A Multivariate Kernel Approach to Forecasting the Variance Covariance of Stock Market Returns

A Multivariate Kernel Approach to Forecasting the Variance Covariance of Stock Market Returns

This paper introduces a multivariate kernel based forecasting tool for the prediction of variance-covariance matrices of stock returns. The method introduced allows for the incorporation of macroeconomic variables into the forecasting process of the matrix without resorting to a decomposition of the...

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Bibliographic Details
Main Authors: Ralf Becker, Adam Clements, Robert O'Neill
Format: Article
Language:English
Published: MDPI AG 2018-02-01
Series:Econometrics
Subjects:
volatility forecasting
kernel density estimation
similarity forecasting
Online Access:http://www.mdpi.com/2225-1146/6/1/7

Internet

http://www.mdpi.com/2225-1146/6/1/7

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