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Optimal Estimation Strategies for Bivariate Fractional Cointegration Systems and the Co-persistence Analysis of Stock Market Realized Volatilities

Marcel Aloy () and Gilles de Truchis ()

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Abstract: Estimation methods of bivariate fractional cointegration models are numerous and have in most cases non-equivalent asymptotic and finite sample properties, implying difficulties in determining an optimal estimation strategy. This paper addresses this issue by means of simulations and provides useful guidance to practitioners. Our Monte Carlo study reveals the superiority of techniques that estimate jointly all parameters of interest, over those operating in two steps. To illustrate the empirical relevance of our results, we propose a co-persistence analysis of two stock market realized volatility series.

Keywords: Economie; quantitative (search for similar items in EconPapers)
Date: 2016-06
Note: View the original document on HAL open archive server: https://hal-amu.archives-ouvertes.fr/hal-01447864
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Published in Computational Economics, Springer Verlag, 2016, 48 (1), pp.83--104. 〈10.1007/s10614-015-9531-6〉

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Journal Article: Optimal Estimation Strategies for Bivariate Fractional Cointegration Systems and the Co-persistence Analysis of Stock Market Realized Volatilities (2016) Downloads
Working Paper: Optimal Estimation Strategies for Bivariate Fractional Cointegration Systems and the Co-persistence Analysis of Stock Market Realized Volatilities (2015)
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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-01447864

DOI: 10.1007/s10614-015-9531-6

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