Estimation In Conditionally Heteroscedastic T

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Estimation In Conditionally Heteroscedastic Time Series Models

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Introduction.- Financial time series: facts and models.- Some mathematical tools.- Parameter estimation: an overview.- The QMLE in heteroscedastic time series models: a stochastic recurrence equations approach.- Maximum-likelihood estimation in conditionally heteroscedastic time series models.- Whittle estimation in a heavy-tailed GARCH (1,1) model. EAN/ISBN : 9783540269786 Publisher(s): Springer, Berlin Format: ePub/PDF Author(s): Straumann, Daniel

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