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- W4289444015 endingPage "101724" @default.
- W4289444015 startingPage "101724" @default.
- W4289444015 abstract "We perform a large-scale analysis to evaluate the performance of traditional and Markov-switching GARCH models for the volatility of 292 cryptocurrencies. For each cryptocurrency, we estimate a total of 27 alternative GARCH specifications. We consider models that allow up to three different regimes. First, the models are compared in terms of goodness-of-fit using the Deviance Information Criterion and the Bayesian Predictive Information Criterion. Next, we evaluate the ability of the models in forecasting one-day ahead conditional volatility and Value-at-Risk. The results indicate that for a wide range of cryptocurrencies, time-varying models outperform traditional ones." @default.
- W4289444015 created "2022-08-02" @default.
- W4289444015 creator A5005656285 @default.
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- W4289444015 date "2022-12-01" @default.
- W4289444015 modified "2023-10-10" @default.
- W4289444015 title "On the volatility of cryptocurrencies" @default.
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- W4289444015 doi "https://doi.org/10.1016/j.ribaf.2022.101724" @default.
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