Intraday foreign exchange rate volatility forecasting: univariate and multilevel functional GARCH models
arxiv(2023)
摘要
This paper seeks to predict conditional intraday volatility in foreign
exchange (FX) markets using functional Generalized AutoRegressive Conditional
Heteroscedasticity (GARCH) models. We contribute to the existing functional
GARCH-type models by accounting for the stylised features of long-range and
cross-dependence through estimating the models with long-range dependent and
multi-level functional principal component basis functions. Remarkably, we find
that taking account of cross-dependency dynamics between the major currencies
significantly improves intraday conditional volatility forecasting.
Additionally, incorporating intraday bid-ask spread using a functional GARCH-X
model adds explainability of long-range dependence and further enhances
predictability. Intraday risk management applications are presented to
highlight the practical economic benefits of our proposed approaches.
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