报告题目:Modeling Seasonality and Serial Dependence of Electricity Price Curves with Warping Functional Autoregressive Dynamics
报告人：张洁洁博士
报告时间：下午1：30
报告地点：理A110
报告题目: Modeling Seasonality and Serial Dependence of Electricity Price Curves with Warping Functional Autoregressive Dynamics
报告时间：11月28日（周二）下午1：30
报告地点：理A110
报告人：张洁洁博士（新加坡国立大学）
摘要:
Electricity prices are high dimensional, serially dependent and have seasonal variations. We propose a Warping Functional AutoRegressive (WFAR) model that simultaneously accounts for the cross time-dependence and seasonal variations of the large dimensional data. In particular, electricity price curves are obtained by smoothing over the 24 discrete hourly prices on each day. In the functional domain, seasonal phase variations are separated from level amplitude changes in a warping process with the Fisher-Rao distance metric and the aligned (season-adjusted) electricity price curves are modeled in the functional autoregression framework. In real application in both the California power market and the Nord Pool power market, the WFAR model provides superior out-of-sample forecasts with forecast error reduced significantly compared to several alternative models.
报告人简介： 张洁洁博士于2014年本科毕业于武汉大学数学与统计学院，同年获得新加坡政府全额奖学金资助的直博研究生资格，前往新加坡国立大学统计与应用概率系开始博士学习，师从Chen Ying教授。研究方向包括Functional Data Analysis, Network Analytics, Time Warping, Bitcoin Analysis和Time Series Analysis。