A Class of Antipersistent Processes
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Abstract
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DOI: 10.1111/j.1467-9892.2006.00509.x
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Cited by:
- Hailin Sang & Yongli Sang, 2017. "Memory properties of transformations of linear processes," Statistical Inference for Stochastic Processes, Springer, vol. 20(1), pages 79-103, April.
- Isao Ishida & Toshiaki Watanabe, 2009.
"Modeling and Forecasting the Volatility of the Nikkei 225 Realized Volatility Using the ARFIMA-GARCH Model,"
CIRJE F-Series
CIRJE-F-608, CIRJE, Faculty of Economics, University of Tokyo.
- Isao Ishida & Toshiaki Watanabe, 2009. "Modeling and Forecasting the Volatility of the Nikkei 225 Realized Volatility Using the ARFIMA-GARCH Model," CARF F-Series CARF-F-145, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
- Isao Ishida & Toshiaki Watanabe, 2009. "Modeling and Forecasting the Volatility of the Nikkei 225 Realized Volatility Using the ARFIMA-GARCH Model," Global COE Hi-Stat Discussion Paper Series gd08-032, Institute of Economic Research, Hitotsubashi University.
- Lopes, SÃlvia R.C. & Prass, Taiane S., 2014. "Theoretical results on fractionally integrated exponential generalized autoregressive conditional heteroskedastic processes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 401(C), pages 278-307.
- Hassler, Uwe, 2012. "Impulse responses of antipersistent processes," Economics Letters, Elsevier, vol. 116(3), pages 454-456.
- Zevallos, Mauricio & Palma, Wilfredo, 2013. "Minimum distance estimation of ARFIMA processes," Computational Statistics & Data Analysis, Elsevier, vol. 58(C), pages 242-256.
- Shelton Peiris & Richard Hunt, 2023. "Revisiting the Autocorrelation of Long Memory Time Series Models," Mathematics, MDPI, vol. 11(4), pages 1-8, February.
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