As we enter the big data era, there is a boom in the development of modern techniques, such as high-dimensional econometrics, approaches for non-Euclidean data structures, and machine learning methods. The research cluster of
Econometrics with Data Science (EwDS) embraces this trend and brings together researchers with expertise in theoretical econometrics, applied econometrics, forecasting, and various data science techniques, including text analysis, indicator saturation, functional data analysis, and vine copula.
The cluster members have published their research in the world-leading academic journals: Annals of Statistics, Journal of Econometrics, Journal of Business and Economic Statistics, European Journal of Operational Research, Journal of Applied Econometrics, Journal of Financial Econometrics, Econometric Review, and International Journal of Forecasting, among others.
Academics at Reading:
Philip Ramirez Hafsa Shoukat
We are a newly established cluster (est. March 2023) and welcome new members (from any department at the University of Reading) whose research involves econometrics and data science. If you are interested in joining us, please contact the cluster coordinator, Shixuan Wang (
Chen, Jian, Clements, Michael P., Urquhart, Andrew, (2023) Modelling price and variance jump clustering using the marked Hawkes process . Journal of Financial Econometrics.
Lazar, Emese, Wang, Shixuan, Xue, Xiaohan, (2023) Loss function-based change point detection in risk measures. European Journal of Operational Research. Xu, Xiu, Wang, Weining, Shin, Yongcheol,
(2022) Zheng, Chaowen, . Journal of Business and Economic Statistics. Dynamic network quantile regression model Chen, Jia, Shin, Yongcheol,
(2022) Zheng, Chaowen, . Journal of Econometrics, 229 (1). pp. 55-79. Estimation and inference in heterogeneous spatial panels with a multifactor error structure Horváth, Lajos, Liu, Zhenya, Rice, Gregory,
Zhan, Yaosong, (2022) Wang, Shixuan, . Journal of Business and Economic Statistics. Testing stability in functional event observations with an application to IPO performance
van der Klaauw, Bas, (2021) Kastoryano, Stephen, . Journal of Applied Econometrics, 37(2). pp. 227-241. Dynamic evaluation of job search assistance Horváth, Lajos, Kokoszka, Piotr,
(2021) Wang, Shixuan, . Annals of Statistics, 49 (4). pp. 2271-2291. Monitoring for a change point in a sequence of distributions Horváth, Lajos, Liu, Zhenya, Rice, Gregory,
(2020) Wang, Shixuan, . Journal of Econometrics, 215 (1). pp. 209-238. Sequential monitoring for changes from stationarity to mild non-stationarity Antoch, Jaromír, Hanousek, Jan, Horváth, Lajos, Hušková, Marie,
(2019) Wang, Shixuan, . Econometric Reviews, 38(7). pp. 828-855. Structural breaks in panel data: large number of panels and short length time series
Syntetos, Aris A., Liu, Ying, Di Cairano-Gilfedder, Carla, Naim, Mohamed M., (2023) Wang, Shixuan, . European Journal of Operational Research, 306 (2). pp. 893-908. Improving automotive garage operations by categorical forecasts using a large number of variables Rostami-Tabar, Bahman, Goltsos, Thanos E.,
(2023) Wang, Shixuan, . Computers in Industry, 145. Forecasting for lead-time period by temporal aggregation: whether to combine and how Angelini, Giovanni, De Angelis, Luca,
(2022) Singleton, Carl, . International Journal of Forecasting, 38 (1). pp. 282-299. Informational efficiency and behaviour within in-play prediction markets Ramirez, Philip,
Reade, J. James, Singleton, Carl, (2022) Betting on a buzz: mispricing and inefficiency in online sportsbooks. International Journal of Forecasting. Brown, Alasdair,
Vaughan Williams, Leighton, (2019) Reade, J. James, . International Journal of Forecasting, 35 (1). pp. 420-428. When are prediction market prices most informative?
Vaughan Williams, Leighton, (2019) Reade, J. James, . International Journal of Forecasting, 35 (1). pp. 336-350. Polls to probabilities: comparing prediction markets and opinion polls
Reade, James, (2022) Wang, Shixuan, . Journal of Regional Science, 62 (4). pp. 1149-1178. Measuring US regional economic uncertainty
Clements, Mike P. , (2020) Reade, James J., . International Journal of Forecasting, 36 (4). pp. 1488-1500. Forecasting and forecast narratives: the Bank of England inflation reports Brown, Alasdair, Rambacussing, Dooruj,
Rossi, Giambattista, (2018) Reade, J. James, . Economic Inquiry, 56 (3). pp. 1748-1763. Forecasting with social media: evidence from Tweets on soccer matches
Apergis, Nicholas, Pan, Wei-Fong,
Reade, James, (2023) Wang, Shixuan, . Energy Economics, 120. Modelling Australian electricity prices using indicator saturation Pretis, Felix,
Sucarrat, Genaro, (2018) Reade, James, Automated General-to-Specific (GETS) regression modeling . Journal of Statistical Software, 86 (3). and indicator saturation methods for the detection of outliers and structural breaks
Functional Data Analysis
Clements, Mike P., & Wang, Shixuan. (2023).
Economics Discussion Paper, University of Reading. Do Professional Forecasters’ Phillips Curves Incorporate the Beliefs of Others? Horváth, Lajos, Kokoszka, Piotr, VanderDoes, Jeremy,
(2022) Wang, Shixuan, . Journal of Time Series Analysis, 43 (6). pp. 872-894. Inference in functional factor models with applications to yield curves Bouri, Elie, Lau, Chi Keung Macro, Saeed, Tareq,
Wang, Shixuan, Zhao, Yuqian, (2021) On the intraday return curves of Bitcoin: predictability and trading opportunities. International Review of Financial Analysis, 76. Horváth, Lajos, Liu, Zhenya, Rice, Gregory,
(2020) Wang, Shixuan, . International Journal of Forecasting, 36 (2). pp. 646-665. A functional time series analysis of forward curves derived from commodity futures
Li, Hemei, Liu, Zhenya,
(2022) Wang, Shixuan, . International Journal of Finance and Economics, 27 (2). pp. 2438-2457. Vines climbing higher: risk management for commodity futures markets using a regular vine copula approach Han, Xuyuan, Liu, Zhenya,
(2022) Wang, Shixuan, . Journal of Commodity Markets, 25. An R-vine copula analysis of non-ferrous metal futures with application in Value-at-Risk forecasting Apergis, Nicholas, Gozgor, Giray, Lau, Chi Keung Marco,
(2020) Wang, Shixuan, Dependence structure in the Australian electricity markets: new evidence from regular vine . Energy Economics, 90. copulae
How to use ChatGPT to facilitate academic research? – Yuhao Mu (Renmin University of China), April 19, 12 noon via Teams. Yuhao’s slides are here. Video recording below:
If you would like to receive information about our future events, please contact the cluster coordinator, Shixuan Wang (
Research Led Teaching