19th Annual Financial Mathematics Quant Symposium 2017

Nineteenth Annual Financial Mathematics Quant Symposium

(Formerly: Financial Math Festival)

February 17-18, 2017

Schedule of Events

Friday, 17 February 2017

3:15 p.m., 204B Love Building


3:45 p.m., 101 Love Building

Welcome, Announcements and Recognitions

Welcome, by Xiaoming Wang, Chair, Department of Mathematics
Message from the Dean, College of Arts and Sciences
Announcements and Recognitions, by Alec Kercheval, Director of Financial Mathematics

4:00 p.m., 101 Love Building


Ling Zhu, Department of Mathematics, introducing Peter Carr
Giray Ökten, Department of Mathematics, introducing Linlin Xu
Mike Navon, Department of Scientific Computing, introducing John Geng

4:10 p.m., 101 Love Building

Convexity adjustments in rates products

Dr. John Geng

Quantitative Associate, Wells Fargo, Charlotte

Rates products range from vanilla products like swaps and European swaptions to exotic products involving full term structure models. In terms of model complexity, convexity adjustment lies in the middle of these two extremes. In this talk, we will discuss the theory behind the convexity adjustment and related products, such as CMS swaps, caps, floors, and spread options.

5:20 p.m., New Chemistry Building Lobby


Saturday, 18 February 2017

9:00 a.m., 204B Love Building

Bagels & Coffee

9:30 a.m., 101 Love Building

Tropical Finance: How to Have your Cake and Eat it Too

Dr. Peter Carr

Chair of the Finance and Risk Engineering Department, New York University

A convertible bond allows its holder to choose whether the instrument should be a bond or a stock. We present a radically simple arbitrage-free valuation formula based on ideas found in tropical mathematics.

10:15 a.m., 204B Love Building

Short Break

10:30 a.m., 101 Love Building

Algorithmic Differentiation in Finance

Dr. Linlin Xu

Associate, Quantitative Analytics, Barclays, NYC

Sensitivity analysis plays an important role in risk management in large financial institutions. Fast and accurate sensitivity calculation becomes challenging when the pricing problem itself is computationally expensive. Algorithmic differentiation (AD) is a fast algorithm that delivers all risks for 4-6x cost of valuation regardless of the number of inputs. We briefly introduce the idea of AD and discuss the challenges of applying it in practice. We then review its performance in production code for several financial instruments.

11:15 a.m., 101 Love Building

Jobs! Q and A

Information for students about jobs in the sector.

Panel: the Speakers

11:45 a.m., 2nd Floor, Love Building

Student Poster Session

Students defend their work in the poster prize competition.

Cooperating Departments are: Computer Science, Economics, Finance, Mathematics, Risk Management, Scientific Computing, and Statistics. For more information on graduate study in Financial Mathematics and a list of participating faculty, see the homepage for Financial Mathematics at Florida State University.

News and Highlights


Thanks for advice and support to our Financial Sector Advisors: Greg Anderson (Bank of America Merrill Lynch), E. Robert Fernholz (former Chief Investment Officer INTECH), Lisa Goldberg (UC Berkeley), Wenbo Hu (Bell Trading), Benoit Montin (Barclay's Capital), Steven Perfect (FSU), Edward Qian (PanAgora), Dan Waggoner (Federal Reserve Bank Atlanta).

Special thanks to faculty and staff for planning and execution, to Xiaoming Wang of the Department of Mathematics and Dean Sam Huckaba of the College of Arts and Sciences for financial support to make this event possible.