Personal profile
Research interests
Mathematics & Statistics - Empirical processes
Mathematics & Statistics - Nonstationary time series
Mathematics & Statistics - Nonlinear time series
Mathematics & Statistics - Long memory time series
Related documents
Education/Academic qualification
PhD in Statistics, PhD, The University of Hong Kong
1997
Fingerprint
- 1 Similar Profiles
Collaborations and top research areas from the last five years
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Statistical Inferences of the Heavy-tailed Multivariate ARMA-GARCH Model with Change-point and Threshold Effects
LING, S. (PI)
RGC - Senior Research Fellow Scheme
1/01/23 → 31/12/27
Project: Research
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Self-weighted LADE-based Inference for the Structure-changed and Heavy-tailed ARMA Model with Unspecified ARCH-type Noises
LING, S. (PI)
1/01/23 → 30/06/25
Project: Research
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Simultaneous Testing of Change-points with a Threshold in a General Class of Time Series Models
LING, S. (PI)
1/01/22 → 31/12/24
Project: Research
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Testing and Estimation of Change-points in the Mean of Linear Processes with Heavy-tailed G-GARCH Noises -- A Trimmed LSE Approach
LING, S. (PI)
1/01/21 → 31/12/23
Project: Research
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Statistical Inferences of Heavy-Tailed Vector Error Correction ARMA Models
LING, S. (PI)
1/01/19 → 31/12/21
Project: Research
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Noncausal AR-ARCH Model and Its Applications to Financial Time Series
Zhan, Y., Ling, S., Liu, Z. & Wang, S., Jan 2026, In: International Journal of Finance and Economics. 31, 1, p. 1424-1443 20 p.Research output: Contribution to journal › Journal Article › peer-review
Open Access -
Bootstrap unit root inference for linear processes of possibly heavy-tailed GARCH-type noises
Zhang, R., Sin, C. Y. & Ling, S., 2025, In: Econometric Reviews. 44, 6, p. 715-744 30 p.Research output: Contribution to journal › Journal Article › peer-review
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Modeling bimodal stock price dynamics by a parsimonious diffusion process
Zhan, Y., Ling, S., Liu, Z. & Wang, S., Sept 2025, In: International Review of Financial Analysis. 105, 104367.Research output: Contribution to journal › Journal Article › peer-review
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Neural Network for Partially Linear Time Series Models
Wei, X., Chen, M. & Ling, S., 8 Aug 2025, In: Annals of Financial Economics. 20, 2, 2550014.Research output: Contribution to journal › Journal Article › peer-review
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Statistical Inference for Heavy-tailed and Partially Nonstationary Vector ARMA Models
Guo, F. & Ling, S., 2025, In: Statistica Sinica. v. 35, p. 1-27Research output: Contribution to journal › Journal Article › peer-review
Activities
- 9 Editorial work
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计量经济学报 (Journal)
LING, S. (Associate Editor)
1 Jan 2021 → …Activity: Publication peer-review and editorial work › Editorial work
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Statistica Sinica (Journal)
LING, S. (Associate Editor)
1 Aug 2020 → …Activity: Publication peer-review and editorial work › Editorial work
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Journal of Data Science (Journal)
LING, S. (Associate Editor)
1 Aug 2019 → …Activity: Publication peer-review and editorial work › Editorial work
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Journal of Time Series Analysis}, John Wiley \& Sons Ltd. (Journal)
LING, S. (Co Editor)
1 Jun 2018 → …Activity: Publication peer-review and editorial work › Editorial work
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Journal of Econometrics (Journal)
LING, S. (Other Editorial Role)
1 Aug 2017 → 1 Aug 2019Activity: Publication peer-review and editorial work › Editorial work
Awards
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Selected by the University for recognition at the 4th HKUST Faculty Recognition Ceremony
LING, S. (Recipient), 2022
Prize: Honorary Award
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The World's Top 2\% Most-cited Scientists by Stanford University (2019, 2020, 2021, 2022)
LING, S. (Recipient), 2022
Prize: Honorary Award