Univariate GARCH models with realized variance

Detta är en Kandidat-uppsats från Uppsala universitet/Statistiska institutionen

Författare: Carl Börjesson; Ossian Löhnn; [2019]

Nyckelord: GARCH; EGARCH; GJRGARCH; external regressor; realized variance; volatility; Value at Risk; nig; Normal inverse gaussian; std; Student’s t distribution; norm; Normal distribution; rugarch; rolling forecast;

Sammanfattning: This essay investigates how realized variance affects the GARCH-models (GARCH, EGARCH, GJRGARCH) when added as an external regressor. The GARCH models are estimated with three different distributions; Normal-, Student’s t- and Normal inverse gaussian distribution. The results are ambiguous - the models with realized variance improves the model fit, but when applied to forecasting, the models with realized variance are performing similar Value at Risk predictions compared to the models without realized variance.

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