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CRETA Workshop on Advanced Econometrics 15 (20 March 2013)

訊息標題:

CRETA Workshop on Advanced Econometrics 15 (20 March 2013)

簡介摘要:

CRETA Workshop on Advanced Econometrics 15 - 20 March 2013, Heng-Lih Sinology Lecture Hall, B1, Building 1 College of Management, NTU

 

CRETA is honored to invite Professor Wolfgang Härdle from Humboldt-Universität zu Berlin as a visitor on Mar. 20. During his visit, Prof. Härdle will lecture on Yield Curve Modeling and Forecasting using Semiparametric Factor Dynamics and Quantile Regression with high dimensional Single-Index Models on CRETA Workshop on Advanced Econometrics 15. The workshop is due to take place on Mar. 20 (Wed.) at Heng-Lih Sinology Lecture Hall, B1, Building 1 College of Management, NTU (台大管理學院一號館B1國學講堂). All participants are welcomed! Please be sure to register your attendance online by noon, Mar. 18 (Mon.).

*Date: Mar. 20 (Wed.), 2013, 16:00 pm – 17:30 pm
*Venue: Heng-Lih Sinology Lecture Hall, B1, Building 1 College of Management, NTU
(台灣大學管理學院一號館B1國學講堂)
*Topic:
1. Yield Curve Modeling and Forecasting using Semiparametric Factor Dynamics
2. Quantile Regression with high dimensional Single-Index Models

[Regirstration Fee]
台灣大學在學學生及現任教職員和台灣經濟計量學會會員為免費參加
其他參加者報名費為 NT$600
(當天將開放現場繳交台灣經濟計量學會 2013 年年度會費)

[Lecture Overview]
1. Yield Curve Modeling and Forecasting using Semiparametric Factor Dynamics
Using a Dynamic Semiparametric Factor Model (DSFM) we investigate the term structure of interest rates. The proposed methodology is applied to monthly interest rates for four southern European countries: Greece, Italy, Portugal and Spain from the introduction of the Euro to the recent European sovereign-debt crisis. Analyzing this extraordinary period, we compare our approach with the standard market method - dynamic Nelson-Siegel model. Our findings show that two nonparametric factors capture the spatial structure of the yield curve for each of the bond markets separately. We attributed both factors to the slope of the yield curve. For panel term structure data, three nonparametric factors are necessary to explain 95% variation. The estimated factor loadings are unit root processes and reveal high persistency. In comparison with the benchmark model, the DSFM technique shows superior short term forecasting.


2. Quantile Regression with high dimensional Single-Index Models
Quantile regression is in the focus of many estimation techniques and is an important tool in data analysis. When it comes to nonparametric specications of the conditional quantile (or more generally tail) curve one faces, as in mean regression, a dimensionality problem. We propose a projection based single index model specication. For very high dimensional regressors X one faces yet another dimensionality problem and needs to balance precision vs. dimension. Such a balance may be achieved by combining semiparametric ideas with variable selection techniques

講者介紹:

Professor Härdle is currently Ladislaus von Bortkiewicz chair professor of statistics at the School of Business and Economics, Humboldt-Universität zu Berlin and also the director of C.A.S.E. – Center for Applied Statistics & Economics. Professor Härdle’s research interests focus on the dimension reduction techniques, computational statistics and quantitative finance. His research articles have been published in several prestigious journals, such as Journal of the American Statistical Association, Journal of Econometrics, Journal of Financial Econometrics, Journal of Empirical Finance, Journal of Forecasting, Journal of Risk and Insurance and Quantitative Finance.