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We propose a new class of observation-driven time-varying parameter models for dynamic volatilities and correlations to handle time series from heavy-tailed distributions. The model adopts generalized autoregressive score dynamics to obtain a time-varying covariance matrix of the multivariate...
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autoregressive conditional heteroskedasticity model and the dynamic conditional correlation model where distributional assumptions …
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autoregressive conditional heteroskedasticity model and the dynamic conditional correlation model where distributional assumptions …
Persistent link: https://www.econbiz.de/10009126699
We study whether prices of traded options contain information about future extreme market events. Our option-implied conditional expectation of market loss due to tail events, or tail loss measure, predicts future market returns, magnitude, and probability of the market crashes, beyond and above...
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This paper considers a multivariate t version of the Gaussian dynamic conditional correlation (DCC) model proposed by …
Persistent link: https://www.econbiz.de/10003586562