engines supporting fast calculation of Greeks for which he has a Patent pending. Previous to this role, he has worked in Commodities Exotics in New York and London and in the cross-asset modeling R&D group of GMAG in the London office. His current research interests are in the field of Credit Default Intensity Modelling and Computational Finance, mainly focusing on efficient numerical techniques for Derivatives Pricing and Risk Management. Luca holds a M.S. cum laude in General Physics from University of Florence (1996), and an M.Phil. and Ph.D. cum laude in Condensed Matter Theory, from the International School for Advanced Studies, Trieste (2000).
Show how algorithmic differentiation can be used as a design paradigm to implement the adjoint calculation of sensitivities in Monte Carlo in full generality and with minimal analytical effort. With several examples we illustrate the workings of this technique and demonstrate how it can be straightforwardly implemented to reduce the time required for the computation of the risk of any portfolio by orders of magnitude.
Date: April 29, 2011
Miguel Castro, Two Sigma Investment: Forecasting in High-Frequency Trading
Forecasting in High-Frequency Trading
Miguel Castro, Managing Director, Two Sigma Investments
Dr. Miguel Castro has 10 years of experience in algorithmic trading. He is presently Managing Director at Two Sigma Investments where he leads a small quant research team in high-frequency algorithmic trading. Before Two Sigma, he worked for a large European bank, and prior to that, for another quantitative hedge fund. Before his life in finance, he worked in research and development for Intel Corporation. Miguel holds a B.A. in Physics and Mathematics from Cornell University, an M.S. in Electrical Engineering with specialty in Machine Learning, and a Ph.D. in Physics, both from Purdue University. He also holds an MBA with emphasis in finance from the University of California at Berkeley’s Haas School of Business.
Forecasting is at the heart of algorithmic trading. Besides the usual difficulties due to market efficiencies, high-frequency forecasting presents its own set of challenges. We will consider forecasting in the context of high-frequency algo trading, and explore some challenges and useful techniques.
Date: April 12, 2011
Ron Burtnett – A Conversation with Jim Gatheral
Ron Burtnett – A conversation with Jim Gatheral
Ron Burtnett, Formerly Global Head of Operational Risk Measurement at Morgan Stanley
Professor Jim Gatheral invited Ron Burtnett to a conversation on how his mathematical training contributed to his success, and how he sees the future for mathematically-trained people. This promises to be an exceedingly interesting event, with a “Charlie Rose” format!
Date: January 25, 2011
Peter Carr, Morgan Stanley: An Alternate History of the Black-Scholes PDE
An Alternate History of the Black Scholes PDE
Peter Carr, Global Head of Market Modeling at Morgan Stanley
Dr. Peter Carr is a Managing Director at Morgan Stanley in New York. He is also the Executive Director of the Masters in Math Finance program at NYU’s Courant Institute. Prior to his current positions, he headed quantitative research groups at Bloomberg LP and at Bank of America Securities. His prior academic positions include 4 years as an adjunct professor at Columbia University and 8 years as a finance professor at Cornell University. Since receiving his PhD. in Finance from UCLA in 1989, he has published extensively in both academic and industry-oriented journals. He is currently the treasurer of the Bachelier Finance Society and an associate editor for 8 journals related to mathematical finance and derivatives. He has given numerous talks at both practitioner and academic conferences. He is also credited with numerous contributions to quantitative finance including: co-inventing the variance gamma model, inventing static and semi-static hedging of exotic options, and popularizing variance swaps and corridor variance swaps. Peter has won awards from Wilmott Magazine for “Cutting Edge Research” and from Risk Magazine for “Quant of the Year”. Peter has just been named the 2010 IAFE Financial Engineer of the Year
The Black-Scholes partial differential equation (PDE) was first published in 1973, having been derived previously by Black in 1969. This linear PDE is celebrated primarily because it is independent of the attitudes towards risk of investors in the economy. In 1968, Black derived a nonlinear PDE that shares this fundamental risk-neutral property. We show that the famous linear PDE could have been derived from the nonlinear PDE using financial and mathematical concepts available in 1968.
