Modelling stochastic volatility in asset returns using fractionally integrated semiparametric techniques
This study estimates the order of integration in the volatility process of several exchange rates and stock returns using fractionally integrated semiparametric techniques, namely a local Whittle semiparametric estimator. The results suggest that all series can be well described in terms of I ( d ) statistical models, with values of d higher than 0, indicating long-memory behaviour.
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Volume (Year): 2 (2006)
Issue (Month): 1 (January)
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References listed on IDEAS
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- Tom Doan, . "PPUNIT: RATS procedure to perform Phillips-Perron Unit Root test," Statistical Software Components RTS00160, Boston College Department of Economics.
- Ruiz, Esther, 1994. "Quasi-maximum likelihood estimation of stochastic volatility models," Journal of Econometrics, Elsevier, vol. 63(1), pages 289-306, July.
- Lobato, Ignacio N., 1999. "A semiparametric two-step estimator in a multivariate long memory model," Journal of Econometrics, Elsevier, vol. 90(1), pages 129-153, May.
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