Nonparametric estimation of time-varying covariance matrix in a slowly changing vector random walk model Report as inadecuate




Nonparametric estimation of time-varying covariance matrix in a slowly changing vector random walk model - Download this document for free, or read online. Document in PDF available to download.

Abstract

A new multivariate random walk model with slowly changing parameters is introduced and investigated in detail. Nonparametric estimation of local covariance matrix is proposed.The asymptotic distributions, including asymptotic biases, variances and covariances of the proposed estimators are obtained. The properties of the estimated value of a weighted sum of individual nonparametric estimators are also studied in detail. The integrated effect of the estimation errors from the estimation for the difference series to the integrated processes is derived. Practical relevance of the model and estimation is illustrated by application to several foreign exchange rates.



Item Type: MPRA Paper -

Institution: Heriot-Watt University and Brunel University-

Original Title: Nonparametric estimation of time-varying covariance matrix in a slowly changing vector random walk model-

Language: English-

Keywords: Multivariate time series; slowly changing vector random walk; local covariance matrix; kernel estimation; asymptotic properties; forecasting-

Subjects: C - Mathematical and Quantitative Methods > C3 - Multiple or Simultaneous Equation Models ; Multiple Variables > C32 - Time-Series Models ; Dynamic Quantile Regressions ; Dynamic Treatment Effect Models ; Diffusion Processes ; State Space ModelsG - Financial Economics > G0 - General > G00 - GeneralC - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C14 - Semiparametric and Nonparametric Methods: General-





Author: Feng, Yuanhua

Source: https://mpra.ub.uni-muenchen.de/1597/



DOWNLOAD PDF




Related documents