dachuanchen

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Dachuan Chen

Assistant Professor

School of Statistics and Data Science

Nankai University

Email: dachuan.chen.us@gmail.com

This page is updated in October 2023.

General Background

I joined the School of Statistics and Data Science of Nankai University at December 2019. I received my Ph.D. degree in Business Administration at University of Illinois at Chicago at May 2019. My dissertation advisors are Professor Lan Zhang (from UIC) and Professor Per Mykland (from University of Chicago). I received my B.S. degree in Statistics from Nankai University, Tianjin, P.R. China, in 2012. I was a Ph.D. student in the Computer Science and Information System Program at University of Colorado at Denver from 2012 to 2014. I was an exchange scholar at Department of Statistics, University of Chicago from 2015 to 2016. I received the Stevanovich Student Fellowship for 2018 from the Stevanovich Center for Financial Mathematics, University of Chicago.

Research Interests

Financial Econometrics, High Frequency Econometrics, High Dimensional Statistics

Academic Appointments

  1. Dec 2019 - present: Nankai University, School of Statistics and Data Science, Assistant Professor;

  2. Sept 2023 - present: The Hong Kong University of Science and Technology, Department of Information System, Business Statistics and Operations Management, Visiting Scholar.

Publications

  1. Chen, D. (2024). High Frequency Principal Component Analysis based on Correlation Matrix that is Robust to Jumps, Microstructure Noise and Asynchronous Observation Times. Forthcoming in Journal of Econometrics.

  2. Chen, D., Song, F. and Feng, L. (2023). Rank Based Tests for High Dimensional White Noise. Forthcoming in Statistica Sinica.

  3. Chen, D., Li, C., Tang, C.Y. and Yan, J. (2023). The Leverage Effect Puzzle under Semi-nonparametric Stochastic Volatility Models. Forthcoming in Journal of Business & Economic Statistics.

  4. Chen, D., Mykland, P.A. and Zhang, L. (2023). Realized Regression with Asynchronous and Noisy High Frequency and High Dimensional Data. Forthcoming in Journal of Econometrics.

  5. Chen, D., Mykland, P.A., and Zhang, L. (2020). The Five Trolls under the Bridge: Principal Component Analysis with Asynchronous and Noisy High Frequency Data. Journal of The American Statistical Association, 115(532), 1960-1977.

  6. Mykland, P.A., Zhang, L., and Chen, D. (2019). The Algebra of Two Scales Estimation, and the S-TSRV: High Frequency Estimation that is Robust to Sampling Times. Journal of Econometrics, 208(1), 101-119.

  7. Li, C., and Chen, D. (2016). Estimating jump-diffusions using closed-form likelihood expansions. Journal of Econometrics, 195(1), 51-70.

  8. Li, C., An, Y., Chen, D., Lin, Q., and Si, N. (2016). Efficient computation of the likelihood expansions for diffusion models. IISE Transactions, 48(12), 1156-1171. (IISE Transactions Operations Engineering and Analytics Best Paper Award, The Institute of Industrial and Systems Engineers, 2018.)

  9. Backues, S. K., Chen, D., Ruan, J., Xie, Z., and Klionsky, D. J. (2014). Estimating the size and number of autophagic bodies by electron microscopy. Autophagy, 10(1), 155-164.

Working Papers

  1. Chen, D., Feng, L., Mykland, P.A. and Zhang, L., 2023. High Dimensional Regression Coefficient Test with High Frequency Data. Available at SSRN 4139323. In revision.

  2. Chen, D. and Feng, L. 2023. Change Point Detection in Beta Process with High Frequency Data. Available at SSRN 4398513.

  3. Chen, D., Chen, H., Feng, L. and Xie, S. 2023. High Frequency ANOVA that is Robust to Jumps, Microstructure Noise and Asynchronous Observation Times. Available at SSRN 4420129. In revision.

  4. Chen, D. and Xie, S. 2023. High Frequency Factor Analysis with Partially Observable Factors. Available at SSRN 4539005. In revision.

  5. Chen, D., Li, Y. and Wang, C.D. 2023. Estimating Leverage Effect and Volatility of Volatility in the Presence of Jumps, Microstructure Noise and Irregular Observation Times. Available at SSRN 4625351.

[Dachuan's Webpage at Stevanovich Center of Financial Mathematics, University of Chicago]