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Volatility (SV) and Generalised Autoregressive Conditional Heteroskedasticity (GARCH) models which are both extended to include … outperforms the GARCH model. …
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–regime and Markov-switching GARCH (MSGARCH) models, from a risk management perspective. I find that, for daily, weekly, and ten … étude à grande échelle empirique pour comparer la` performance de prévision de modèle GARCH sans changement de régime et de … modèle GARCH à changement de régimes Markovien (MSGARCH) du point de vue d’un gestionnaire des risques. Les résultats …
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intraday stock returns. Value-at-Risk (VaR) predictions obtained from daily GARCH models extended with additional information … risk. ARFIMA models produce better backtesting results than GARCH models but fare worse in terms of independence of the … hits sequence. Encompassing tests further suggest that GARCH and ARFIMA models can be fruitfully combined to produce more …
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The sum of squared intraday returns provides an unbiased and almost error-free measure of ex-post volatility. In this paper we develop a nonlinear Autoregressive Fractionally Integrated Moving Average (ARFIMA) model for realized volatility, which accommodates level shifts, day-of-the-week...
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