A Unified Approach To The Measurement Error Problem In Time Series Models
AbstractThe measurement error problem that we consider in this paper is concerned with the situation where time series data of various kinds short memory, long memory, and random walk processes are contaminated by white noise. We suggest a unified approach to testing for the existence of such noise. It is found that the power of our test crucially depends on the underlying process.
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Bibliographic InfoArticle provided by Cambridge University Press in its journal Econometric Theory.
Volume (Year): 18 (2002)
Issue (Month): 02 (April)
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- Manuabu Asai & Michael McAleer & Marcelo C. Medeiros, 2010.
"Modelling and Forecasting Noisy Realized Volatility,"
Working Papers in Economics
10/21, University of Canterbury, Department of Economics and Finance.
- Asai, Manabu & McAleer, Michael & Medeiros, Marcelo C., 2012. "Modelling and forecasting noisy realized volatility," Computational Statistics & Data Analysis, Elsevier, vol. 56(1), pages 217-230, January.
- Manabu Asai & Michael McAleer & Marcelo C. Medeiros, 2011. "Modelling and Forecasting Noisy Realized Volatility," Documentos del Instituto Complutense de AnÃ¡lisis EconÃ³mico 2011-09, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales.
- Asai, M. & McAleer, M.J. & Medeiros, M., 2011. "Modelling and Forecasting Noisy Realized Volatility," Econometric Institute Report EI 2011-05, Erasmus University Rotterdam, Econometric Institute.
- Manabu Asai & Michael McAleer & Marcelo C. Medeiros, 2011. "Modelling and Forecasting Noisy Realized Volatility," KIER Working Papers 758, Kyoto University, Institute of Economic Research.
- Manabu Asai & Michael McAleer & Marcelo C. Medeiros, 2009. "Modelling and Forecasting Noisy Realized Volatility," CIRJE F-Series CIRJE-F-669, CIRJE, Faculty of Economics, University of Tokyo.
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