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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

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In this article, 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 and the Madrid Stock Exchange Index.

Document Type: Research Article


Affiliations: Department of Quantitative Methods, University of Las Palmas de GC, Spain Campus de Tafira. Facultad de Ciencias Economicas y EE, Las Palmas de Gran Canaria, Spain

Publication date: 2009-12-01

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