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The asymmetric moving average model (asMA) is extended to allow forasymmetric quadratic conditional heteroskedasticity (asQGARCH). Theasymmetric parametrization of the conditional variance encompassesthe quadratic GARCH model of Sentana (1995). We introduce a framework fortesting asymmetries in...
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Estimation of the volatility of time series has taken off since the introduction of the GARCH and stochastic volatility … unobserved stochastic volatility, and the varying approaches that have been taken for such estimation.In order to simplify the … comprehension of these estimation methods, the main methods for estimating stochastic volatility are discussed, with focus on their …
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Estimation of the volatility of time series has taken off since the introduction of the GARCH and stochastic volatility … unobserved stochastic volatility, and the varying approaches that have been taken for such estimation. In order to simplify the … comprehension of these estimation methods, the main methods for estimating stochastic volatility are discussed, with focus on their …
Persistent link: https://www.econbiz.de/10011386124
motion (GBM) process. That is, we show what difficulties can arise when failing to account for estimation risk. Our working … parameter sigma, we derive the resulting marginal distribution of the approximated GBM. This allows us to derive post-estimation … results for the technically more-complicated formulae associated with our post-estimation process. We discuss an assortment of …
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