Dynamic Change Detection with Application to Skilled Funds Selection
Date: Thursday, 8 September 2022
Time: 4:00 - 5:00 pm
Speaker: Dr Lilun Du (Hong Kong University of Science and Technology)
Nowadays, data often arrive in large-scale streams, making timely and accurate decision necessary. It has become important to rapidly and sequentially identify individual stream whose behavior deviates from the norm in the framework of false discovery rate control. By fully exploiting the sequential feature of data streams, we introduce a distribution-free procedure which imposes minimum requirement on the knowledge of streaming observations. The idea is to combine an order-preserved sample-splitting strategy with exponentially weighted moving average approach to construct a series of statistics with marginal symmetry property, and then to utilize the symmetry property for obtaining a data-driven threshold. Finite-sample and asymptotic results on the false discovery rate control will be discussed. Another feature of this procedure is that it can conveniently incorporate side-information. Numerical experiments indicate that the proposed method is both accurate and powerful. For illustration, we apply the new method to selecting skilled funds in the financial market.
Bio: Dr. Lilun DU is currently an assistant professor of department of Information Systems, Business Statistics and Operations Management at Hong Kong University of Science and Technology. He received his PhD in Statistics from University of Wisconsin-Madison in Year 2015. He has broad research interests in multiple hypotheses testing, empirical Bayes method, and streaming data analytics. Dr. DU also works in Operation Analytics and has derived data-driven tools for solving problems in high-volume recruitment. His work has been published in Annals of Statistics, Journal of American Statistical Association, Manufacturing & Services Operations Management, and Operations Research.
Zoom Link: Please contact Yanrong Yang (yanrong.yang@anu.edu.au) to obtain the zoom link for this seminar.