Rupak Chatterjee

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Rupak Chatterjee, PhD, is the Co-Director of the Center for Quantum Science and Engineering at the Stevens Institute of Technology. He is a professor in the Department of Physics and an inaugural member of the Hanlon Financial Systems Center. His last role on Wall Street before returning to academia was as Director of the Multi-Asset Hybrid Derivatives Research group at Citigroup in New York. He was also the Global Basel III coordinator for all modeling efforts needed to satisfy the new regulatory risk requirements imposed on banks. Previously, he was a quantitative analyst at Barclays Capital, a vice president at Credit Suisse, and a senior vice president at HSBC. His educational background is in theoretical physics which he studied at Stony Brook University and the University of Chicago. 



Background and Early Life

Education

Research Fellow, University of Chicago.

Ph.D., Theoretical Physics, Stony Brook University.

M. Math, University of Waterloo.

B. Sc., University of Calgary.

Career

Stevens Institute of Technology, New Jersey (2012-Present)

Professor; Founding Member of the Center for Quantum Science and Engineering

Citigroup, New York (2005-2012)

Global Head of Basel III Modelling; Director of Multi-Asset Quantitative Research

HSBC, New York (2001-2005)

Senior Vice President, Quantitative Analyst

Credit Suisse First Boston, New York (1999-2001)

Vice President, Quantitative Analyst

Barclays Capital, New York (1997-1999)

Derivatives Structurer/Quantitative Analyst

Personal Life

Professor Chatterjee grew up in Calgary, the largest city in the province of Alberta, Canada. As a seventh grader, he learned to play the tenor saxophone and was determined to forge a career in jazz. Yet, like his physicist father, he decided to pursue the study of physics. He went on to earn a Ph.D. in theoretical physics at Stony Brook University. Though he veered away from a career in music, he continues to play the tenor sax as a semi-pro. Every summer, he performs a few concerts with a small band at Woodbury Commons in Central Valley, NY. Professor Chatterjee’s career in banking happened serendipitously. At the time of his graduation from the University of Chicago, the Cold War had ending and opportunities for newly minted physicists shrunk drastically. Wall Street firms were recruiting and Professor Chatterjee was offered a position at Barclays Capital as a derivatives structurer/quantitative analyst in New York City. Thus began his career trajectory, as he later became a vice president at Credit Suisse and a senior vice president at HSBC. Prior to returning to academia, he was Director of the Multi-Asset Hybrid Derivatives Quantitative Research group at Citigroup in New York. He was also the Global Basel III coordinator for all modeling efforts needed to satisfy the new regulatory risk requirements imposed on banks.

Life at Stevens

Ph.D. Students

Sebastian Tudor

Master's Thesis Students

Not Available


Teaching

Research

Active Research Project(s)

Quantum Computing and Computational Finance

The complexities of the financial world have grown dramatically in the twenty first century. A clear manifestation of this was the 2007 subprime mortgage crisis that led to a global recession. The widespread application of simplified modeling techniques for the risk analysis of complex credit derivatives products (CDO’s), due to the lack of computational power and speed, was blamed for the lack of transparency of the real risk embedded in such assets. Quantum systems may provide a completely new approach offering massive data storage and an exponential speed up of computing power. The main thrust of our research effort is to identify which computational finance problems are well suited for specifc quantum devices. This consists of matching critical modeling issues such as improved credit rating methodologies, stochastic volatility modelling, and real time options risk management to appropriate computational finance techniques that are natural fits for the current generation of quantum based tools. Examples of such quantum tools are quantum optimization devices (D Wave), quantum random number generators, and quantum gate computers.

Pure Volatility Instruments

Stochastic volatility models are being investigated for the valuation and risk management of variance swaps and swaptions. Both the OHMC method and a quadrinomial volatility tree method are being used for this investigation.


Selected Publication(s)

H Zhao, R Chatterjee, T Lonon, I Florescu (2018) Pricing Bermudan Variance Swaptions Using Multinomial Trees.

E Alos, R Chatterjee, S Tudor, TH Wang (2018) Target volatility option pricing in lognormal fractional SABR model.

S Tudor, R Chatterjee, I Tydniouk (2018) On a New Parametrization Class of Solvable Diffusion Models and Transition Probability Kernels. To Appear in Quantitative Finance..

R Chatterjee, Z Cui, J Fan, MI Liu (2017) An Efficient and Stable Method for Short Maturity Asian Options. To Appear in Journal Of Futures Markets.

R Chatterjee, T Yu (2017) Generalized Coherent States, Reproducing Kernels, and Quantum Support Vector Machines. Quantum Information & Computation 17 (15&16), 1292.

H Zhao, Z Zhao, R Chatterjee, T Lonon, I Florescu (2017) Pricing Variance, Gamma and Corridor Swaps Using Multinomial Trees. The Journal of Derivatives 25 (2), 7-21.

Chatterjee, R. (2014). Practical Methods of Financial Engineering and Risk Management: Tools for Modern Financial Professionals. Springer-Apress.

Chatterjee, R., & Takhtajan, L. (1996). Aspects of classical and quantum Nambu mechanics. Letters in Mathematical Physics, 37(4), 475-482.

Chatterjee, R. (1996). Dynamical symmetries and Nambu mechanics. Letters in Mathematical Physics, 36(2), 117-126.

Balazs, N. L., Chatterjee, R., & Jackson, A. D. (1995). Coin tossing as a billiard problem. Physical Review E, 52(4), 3608.

Chatterjee, R., Jackson, A. D., & Balazs, N. L. (1996). Rigid-body motion, interacting billiards, and billiards on curved manifolds. Physical Review E, 53(6), 5670. Chicago

Chatterjee, R., & Jackson, A. D. (1996). Surfing Arnold's web. Nuclear Physics A, 606(1), 27-40.

Wang, J., Petrelli, A., Balachandran, R., Siu, O., Zhang, J., Chatterjee, R., & Kapoor, V. (2009). General Auto-Regressive Asset Model. Available at SSRN 1428555.

Petrelli, A., Zhang, J., Siu, O., Chatterjee, R., & Kapoor, V. (2008). Optimal dynamic hedging of cliquets. DefaultRisk. com, May.

Balachandran, R., Siu, O., Chatterjee, R., Jun, Z., & Kapoor, V. (2010). Optimal Dynamic Hedging of Equity Options: Residual-Risks, Transaction-Costs, & Conditioning. SSRN Working Paper Series.

Petrelli, A., Balachandran, R., Zhang, J., Siu, O., Chatterjee, R., & Kapoor, V. (2009). Optimal Dynamic Hedging of Multi-Asset Options. Available at SSRN 1358667.






References



Rupak Chatterjee
Industry Professor in the Department of Physics at the Stevens Institute of Technology;
Email Rupak.Chatterjee@stevens.edu
Phone (201) 216 5099
Office Burchard 709