Average quantile regression and new coherent risk measures

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• Keming Yu (Brunel University)
• Tuesday 06 May 2025, 14:30-15:00
• Seminar Room 1, Newton Institute.

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RCLW01 - Uncertainty in multivariate, non-Euclidean, and functional spaces: theory and practice

This talk introduces the innovative concept of Average Quantile Regression (AQR), which  not only applies to regression model  beyond mean but also serves as a coherent risk measure. Many traditional  regression models beyond mean and risk measures can be viewed as special cases of AQR . As a flexibly non-parametric regression model, AQR demonstrates outstanding performance in handling high-dimensional and large datasets, particularly those generated by distributed systems, offering a convenient framework for their statistical analysis. We derive the corresponding estimators and develop their asymptotic properties. Simulations and real data analyses are conducted to illustrate the finite-sample performance of the proposed methods.

This talk is part of the Isaac Newton Institute Seminar Series series.

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