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• W1996140087 abstract "Abstract. A new way of estimating stochastic volatility models is developed. The method is based on the existence of autoregressive moving average (ARMA) representations for powers of the log‐squared observations. These representations allow to build a criterion obtained by weighting the sums of squared innovations corresponding to the different ARMA models. The estimator obtained by minimizing the criterion with respect to the parameters of interest is shown to be consistent and asymptotically normal. Monte‐Carlo experiments illustrate the finite sample properties of the estimator. The method has potential applications to other non‐linear time‐series models." @default.
• W1996140087 created "2016-06-24" @default.
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• W1996140087 date "2006-01-30" @default.
• W1996140087 modified "2023-10-16" @default.
• W1996140087 title "Linear-representation Based Estimation of Stochastic Volatility Models" @default.
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• W1996140087 doi "https://doi.org/10.1111/j.1467-9469.2006.00495.x" @default.
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