Approximate Whittle Analysis of Fractional Cointegration and the Stock Market Synchronization Issue

Gilles de Truchis

Working Papers from HAL

Abstract: I consider a bivariate stationary fractional cointegration system and I propose a quasi-maximum likelihood estimator based on the Whittle analysis of the joint spectral density of the regressor and errors to estimate jointly all parameters of interest of the model: the long run coefficient and the long memory parameters of the regressor and errors. I lead a Monte Carlo experiment which reveals the good finite sample properties of this estimator, even when the parameter space is extended to the non-stationary regions. An application to the stock market synchronization is proposed to illustrate the empirical relevance of this estimator.

Keywords: Monte-Carlo simulation; Parametric estimation; Fractional cointegration; Frequency domain; Full-band estimator (search for similar items in EconPapers)
Date: 2012-09
Note: View the original document on HAL open archive server: https://shs.hal.science/halshs-00793220v1
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Related works:
Journal Article: Approximate Whittle analysis of fractional cointegration and the stock market synchronization issue (2013)
Working Paper: Approximate Whittle analysis of fractional cointegration and the stock market synchronization issue (2013)
Working Paper: Approximate Whittle Analysis of Fractional Cointegration and the Stock Market Synchronization Issue (2012)
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