Personal Profile

Qiushi Zhang holds a Ph.D. in Economics from Duke University and is an Associate Professor at the Shenzhen Audencia Financial Technology Institute, Shenzhen University. Research focuses on econometrics, financial economics, high-frequency financial data, and financial derivatives, with publications in leading international journals including the Review of Economics and Statistics. Prior to joining Shenzhen University, Dr. Zhang served as Associate Professor at the China School of Banking and Finance, University of International Business and Economics, and as Deputy Director of the Master of Quantitative Finance Program. Dr. Zhang serves as a referee for the Journal of Business & Economic Statistics and the Journal of Financial Econometrics.

Education Experience

2021　Ph.D. in Economics, Duke University

2017　B.A. in Economics (Honors) and Mathematics (Honors), New York University

Work Experience

2026.8 – Present: Associate Professor, Shenzhen Audencia Financial Technology Institute & Webank Institute of Fintech, Shenzhen University

2023.1–2026.7　Associate Professor, China School of Banking and Finance, University of International Business and Economics

2024.6–2026.7　Deputy Director, Master of Quantitative Finance Program, University of International Business and Economics

2021.8–2022.12　Assistant Professor, China School of Banking and Finance, University of International Business and Economics

Research Interests

Econometrics; Financial Economics; High-Frequency Financial Data; Financial Derivatives.

Publications

Journal Articles (Published)

[1] Li, J., Todorov, V., & Zhang, Q. (2024). Testing the Dimensionality of Policy Shocks. Review of Economics and Statistics, 106(2), 470–482.

[2] Li, J., Wang, D., & Zhang, Q. (2024). Reading the Candlesticks: An OK Estimator for Volatility. Review of Economics and Statistics, 106(4), 1114–1128.

Working Papers

[3] Bollerslev, T., Li, J., Li, Y., & Zhang, Q. Illuminating Important Economic News by Candlesticks: Optimal Testing Meets Technical Analysis. Revise and Resubmit.

Book Chapters

[4] Greene, W., & Zhang, Q. (2019). Nonlinear and Related Panel Data Models. In M. Tsionas (Ed.), Panel Data Econometrics. Academic Press.

Courses Taught

Undergraduate:

· Numerical Computing (Bilingual, Quantitative Finance Experimental Class)

· Time Series Analysis (Bilingual, Quantitative Finance Experimental Class)

· Quantitative Finance Seminar

Graduate:

· Advanced Time Series Analysis (Master's and PhD)

· Applied Data Analysis (Master's)

· Frontier Theories and Research Methods in Financial Engineering (PhD)

Academic Service

Referee: Journal of Business & Economic Statistics; Journal of Financial Econometrics.