Finite sample properties of a QML estimator of stochastic volatility models with long memory
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- Pérez, Ana, 1999. "Finite sample properties of a QML estimator of stochastic volatility models with long memory," DES - Working Papers. Statistics and Econometrics. WS 6360, Universidad Carlos III de Madrid. Departamento de EstadÃstica.
References listed on IDEAS
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Citations
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Cited by:
- Asai Manabu & So Mike K.P., 2015. "Long Memory and Asymmetry for Matrix-Exponential Dynamic Correlation Processes," Journal of Time Series Econometrics, De Gruyter, vol. 7(1), pages 69-94, January.
- Artiach, Miguel & Arteche, Josu, 2012. "Doubly fractional models for dynamic heteroscedastic cycles," Computational Statistics & Data Analysis, Elsevier, vol. 56(6), pages 2139-2158.
- Arteche, J., 2006.
"Semiparametric estimation in perturbed long memory series,"
Computational Statistics & Data Analysis, Elsevier, vol. 51(4), pages 2118-2141, December.
- Josu Arteche, 2006. "Semiparametric estimation in perturbed long memory series," Computing in Economics and Finance 2006 22, Society for Computational Economics.
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- Asai, Manabu & McAleer, Michael, 2015.
"Forecasting co-volatilities via factor models with asymmetry and long memory in realized covariance,"
Journal of Econometrics, Elsevier, vol. 189(2), pages 251-262.
- Manabu Asai & Michael McAleer, 2014. "Forecasting Co-Volatilities via Factor Models with Asymmetry and Long Memory in Realized Covariance," Documentos de Trabajo del ICAE 2014-05, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
- Manabu Asai & Michael McAleer, 2014. "Forecasting Co-Volatilities via Factor Models with Asymmetry and Long Memory in Realized Covariance," Tinbergen Institute Discussion Papers 14-037/III, Tinbergen Institute.
- Manabu Asai & Michael McAleer, 2014. "Forecasting Co-Volatilities via Factor Models with Asymmetry and Long Memory in Realized Covariance," Working Papers in Economics 14/10, University of Canterbury, Department of Economics and Finance.
- Kwan, Wilson & Li, Wai Keung & Li, Guodong, 2012. "On the estimation and diagnostic checking of the ARFIMA–HYGARCH model," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3632-3644.
- Ruiz Esther & Pérez Ana, 2012. "Maximally Autocorrelated Power Transformations: A Closer Look at the Properties of Stochastic Volatility Models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 16(3), pages 1-33, September.
- Ana Pérez & Esther Ruiz, 2002.
"Modelos de memoria larga para series económicas y financieras,"
Investigaciones Economicas, Fundación SEPI, vol. 26(3), pages 395-445, September.
- Pérez, Ana, 2001. "Modelos de memoria larga para series económicas y financieras," DES - Documentos de Trabajo. EstadÃstica y EconometrÃa. DS ds010101, Universidad Carlos III de Madrid. Departamento de EstadÃstica.
- Manabu Asai & Chia-Lin Chang & Michael McAleer, 2016.
"Realized Matrix-Exponential Stochastic Volatility with Asymmetry, Long Memory and Spillovers,"
Tinbergen Institute Discussion Papers
16-076/III, Tinbergen Institute.
- Manabu Asai & Chia-Lin Chang & Michael McAleer, 2016. "Realized Matrix-Exponential Stochastic Volatility with Asymmetry, Long Memory and Spillovers," Documentos de Trabajo del ICAE 2016-15, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
- Asai, M. & Chang, C-L. & McAleer, M.J., 2016. "Realized Matrix-Exponential Stochastic Volatility with Asymmetry, Long Memory and Spillovers," Econometric Institute Research Papers EI2016-41, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
- Carmen Broto & Esther Ruiz, 2004.
"Estimation methods for stochastic volatility models: a survey,"
Journal of Economic Surveys, Wiley Blackwell, vol. 18(5), pages 613-649, December.
- Broto, Carmen, 2002. "Estimation methods for stochastic volatility models: a survey," DES - Working Papers. Statistics and Econometrics. WS ws025414, Universidad Carlos III de Madrid. Departamento de EstadÃstica.
- Trino-Manuel Ñíguez, 2003. "Volatility And Var Forecasting For The Ibex-35 Stock-Return Index Using Figarch-Type Processes And Different Evaluation Criteria," Working Papers. Serie AD 2003-33, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
- Asai, Manabu & Chang, Chia-Lin & McAleer, Michael, 2022. "Realized matrix-exponential stochastic volatility with asymmetry, long memory and higher-moment spillovers," Journal of Econometrics, Elsevier, vol. 227(1), pages 285-304.
- Adam McCloskey, 2013.
"Estimation of the long-memory stochastic volatility model parameters that is robust to level shifts and deterministic trends,"
Journal of Time Series Analysis, Wiley Blackwell, vol. 34(3), pages 285-301, May.
- Adam McCloskey, 2012. "Estimation of the Long-Memory Stochastic Volatility Model Parameters that is Robust to Level Shifts and Deterministic Trends," Working Papers 2012-17, Brown University, Department of Economics.
- Ruiz, Esther & Veiga, Helena, 2008.
"Modelling long-memory volatilities with leverage effect: A-LMSV versus FIEGARCH,"
Computational Statistics & Data Analysis, Elsevier, vol. 52(6), pages 2846-2862, February.
- Veiga, Helena, 2006. "Modelling long-memory volatilities with leverage effect: ALMSV versus FIEGARCH," DES - Working Papers. Statistics and Econometrics. WS ws066016, Universidad Carlos III de Madrid. Departamento de EstadÃstica.
- repec:ehu:cuader:10261 is not listed on IDEAS
- Ferraz, Rosemeire O. & Hotta, Luiz K., 2007. "Quasi-Maximum Likelihood Estimation of Long-Memory Stochastic Volatility Models," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 27(2), November.
- Arteche, Josu, 2004. "Gaussian semiparametric estimation in long memory in stochastic volatility and signal plus noise models," Journal of Econometrics, Elsevier, vol. 119(1), pages 131-154, March.
- Grané, A. & Veiga, H., 2008. "Accurate minimum capital risk requirements: A comparison of several approaches," Journal of Banking & Finance, Elsevier, vol. 32(11), pages 2482-2492, November.
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