The abstract proposes QRS and probabilistic stacking for quantile forecasts of cryptocurrency realized variance, claiming QRS with linear models performs best, but the supplied full text is unrelated.
Jadoon, Department of Aerospace Engineering & Engineering Mechanics, The University of Texas at Austin, Austin, TX 78712 Ravi G
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Probabilistic Forecasting Cryptocurrencies Volatility: From Point to Quantile Forecasts
The abstract proposes QRS and probabilistic stacking for quantile forecasts of cryptocurrency realized variance, claiming QRS with linear models performs best, but the supplied full text is unrelated.