Fin-X Lab
Finance ✖️ Big Data ✖️ Statistical Learning
Fin-X Lab
Finance ✖️ Big Data ✖️ Statistical Learning
News
The Fin‑X Lab invites applications for PhD students, Research Assistants (RA), and Postdoctoral researchers. Candidates with strong quantitative backgrounds, high self‑motivation, and keen interests in research on financial big data, statistical theory and methodology, and data‑driven learning and applications in business are encouraged to apply. Please send your CV to yiding@um.edu.mo
Financial econometrics; High-dimensional statistics; Financial technology; Statistical learning; Portfolio optimization; Asset allocation; High-frequency financial data
Area 1: High-dimensional volatility models and statistical theory
Ding, Yi and Engle, Robert and Li, Yingying and Zheng, Xinghua, “Multiplicative factor model for volatility”, Journal of Econometrics, 2025, 105959
Ding, Yi and Zheng, Xinghua, “High-dimensional covariance matrices under dynamic volatility models: asymptotics and shrinkage estimation”, The Annals of Statistics, 2024, Vol. 52, No. 3, 1027104
Area 2: High-dimensional portfolio optimization
Ding, Yi and Li, Yingying and Zheng, Xinghua, “High dimensional minimum variance portfolio under statistical factor model” (2021), Journal of Econometrics, 2021, 222(1): 502-515.
Ding, Yi and Li, Yingying and Song, Rui, “Statistical learning for individualized asset allocation”, Journal of the American Statistical Association, 2022: 1-11.
Area 3: High-dimensional tail risk and factor modeling
Ding, Yi and Li, Yingying and Liu, Guoli and Zheng, Xinghua, “Stock co-jump networks”, Journal of Econometrics, 2024, 239(2): 105420.
Andersen, Torben and Ding, Yi and Todorov, Viktor and Yu, Seunghyeon, “The Factor Structure of Jump Risk”, Journal of Econometrics, 2026, 106215
Chang, Jinyuan and Ding, Yi and Shi, Zhentao and Zhang, Bo, “Zero Variance Portfolio” (2025), under review
Andersen, Torben and Ding, Yi and Todorov, Viktor, “The Granular Origin of Tail Dispersion Risk” (2025), under review
Andersen, Torben and Ding, Yi and Todorov, Viktor, “Tails of Cross-Sectional Return Distributions at High Frequencies” (2025), under review
Ding, Yi and Zheng, Xinghua, “High-Dimensional Covariance Matrix Estimation under Elliptical Factor Model with 2 + εth Moment” (2025), under review
Chen, Zhanhui and Ding, Yi and Li, Yingying and Zheng, Xinghua, “Cross-Sectional Learning and Inference for the Stochastic Discount Factor” (2025), under review
Ding, Yi and Xu, Yumin and Zhang, Ruixun, “Liquidity Jump Networks” (2025), working paper
Ding, Yi and Shi, Songze1, “A Fine Lens on Common Trading Flows” (2025), work in progress
Ding, Yi and Li, Yingying and Hu, Shiman and Zheng, Xinghua, “Predictive Factor Model for Jump Intensities” (2025), work in progress