半参数金融时间序列模型专题讲座

1. 题目：Several semiparametric GARCH models and their application to decomposing financial risk

时间：2013年9月12日，15:00-16:00

地点：邵逸夫科学馆513

2. 题目：Semiparametric ACD and related models for analyzing high-frequency financial data

时间：2013年9月13日，19:00-20:00

地点：邵逸夫科学馆513

3. 题目：Semiparametric long-memory financial time series models

时间：2013年9月17日，9：00-10：00

地点：邵逸夫科学馆513

学术讲座

题目：Data-driven estimation of realized volatility under independent microstructure noise

时间：2013年9月24日，9:00-10:00

地点：邵逸夫科学馆513

Abstract:

One of the most important concepts in financial econometrics and financial mathematics introduced in the last two decades is the realized volatility (RV), which is a model-free estimator of the daily integrated volatility (IV) based on high-frequency financial data. RV can be estimated in some simple ways. However, it is found that, if the data exhibit microstructure noise (MN), most of the simple definitions of RV are now inconsistent estimators of the IV. Different proposals are introduced to solve this problem. Most recently, Barndorf-Nielsen et sal. (2008, 2009 and 2011) introduced the realized kernels (RK), which are consistent estimates of the IV under give conditions. A crucial point to calculate the RV is the selection of the bandwidth. Our purpose is to propose an iterative plug-in algorithm for selecting the bandwidth for RK under the assumption that the MN are i.i.d. It is shown that the proposed algorithm is a fix-point search method and runs very quickly. To our knowledge this proposal is the first fully data-driven algorithm for selecting the bandwidth for RK. The nice properties of the proposed bandwidth selector are indicated by asymptotic results and application to high-frequency data of a few German and French firms within a period of several years.