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      Bayesian Realized-GARCH Models for Financial Tail Risk Forecasting Incorporating Two-sided Weibull Distribution

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          Abstract

          The realized GARCH framework is extended to incorporate the two-sided Weibull distribution, for the purpose of volatility and tail risk forecasting in a financial time series. Further, the realized range, as a competitor for realized variance or daily returns, is employed in the realized GARCH framework. Further, sub-sampling and scaling methods are applied to both the realized range and realized variance, to help deal with inherent micro-structure noise and inefficiency. An adaptive Bayesian Markov Chain Monte Carlo method is developed and employed for estimation and forecasting, whose properties are assessed and compared with maximum likelihood, via a simulation study. Compared to a range of well-known parametric GARCH, GARCH with two-sided Weibull distribution and realized GARCH models, tail risk forecasting results across 7 market index return series and 2 individual assets clearly favor the realized GARCH models incorporating two-sided Weibull distribution, especially models employing the sub-sampled realized variance and sub-sampled realized range, over a six year period that includes the global financial crisis.

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          Most cited references17

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          Generalized autoregressive conditional heteroskedasticity

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            • Record: found
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            • Article: not found

            Weak convergence and optimal scaling of random walk Metropolis algorithms

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              • Record: found
              • Abstract: not found
              • Article: not found

              Answering the Skeptics: Yes, Standard Volatility Models do Provide Accurate Forecasts

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                Author and article information

                Journal
                2017-07-11
                Article
                1707.03715
                1e7e472e-1b48-4eae-a0bd-fbfe7459fa91

                http://arxiv.org/licenses/nonexclusive-distrib/1.0/

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                33 pages, 5 figures, 8 tables. arXiv admin note: substantial text overlap with arXiv:1612.08488
                q-fin.RM

                Risk management
                Risk management

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