Date: November 29, 2010
Michael Botlo – A Conversation with Jim Gatheral
Michael Botlo – A conversation with Jim Gatheral
Michael Botlo, co-founder and the CEO of Quantbot Technologies
Dr. Michael Botlo is a co-founder and the CEO of the quantitative investment advisor Quantbot Technologies that transacts daily in many global equity markets. Before 2009, he led Electronic Product Development in the Global Market Division at Merrill Lynch. In this role, he was responsible for the implementation of the automated trading vision across liquid asset classes. Before joining Merrill, Michael was a founding member of the Electronic Trading Lab at Morgan Stanley. The group successfully developed the Firm’s electronic capabilities in global Delta1 Equities, from quantitative proprietary to algorithmic agency businesses. Michael holds a Masters Degree in Astronomy and a PhD in Elementary Particle physics. He has spent several years as a research fellow at various nuclear research facilities across the globe.
Professor Jim Gatheral invited Dr. Michael Botlo to a conversation regarding careers in quant space, and their future. This promises to be an exceedingly interesting event, with a “Charlie Rose” format!
In an informal conversation with Jim Gatheral, Michael Botlo will describe his current role at Quantbot, his previous career, how his mathematical training has contributed to his success, and how he sees the future for mathematically-trained people. Questions from the audience are encouraged.
Date: November 29, 2010
John Crosby, UBS: Optimal Hedging of Variance Derivatives
Optimal Hedging of Variance Derivatives
John Crosby, Executive Director, Quantitative Analytics and Derivatives Research at UBS, London , and Visiting Professor of Quantitative Finance, Glasgow University
John began his career by trading FX options. He then moved to Monis (formerly London Business School Financial Software) where he wrote their pricing libraries for a very wide range of exotic derivatives as well as co-writing their three-factor Convertible bond model, which captured stochastic equity prices, interest-rates and default risk. He then headed quant teams at Barclays Capital and Lloyds where he developed derivatives models across all asset classes. He is best known for publishing several papers in the area of commodity and hybrid derivatives. John is a visiting Professor at Glasgow University and an invited lecturer on the M.Sc. course in Mathematical Finance at Oxford University as well as being an Executive Director in the front-office Fixed Income, Foreign Exchange and Commodity derivatives research and quantitative analytics team at UBS.
- Hedging of variance swaps – why the existing log-contract approach is, in general, sub-optimal
- Optimal hedging of variance swaps
- Optimal hedging of other variance-equity hybrid derivatives
- Implications for hedging under extreme market conditions such as in Autumn 2008
Date: November 16, 2010
Jim Conklin, FX Concepts: Introduction to Quant Macro Investing
Introduction to Quant Macro Investing
Jim Conklin, Managing Director and Head of Investment Research, Product Development Committee, FX Concepts
- General description of the investment strategy, sector, in the context of the “buy-side” as a whole
- Opportunities for “quants” in the Quant Macro area
- Quantitative description of the strategy: forecasting methods
- Quantitative description of the strategy: the use of optimization
Date: November 2, 2010
Todd Mitty – A Conversation with Jim Gatheral
Dr. Todd Mitty – A conversation with Jim Gatheral
Todd Mitty, Global Head of Delta One Business Development at Credit Suisse
Professor Jim Gatheral invited Dr. Todd Mitty to a conversation regarding careers in quant space, and their future. This will be an exceedingly interesting event, with a “Charlie Rose” format.
Date: November 1, 2010
Security pricing services: How valuation models are replacing evaluators
Andrew Kalotay, Kalotay Associates
Date: March 26, 2009
Attilio Meucci, Bloomberg L.P.
Date: March 20, 2009
Robert Young, Citigroup
Date: March 13, 2009
Applications for Financial Engineering at the Fed
Karen H. Johnson, Federal Reserve Board
Date: February 20, 2009
Is There A Future for Financial Engineering?
Martin Helm, Deutsche Bank
Date: February 13, 2009
Structuring Trade Execution Analytics Around theInvestment Process
Ian Domowitz, Investment Technology Group
Date: December 16, 2008
Quantitative Challenges in Algorithmic Execution
Robert Almgren, Quantitative Brokers
Date: December 9, 2008