Semiparametric Estimation of the Intensity of Long Memory in Conditional Heteroskedasticity
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- Giraitis, Liudas & Kokoszka, Piotr & Leipus, Remigijus & Teyssière, Gilles, 1999. "Semiparametric estimation of the intensity of long memory in conditional heteroskedasticity," SFB 373 Discussion Papers 1999,81, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
- Giraitis, L. & Kokoszka, P. & Leipus, R. & Teyssiere, G., 1999. "Semiparametric Estimation of the Intensity of Long Memory in Conditional Heteroskedasticity," G.R.E.Q.A.M. 99a24, Universite Aix-Marseille III.
References listed on IDEAS
- Lobato, Ignacio N & Savin, N E, 1998.
"Real and Spurious Long-Memory Properties of Stock-Market Data,"
Journal of Business & Economic Statistics,
American Statistical Association, vol. 16(3), pages 261-268, July.
- Lobato, I.N. & Savin, N.E., 1996. "Real and Spurious Long Memory Properties of Stock Market Data," Working Papers 96-07, University of Iowa, Department of Economics.
- I.N. Lobato & N.E. Savin, 1996. "Real and Spurious Long Memory Properties of Stock Market Data," Econometrics 9605004, EconWPA, revised 26 Sep 1996.
- Kwiatkowski, Denis & Phillips, Peter C. B. & Schmidt, Peter & Shin, Yongcheol, 1992.
"Testing the null hypothesis of stationarity against the alternative of a unit root : How sure are we that economic time series have a unit root?,"
Journal of Econometrics,
Elsevier, vol. 54(1-3), pages 159-178.
- Kwiatkowski, D. & Phillips, P.C.B. & Schmidt, P., 1990. "Testing the Null Hypothesis of Stationarity Against the Alternative of Unit Root : How Sure are we that Economic Time Series have a Unit Root?," Papers 8905, Michigan State - Econometrics and Economic Theory.
- Denis Kwiatkowski & Peter C.B. Phillips & Peter Schmidt, 1991. "Testing the Null Hypothesis of Stationarity Against the Alternative of a Unit Root: How Sure Are We That Economic Time Series Have a Unit Root?," Cowles Foundation Discussion Papers 979, Cowles Foundation for Research in Economics, Yale University.
- Baillie, Richard T. & Bollerslev, Tim & Mikkelsen, Hans Ole, 1996.
"Fractionally integrated generalized autoregressive conditional heteroskedasticity,"
Journal of Econometrics,
Elsevier, vol. 74(1), pages 3-30, September.
- Tom Doan, "undated". "RATS programs to replicate Baillie, Bollerslev, Mikkelson FIGARCH results," Statistical Software Components RTZ00009, Boston College Department of Economics.
- Ding, Zhuanxin & Granger, Clive W. J., 1996. "Modeling volatility persistence of speculative returns: A new approach," Journal of Econometrics, Elsevier, vol. 73(1), pages 185-215, July.
CitationsCitations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
- Jonathan Dark, 2004. "Long memory in the volatility of the Australian All Ordinaries Index and the Share Price Index futures," Monash Econometrics and Business Statistics Working Papers 5/04, Monash University, Department of Econometrics and Business Statistics.
- Wolfgang Härdle & Julius Mungo, 2008. "Value-at-Risk and Expected Shortfall when there is long range dependence," SFB 649 Discussion Papers SFB649DP2008-006, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
- Jonathan Dark, 2004. "Bivariate error correction FIGARCH and FIAPARCH models on the Australian All Ordinaries Index and its SPI futures," Monash Econometrics and Business Statistics Working Papers 4/04, Monash University, Department of Econometrics and Business Statistics.
- Giraitis, Liudas & Kokoszka, Piotr & Leipus, Remigijus & Teyssiere, Gilles, 2003. "Rescaled variance and related tests for long memory in volatility and levels," Journal of Econometrics, Elsevier, vol. 112(2), pages 265-294, February.
More about this item
Keywordslong memory; ARCH models; semiparametric estimation; modified R / S ; KPSS and V / S statistics; periodogram;
- C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
- C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
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