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A Bayesian Nonparametric Approach on Model Combination for Short-term Interest Rates

来源:湖南大学经济与管理研究中心 日期:2018-05-14 作者:

间:May 18th (Friday), 12:30-14:00PM

点:Room 213, Shuishang Teaching Building

题:A Bayesian Nonparametric Approach on Model Combination for Short-term Interest Rates

主讲人: Qiao Yang

Assistant Professor, Shanghai Tech University

要:The dynamics of short-term interest rates are important input into pricing models of the term structure of interest rates. Most works have focused on adding extra components into the model for improving forecast accuracy such as Maheu & Yang (2016) does. In this paper, our approach takes another direction which uses the model combination framework to improves the forecast performance. We extend Waggoner & Zha (2012) into infinite dimension on combine popular discrete time short-rate models. Our new approach shows significant improvement in density forecasts to existing approaches.

Key words: Beam sampling, Markov switching, density forecast, short-term interest rates

报告人简介:

Dr. Qiao Yang is an Assistant Professor in Shanghai Tech University. He obtained the Ph.D. in Economics at University of Toronto in 2016, and was a Bachelor of Arts Honours, Economics, with Distinction, Queen’s University. His research expertise focuses on Financial Econometrics, Bayesian Econometrics and Time Series. His research An Infinite Hidden Markov Model for Short-term Interest Rates with J. Maheu has been published in Journal of Empirical Finance. His current research has been supported by Shanghai Tech University Start-up Funding.

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