Markov Chain Monte Carlo Methods in Financial Econometrics

被引：0
|
作者：
Michael Verhofen
机构：
[1] University of St. Gallen,Swiss Institute of Banking and Finance
来源：
Financial Markets and Portfolio Management | 2005年 / 19卷 / 4期
关键词：
Empirical Evidence; Markov Chain Monte Carlo; Classical Method; Asset Price; Parameter Uncertainty;
D O I：
10.1007/s11408-005-6459-1
中图分类号：
学科分类号：
摘要：
Markov Chain Monte Carlo (MCMC) methods have become very popular in financial econometrics during the last years. MCMC methods are applicable where classical methods fail. In this paper, we give an introduction to MCMC and present recent empirical evidence. Finally, we apply MCMC methods to portfolio choice to account for parameter uncertainty and to incorporate different degrees of belief in an asset pricing model.
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页码：397 / 405
页数：8
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