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WU Qi (吴琦)

Columbia University, Ph.D., Applied Mathematics

Assistant Professor, School of Data Science

PI, CityU - JD Digits Joint Laboratory in Financial Technology and Engineering

Contact Information

Office: P6618 Yeung Kin Man Academic Building
Phone: 34427018
Email: qiwu55@cityu.edu.hk

Research Interests

  • Quantitative Finance
  • Machine Learning
  • Business Analytics
  • Financial Engineering
Qi WU is a quantitative finance researcher and an assistant professor at City University of Hong Kong. Previously, he was an assistant professor at Chinese University of Hong Kong, and worked at Lehman Brothers, UBS, and DTCC. He received a B.S. in EE from Wuhan University and a M.S. in Physical Electronics from Peking University.

Qi WU is currently working on machine learning approach to financial risk management, term structure modelling in low interest rate environment, incentive analysis in matching and sharing platforms. His earlier academic work include pricing fixed income securities, modelling of volatility and financial tail risk.

His past industrial experience includes developing pricing models for correlation exposure between sovereign credit risk and currency risk; managing portfolios consisting of vanilla swaptions and callable exotics in a market-making capacity; as well as methodology team lead of fixed income analytics for central clearing of USD cash securities and lightly structured debt instruments at the world largest clearing house. Most recently, he engages with leading global fintech companies on developing data-driven financial services.


Previous Experience

  • 2013 - 2018, The Chinese University of Hong Kong, Dept. of SEEM, Assistant Professor, Hong Kong.
  • 2012 - 2013, The Depository Trust & Clearing Corp., Division of Financial Engineering, Senior Quantitative Analyst, New York.
  • 2010 - 2012, UBS Investment Bank, Fixed Income Division, USD Non-Linear Rates and Structured Rates Desk, Associate Director, Stamford CT.
  • 2008, Lehman Brothers, Fixed Income Division, Quantitative Credit Research Group, Associate, London.


Research Grant

  • 2014-17 Early Career Scheme (HKRGC), $656737, "Low-dimensional Modeling of Collateralized Term Structure with Non-Gaussian Dynamics for Centrally-cleared Interest Rate Swaptions", sole-PI.
  • 2016-19 GRF (HKRGC), $482605, "Asymptotic Analysis of Portfolio Tail Risk and the Diversification Effect under Multivariate Elliptical Distributions for Static Portfolios", Co-I with H. SUN, Bank of New York Mellon.
  • 2017-20 GRF (HKRGC), $582000, "Studies on Margin Procyclicality - the Impact of Volatility Persistence and Nonlinear Payoffs", sole-PI.


Publication Show All Publications Show Prominent Publications


Journal

  • Glasserman, Paul. & Wu, Qi. (2018). Persistence and Procyclicality in Margin Requirements. Management Science.
  • Glasserman, Paul. & WU, Qi. (2011). Forward and Future Implied Volatility. International Journal of Theoretical and Applied Finance.
  • WU, Qi. (2010). Series Expansion of the SABR Joint Density. Mathematical Finance.

Conference Paper

  • Wu, Qi. & Yan, Xing, et.al. (2018). Parsimonious Quantile Regression of Asymmetrically Heavy-tailed Financial Return Series. NIPS 2018.

Book Chapter

  • Glasserman, Paul. & WU, Qi. (in press). Chapter 14. Procyclicality of margin requirements. Risk Book: Margin in Derivatives Trading: Impact on Counterparty Risk, Funding and Liquidity.


Work in progress

  • "Efficient Subsidies via Supply Re-usability", 2017

    "Asymptotics of Portfolio Tail Risk Metrics for Elliptically Distributed Asset Returns", 2016.

    "A Dual-curve Short Rate Model with Multi-factor Stochastic Volatility", 2015.

    "The Hidden Role of Interest Rate Risks in Carry Trade Return", 2014



Last update date : 14 Feb 2019