Jiajing Sun

My methodological work centres on time-series econometrics, including the Adjusted-Range Self-Normalisation framework for robust inference on long-run variances under strong dependence and heavy tails — alongside functional time series and self-normalised monitoring.

On the applied side, my work spans financial risk, digital finance, environmental management, and ecological economics. This includes regulatory early-warning research for derivatives markets, text- and machine-learning-based evaluation of financial-technology competitiveness, and virtual water in global supply chains.

I present regularly at international meetings in econometrics and statistics — among them the World, European, Asian, North American, and Australian meetings of the Econometric Society, SoFiE, and CMStatistics — and at invited university seminars. Slides are shared where I can.

I teach postgraduate courses in financial econometrics, advanced time series, regression, and quantitative finance, and write textbooks that connect statistical theory with empirical application and reproducible code in R and Python.