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Peer-Review Record

Building Multivariate Time-Varying Smooth Transition Correlation GARCH Models, with an Application to the Four Largest Australian Banks

by Anthony D. Hall 1, Annastiina Silvennoinen 1 and Timo Teräsvirta 2,3,*
Reviewer 1: Anonymous
Reviewer 2: Anonymous
Submission received: 15 November 2022 / Revised: 26 January 2023 / Accepted: 27 January 2023 / Published: 6 February 2023

Round 1

Reviewer 1 Report

Please see the pdf file.

Comments for author File: Comments.pdf

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Reviewer 2 Report

This paper well explain the methodology for building Multivariate Time-Varying STCC–GARCH models, introduced by Silvennoinen and Teräsvirta (in press). In particular, they show all the steps and data-driven decisions required to specify the parametric structure of the model correctly. Finally, the paper is accompanied by an R-package, "mtvgarch." However, I have two small comments:

1) Double check the capital letters on the title.

 2)At page 4, you write:

“For the Big Four application we simplify the definition (5) slightly by assuming P_(12)=P_(22)”.

Hence, instead of considering four matrices (P_(11),  P_(12),  P_(21),  P_(22)), you consider P_(1), P_(2), and P_(3). Is this only to have P_t positive definite, or is there also some empirical intuition about it?

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

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