Bei proposes a set of computationally efficient methods based on approximating/representing nonlinear processes by linear ones. Initially, a linearization method is introduced for estimating the multiple frequencies in sinusoidal processes utilizing a regularized autoregressive (RAR) approximation. Secondly, a sieve bootstrap scheme is proposed using the linear representation of generalized autoregressive conditional heteroscedastic (GARCH) models to construct prediction intervals for the returns and volatilities. This method is simple, fast and distribution-free, while providing sharp and well-calibrated prediction intervals. Thirdly, a robust Lagrange multiplier (LM) test is considered for detecting GARCH effects. This test utilizes either the bootstrap or permutation procedure to obtain critical values. Intensive numerical studies indicate that the proposed re- sampling algorithms significantly improve the size and power of the LM test in both skewed and heavy-tailed processes. Finally, a nonparametric trend test is introduced in the presence of GARCH effects. Empirical evidence indicates that the test can effectively detect non-monotonic trends under GARCH, especially in the presence of irregular seasonal components.

Bei Chen was born in Suzhou (Jiangsu) and raised in Shanghai, China. She received her BMath in Statistics and Actuarial Science and her MMath in Statistics from the University of Waterloo, where she also completed and defended her PhD thesis. In September 2011, Bei started a position as an Assistant Professor in the Department of Mathematics and Statistics at McMaster University. Her research interests are in time series analysis, financial econometrics and re-sampling methods for dependent data.

The criteria used in selecting the winner of the Pierre Robillard Award include the originality of ideas and techniques, the possible applications and their treatment, and the potential impact of the work. The award is named in memory of Professor Pierre Robillard, an outstanding dynamic young statistician at the Université de Montréal, whose untimely death in 1975 cut short what promised to be a highly distinguished career.

Bei Chen presented the results of her thesis in a special session at the 40th Annual Meeting of the Statistical Society of Canada held in Guelph, Ontario, June 3 to 6, 2012.