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Fractional Cointegration In Stochastic Volatility Models

  • da Silva, Afonso Gonçalves
  • Robinson, Peter M.

Asset returns are frequently assumed to be determined by one or more common factors. We consider a bivariate factor model where the unobservable common factor and idiosyncratic errors are stationary and serially uncorrelated but have strong dependence in higher moments. Stochastic volatility models for the latent variables are employed, in view of their direct application to asset pricing models. Assuming that the underlying persistence is higher in the factor than in the errors, a fractional cointegrating relationship can be recovered by suitable transformation of the data. We propose a narrow band semiparametric estimate of the factor loadings, which is shown to be consistent with a rate of convergence, and its finite-sample properties are investigated in a Monte Carlo experiment.

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Article provided by Cambridge University Press in its journal Econometric Theory.

Volume (Year): 24 (2008)
Issue (Month): 05 (October)
Pages: 1207-1253

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Handle: RePEc:cup:etheor:v:24:y:2008:i:05:p:1207-1253_08
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  1. Bent Jesper Christensen & Morten Ø. Nielsen, . "Semiparametric Analysis of Stationary Fractional Cointegration and the Implied-Realized Volatility Relation in High-Frequency Options Data," Economics Working Papers 2001-4, School of Economics and Management, University of Aarhus.
  2. Clifford Hurvich & Eric Moulines & Philippe Soulier, 2004. "Estimating Long Memory in Volatility," Econometrics 0412006, EconWPA.
  3. Celso Brunetti & Christopher L. Gilbert, 1999. "Bivariate FIGARCH and Fractional Cointegration," Working Papers 408, Queen Mary University of London, School of Economics and Finance.
  4. Javier Hualde & Peter Robinson, 2006. "Semiparametric Estimation of Fractional Cointegration," Faculty Working Papers 07/06, School of Economics and Business Administration, University of Navarra.
  5. D Marinucci & Peter M Robinson, 2001. "Semiparametric Fractional Cointegration Analysis," STICERD - Econometrics Paper Series 420, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
  6. Andrew Harvey (ed.), 1994. "Time Series," Books, Edward Elgar, volume 0, number 599, April.
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