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Statistics in finance

✍ Scribed by Ruey S. Tsay


Publisher
Wiley (John Wiley & Sons)
Year
2011
Tongue
English
Weight
686 KB
Volume
3
Category
Article
ISSN
0163-1829

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✦ Synopsis


Abstract

This article considers Markov chain simulation and statistical analysis of high‐dimensional financial time series. In particular, we discuss Markov chain Monte Carlo methods, for example, Gibbs sampling and Metropolis‐Hasting algorithm, and multivariate volatility models with applications in finance. Real examples are used to demonstrate statistical applications of the methods discussed in risk management and volatility estimation. WIREs Comp Stat 2011 3 289–315 DOI: 10.1002/wics.168

This article is categorized under:

Applications of Computational Statistics > Computational Finance


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