(Quantile) Spillover Indexes: simulation-based evidence, confidence intervals and a decomposition
43 Pages Posted: 29 Nov 2023 Last revised: 29 Nov 2024
Date Written: November 10, 2023
Abstract
Quantile-spillover indexes have recently become popular for analyzing tail interdependence. Through a simulation study, we show that the estimation of spillover indexes is affected by a positive distortion when the parameters of the fitted models are not evaluated with respect to their statistical significance, or are not estimated subject to regularization. The distortion is reduced for increasing sample sizes, thanks to, or by filtering out non-significant parameters, even if in small samples it does not disappear due to type I error. We introduce a simulation-based approach to estimate confidence intervals of quantile spillover indexes. We provide an algebraic decomposition of quantile spillover separating the dynamic interdependence from the contemporaneous interdependence. Empirical evidence on equity sector indices shows that distortions on real data are sizable, and the decomposition highlights the predominance of contemporaneous effects. Our results are confirmed for the Spillover index of Diebold and Yilmaz (2009).
Keywords: Quantile-spillover index, Diebold-Yilmaz index, confidence interval, index decomposition
JEL Classification: C10, C13, C32, C33, C55, C58
Suggested Citation: Suggested Citation
Caporin, Massimiliano and Bonaccolto, Giovanni and Shahzad, Syed Jawad Hussain, (Quantile) Spillover Indexes: simulation-based evidence, confidence intervals and a decomposition (November 10, 2023). Available at SSRN: https://ssrn.com/abstract=4629224 or http://dx.doi.org/10.2139/ssrn.4629224
Do you have a job opening that you would like to promote on SSRN?
Feedback
Feedback to SSRN
If you need immediate assistance, call 877-SSRNHelp (877 777 6435) in the United States, or +1 212 448 2500 outside of the United States, 8:30AM to 6:00PM U.S. Eastern, Monday - Friday.