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Estimating time-varying variances and covariances via nearest neighbour multivariate predictions : applications to the NYSE and the Madrid Stock Exchange Index

[journal article]

Acosta-González, Eduardo; Fernández-Rodríguez, Fernando; Andrada-Félix, Julián

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Please use the following Persistent Identifier (PID) to cite this document:http://nbn-resolving.de/urn:nbn:de:0168-ssoar-241225

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Abstract In this paper we present a technique to obtain the time-varying covariance matrix for several time series for nearest neighbour predictors. To illustrate the use of this technique, we analyse the time-varying variances and correlations between the daily returns on two equity stock market indexes, the New York Stock Exchange (NYSE) and the Madrid Stock Exchange Index (MSEI).
Classification Political Economy; Economic Statistics, Econometrics, Business Informatics
Free Keywords Nonparametric estimation; Stock Market Indexes; Time-varying variance and covariance prediction
Document language English
Publication Year 2009
Page/Pages p. 3437-3445
Journal Applied Economics, 41 (2009) 26
DOI http://dx.doi.org/10.1080/00036840701439371
Status Postprint; peer reviewed
Licence PEER Licence Agreement (applicable only to documents from PEER project)