Ren Yuexuan

Professor Jia LI
Email: jiali@smu.edu.sg
Tel: +65 68280707

Professor Yichong Zhang
Email: yczhang@smu.edu.sg
Tel: +65 68280881

Professor Peter C.B. Phillips
Email: peterphillips@smu.edu.sg
Tel: +65 68280865

Professor Jun Yu
Email: junyu@um.edu.mo
Tel: +853 8822-4716

WORKING PAPERS

"Conformal Prediction for High-Frequency Event Studies" (Job Market Paper)

We propose using a conformal predictive analysis for high-frequency event studies. Unlike existing literature, we recast the inference problem of cumulative abnormal return (CAR) as a counterfactual prediction problem for cumulative return. The general continuous-time model for spot regression can be approximated by a linear regression model with independent and stable-distributed random variables under the fixed-k asymptotic setting, thereby establishing the asymptotic validity of the conformal prediction interval. Extending the theory to incorporate a counterfactual model with many control units, the proposed prediction interval remains valid when using the synthetic control estimator. An intraday event study of AMD’s conference session illustrates the empirical application.

RESEARCH PAPERS

"Robust Inference for Spot Regressions", with Tim Bollerslev, Jia Li and Ulrich Müller.

“A Robust test of Tracking Performance for Leveraged ETFs”, with Tim Bollerslev, Jia Li and Ulrich Müller

PUBLICATION

"Optimal Inference for Spot Regressions.", with Tim Bollerslev, Jia Li, and Yuexuan Ren, American Economic Review, 114 (3): 678-708, 2024