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Oct. 30 | Predicting Returns with Text Data

Time:‍Oct. 30(Friday), 8:30-10:00Venue:Zoom Conference ID:635 4317 6839Speaker:Dacheng Xu, Professor ofEconometrics and Statistics at the University of Chicago Booth School of BusinessSummary:We introduce a new text-mining methodology that extracts information from news articles to predict asset returns. Unlike more common sentiment scores used for stock return prediction (e.g., those sold by commercial vendors or built with dictionary-based methods), our supervised learning framework constructs[Detail]
Oct. 26 | Deep Optimal Transport and Generative Learning

Professor Huang’s current research interests include high-dimensional statistics, bioinformatics, and statistical machine learning. Professor Huang has made contributions through innovative research and development of methods and algorithms to the areas of high-dimensional statistics, computational statistics, statistical genetics and genomics, semiparametric models, and survival. Many of his publications appeared in top-ranked journals, including Annals of Statistics, Bioinformatics, Biometrics[Detail]
Sept. 29 | Testing Community Structure for Hypergraphs

Yang Feng is an associate professor of biostatistics in the School of Global Public Health at New York University. Feng focuses on develop[Detail]
Sept. 23 | Information Based Complexity for High Dimensional Statistical Models

Ming Yuan is a professor of Statistics at Columbia University. He was previously senior investigator in Virology at Morgridge Institute for Research and professor of Statistics at University of Wisconsin at Madison, and prior to that Coca-Cola Junior Professor of Industrial and Systems Engineering at Ge[Detail]
Sept. 1 | Weak Separability Test for Spatial Functional Fields

Yao Fang, professor of Peking University, director of Peking University Statistical Science Center, and the fellow of Institute of Mathematical Statistics (IMS) and the American Statistical Association (ASA). He graduated[Detail]

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