Forecasting gains by using extreme value theory with realised GARCH filter

Forecasting gains by using extreme value theory with realised GARCH filter

Early empirical evidence suggests that the realised generalised autoregressive conditional heteroskedasticity (GARCH) model provides significant forecasting gains over the standard GARCH models in volatility forecasting. We extend this literature in quantile forecasting by implementing conditional e...

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Bibliographic Details
Main Authors: Samit Paul, Prateek Sharma
Format: Article
Language:English
Published: Elsevier 2021-03-01
Series:IIMB Management Review
Subjects:
Extreme value theory
Realised GARCH
Skewed student-t
Realised kernel
Value-at-risk
Expected shortfall
Online Access:http://www.sciencedirect.com/science/article/pii/S0970389621000264

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http://www.sciencedirect.com/science/article/pii/S0970389621000264

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