• Archivio mensile:settembre 2016

    Seminario Ruey Tsay

    Il giorno 4 ottobre alle ore 11.30 presso la Sala del Consiglio della Scuola di Economia e Statistica, al IV piano dell’edificio U7, il prof. Ruey Tsay della University of Chicago Booth School of Business, terrà un seminario su:

    Nonlinear Models for High-Frequency Financial Data

    Abstract

    Nonlinearity is commonly observed in high-frequency data, including financial data. We discuss some recent developments in econometric modeling of nonlinear high-frequency financial data. We discuss both parametric and nonparametric methods, approaches for handling count data, and statistical methods for analyzing big dependent data. Real examples are used to demonstrate the analysis and to compare different methods.

    Tutti gli interessati sono invitati a partecipare. Per ulteriori informazioni:
    ilaria.foroni@unimib.it
    mariangela.zenga@unimib.it.

    Seminario Masanobu Taniguchi

    Il giorno martedì 4 ottobre alle ore 15.00 presso la Aula Seminari al IV piano dell’edificio U7,  il prof. Masanobu Taniguchi della Waseda University di Tokyo terrà un seminario su

    High Order Asymptotic Theory of Shrinkage Estimation for General Statistical Models

    Abstract
    In this paper we develop the high order asymptotic theory of shrinkage estimators for general statistical models, which include dependent processes, multivariate models and regression models, i.e., non-i.i.d. models.
    Introducing a shrinkage estimator of MLE, we compare it with that of MLE by third-order mean squares error (MSE).
    A sufficient condition for the shrinkage estimator to improve the MLE will be given in a very general fashion.
    Our model is described as a curved statistical model p(·;\theta(u)), where \theta is a parameter of larger model and u is a parameter of interest with dim u < dim \theta.
    This setting is especially suitable for estimation of portfolio coefficients u based on mean and variance parameters \theta.
    We also mention the advantage of our shrinkage estimators when the dimension of parameter becomes large.
    Numerical studies are given, and illuminate an interesting feature of the shrinkage estimator. (joint work with: Hiroshi SHIRAISHI, Yoshihiro SUTO, Takashi YAMASHITA)