报告人

Prof. Ostap Okhrin; Dr. Iryna Okhrin

报告题目

Prof. Ostap Okhrin: On the structure and estimation of hierarchical Archimedean copulas

Dr. Iryna Okhrin: Online Surveillance of Volatility Forecasting Models

地点

明商 0105

报告一：On the structure and estimation of hierarchical Archimedean copulas

Abstract: In this paper we provide a methodology for estimating multivariate distributions defined through hierarchical Archimedean copulas. In general the true structure of the hierarchy is unknown. We develop a computationally efficient technique for grouping the data. For this purpose we introduce a hierarchical estimation procedure of the parameters and provide their asymptotic analysis. We consider both parametric and nonparametric estimation of the marginal distributions. The simulation study shows the effectiveness of the grouping procedure in the sense of structure selection. The methodology turns out to be very useful in order to model the distribution of asset returns in practical applications.

报告二：Online" Surveillance of Volatility Forecasting Models

Abstract: A valid statistical model is crucial for proper volatility forecasting. This paper suggests a sequential procedure for monitoring validity of the actual volatility model. A simple state space representation serves for reflecting dynamics of the actual volatility, whereas realized volatility or bipower variation measures refer to the observation equation. Monitoring the stochastic behavior of the resulting forecasting errors allows to decide whether the chosen representation remains correctly specified. A signal indicates that the assumed volatility model may be no more valid. Our approach is illustrated by an empirical study based on selected U.S. market stocks.