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predictors, where robust stands for the use of mixtures of proper conjugate priors. Concerning dynamic analysis, volatility …
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Considering the inferior volatility tracking capability of the point-data-based models, we propose using the more … informative price interval data and building interval regression models for volatility forecasting. To characterize the … heterogeneity of the market and the nonlinearity of volatility, we incorporated the heterogeneous autoregressive structure and the …
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This paper develops a method to select the threshold in threshold-based jump detection methods. The method is motivated by an analysis of threshold-based jump detection methods in the context of jump-diffusion models. We show that over the range of sampling frequencies a researcher is most...
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We consider semiparametric estimation of the memory parameter in a long memorystochastic volatility model. We study the … is particularlydesirable in the context of the long memory stochastic volatility model …
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We consider semiparametric estimation of the memory parameter in a long memorystochastic volatility model. We study the … stochastic volatility model …
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-Watson, LP(p)-estimators, spline regressor and random forest. They are then compared when calibrating local stochastic volatility …
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