Neil Chriss – A conversation with Jim Gatheral

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.

Abstract:

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

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.

Abstract:

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

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).

Abstract:

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

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.

Abstract:

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, Formerly Global Head of Operational Risk Measurement at Morgan Stanley

Abstract:

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

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

Abstract:

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, 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.

Abstract:

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

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.

Abstract:

• 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

Introduction to Quant Macro Investing

Jim Conklin, Managing Director and Head of Investment Research, Product Development Committee, FX Concepts

Abstract:

• 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

Dr. Todd Mitty – A conversation with Jim Gatheral

Todd Mitty, Global Head of Delta One Business Development at Credit Suisse

Abstract:

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

Interviewing for Quant Positions

Jim Gatheral

Professor Jim Gatheral will talk about interviewing for quant positions and answer related questions. Jim is a researcher in the field of Mathematical finance, who has contributed to the study of volatility as applied to the pricing and risk management of derivatives.

He received his PhD in theoretical physics from Cambridge University (1983), and a B.Sc. in Mathematics and Natural Philosophy from the University of Glasgow. He worked at Bank of America and Bankers Trust before heading the Equity Quantitative Analytics group at Merrill Lynch in 1996, where he was a managing director for 17 years. In 1998 he became a fellow of the Masters Program of Mathematics in Finance at the Courant Institute of Mathematical Sciences of New York University, where he was an adjunct professor for 12 years. In March 2010, Jim Gatheral left his position at Merrill Lynch to assume a tenured full professor position at the Financial Engineering Masters Program at Baruch College, where he is teaching volatility surface modeling and market microstructure.

A recurrent subject in his books and papers is the volatility smile, and he published in 2006 a book ‘The volatility surface’ based on a course he taught for 6 years at New York University, along with Nassim Taleb. More recently his work has moved in the direction of Market microstructure, especially as applied to Algorithmic Trading.

Date: September 15, 2010

Security pricing services: How valuation models are replacing evaluators

Andrew Kalotay, Kalotay Associates

Date: March 26, 2009

Managing Diversification

Attilio Meucci, Bloomberg L.P.

Date: March 20, 2009

Mortgage-backed Securities

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

Starting a Hedge Fund

Alex Gurvich, The Rockledge Group

Date: March 1, 2007

An American Hedge Fund

Timothy SykesDate: October 19, 2007

Global Credit Crisis

Greg Caruso, CapitalSource Finance

Date: November 9, 2007

Interest Rate Models’ Implied Volatility Function Stochastic Movements

Blessing Mudavanhu, Merrill Lynch

Date: November 30, 2007