A Heavy-Tailed Distribution for ARCH Residuals with Application to Volatility Prediction
The quest for the `best' heavy-tailed distribution for ARCH/GARCH residuals appears to still be ongoing. In this connection, we propose a new distribution that arises in a natural way as an outcome of an implicit model. The challenging application of prediction of squared returns is also discussed; an optimal predictor is formulated, and the usefulness of the new distribution for prediction is demonstrated on three real datasets.
References listed on IDEAS
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"Generalized autoregressive conditional heteroskedasticity,"
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