Financial volatility modeling: The feedback asymmetric conditional autoregressive range model

An implied assumption in the asymmetric conditional autoregressive range (ACARR) model is that upward range is independent of downward range. This paper scrutinizes this assumption on a broad variety of stock indices. Instead of independence, we find significant cross‐interdependence between the upw...

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Bibliographic Details
Published in:Journal of forecasting 2019-01, Vol.38 (1), p.11-28
Main Author: Xie, Haibin
Format: Article
Language:English
Subjects:
ACARR
Asymmetry
CARR
Economic forecasting
Economic models
FACARR
Forecasting
Interdependence
Leverage
price range
Regression analysis
Securities markets
Volatility
volatility forecasting
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Summary:An implied assumption in the asymmetric conditional autoregressive range (ACARR) model is that upward range is independent of downward range. This paper scrutinizes this assumption on a broad variety of stock indices. Instead of independence, we find significant cross‐interdependence between the upward range and the downward range. Regression test shows that the cross‐interdependence cannot be explained by leverage effect. To include the cross‐interdependence, a feedback asymmetric conditional autoregressive range (FACARR) model is proposed. Empirical studies are performed on a variety of stock indices, and the results show that the FACARR model outperforms the ACARR model with high significance for both in‐sample and out‐of‐sample forecasting.
ISSN:0277-6693
1099-131X
DOI:10.1002/for.2548