Dual-time Modeling and Forecasting in Consumer Banking

摘 要：Longitudinal and survival data are naturally observed with multiple origination dates. They form a dual-time data structure with horizontal axis representing the calendar time and the vertical axis representing the lifetime. In this talk we discuss the age-period-cohort and dual-time factor models, as well as the forecasting techniques over time horizon. Among other fields, we share the potential applications in consumer banking, and demonstrate a large-scale credit risk analysis powered by big data computing.
个人简介：Dr. Aijun Zhang is the director of Center for Big Data in Education at Hong Kong Baptist University. He received PhD in Statistics from University of Michigan at Ann Arbor in 2009. He has more than five years of industrial experience in Bank of America Merrill Lynch, working on lots of quantitative risk management problems. Dr. Zhang's research interests include big data analytics, machine learning and experimental designs.