Professor Shixuan Wang

Professor Shixuan Wang
  • Co-Research Division Leader, Economics Division
  • Associate Editor, Journal of Time Series Analysis
  • Associate Editor, International Journal of Finance & Economics

Areas of interest

  • Change-Point (Structural Break) Detection
  • Functional Data Analysis
  • Statistical Forecasting
  • Risk Management
  • Explainable AI and Machine Learning
  • Healthcare Analytics

Postgraduate supervision

I welcome PhD applications in the area of functional data analysis in finance. Further details can be found on FindAPhD .

My former PhD students (and their current positions) include:

  • Wei-Fong Pan (Associate Professor at Xiamen University)
  • Xiaohan Xue (Assistant Professor at the University of Bath)
  • Jingqi Pan (QIS Structurer at Société Générale)
  • Michael Kunkler (Senior Developer at Xenomorph)

 

Background

I am a Full Professor of Economics at the University of Reading (since 2025), having initially worked as a Lecturer and subsequently an Associate Professor. Before joining Reading in 2018, I was a postdoctoral researcher in statistical forecasting at Cardiff University. I received my PhD from the University of Birmingham in 2017 and was awarded a Royal Economic Society (RES) Junior Fellowship in 2016.

My primary research focuses on econometric methods for change-point detection and functional data analysis, and their interactions with statistical forecasting. I also have an active research interest in using explainable AI and machine learning for healthcare analytics and operations management. My work has been published in leading journals including Annals of Statistics, Journal of Econometrics, Econometric Theory, and Journal of Business & Economic Statistics.

In addition to my research, I am actively engaged in academic leadership and external collaboration. I currently serve as an Associate Editor of Journal of Time Series Analysis and International Journal of Finance & Economics, organise the Forecasting for Social Good (F4SG) research grant, and coordinate the Econometrics with Data Science (EwDS) research cluster. I have collaborated closely with external partners including the NHS and BT. An AI forecasting tool our team developed with the Royal Berkshire NHS Foundation Trust won The AIconics AI Enterprise Business of the Year at The National AI Awards 2026 (research story), and our earlier AI solution for BT was a finalist for AI Business of the Year at The National AI Awards 2024 (research story).
 

Academic qualifications

I hold a PhD in Economics, a MSc (distinction) in Money, Banking and Finance, a BSc in Economics, and a BEng in Electrical Engineering and Automation. I am also a Fellow of the Higher Education Academy.

Websites/blogs

Selected publications

  1. Wang, S., Syntetos, A. A., Flapper, S. D. P., Di Cairano-Gilfedder, C., and Naim, M. M. (2026). Maintenance schedules by conditional inference trees. European Journal of Operational Research. doi:10.1016/j.ejor.2026.08.022.
  2. Horváth, L. and Wang, S. (2026). Detecting changes in GARCH(1,1) processes without assuming stationarity. Econometric Theory, 42(4), 996-1033.
  3. Horváth, L., Lazar, E., Liu, Z., Wang, S., and Xue, X. (2026). Sequential monitoring for changes in dynamic semiparametric risk models. Journal of Business & Economic Statistics, 44(2), 482-496.
  4. Lazar, E., Wang, S., and Xue, X. (2023). Loss function-based change point detection in risk measures. European Journal of Operational Research, 310(1), 415-431.
  5. Horváth, L., Liu, Z., Rice, G., Wang, S., and Zhan, Y. (2023). Testing stability in functional event observations with an application to IPO performance. Journal of Business & Economic Statistics, 41(4), 1262-1273.
  6. Wang, S., Syntetos, A. A., Liu, Y., Di Cairano-Gilfedder, C., and Naim, M. M. (2023). Improving automotive garage operations by categorical forecasts using a large number of variables. European Journal of Operational Research, 306(2), 893-908.
  7. Horváth, L., Kokoszka, P., and Wang, S. (2021). Monitoring for a change point in a sequence of distributions. Annals of Statistics, 49(4), 2271-2291.
  8. Horváth, L., Liu, Z., Rice, G., and Wang, S. (2020). Sequential monitoring for changes from stationarity to mild non-stationarity. Journal of Econometrics, 215(1), 209-238.

Publications

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