Economics at your fingertips  

Improving daily Value-at-Risk forecasts: The relevance of short-run volatility for regulatory quality assessment

Theo Berger and Ramazan Gencay

Journal of Economic Dynamics and Control, 2018, vol. 92, issue C, 30-46

Abstract: In this paper, we present a novel perspective on data filtering and present an innovative wavelet-based approach that leads to improved Value-at-Risk (VaR) forecasts. A separation of financial conditional volatility into short-, mid- and long-run components allows us to study the relevance of these frequency components with respect to a regulatory quality assessment for daily VaR forecasts.

Keywords: Value-at-Risk; Forecasting; Wavelet decomposition; Regulatory back-testing (search for similar items in EconPapers)
JEL-codes: C53 C58 G17 G28 G32 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7) Track citations by RSS feed

Downloads: (external link)
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link:

DOI: 10.1016/j.jedc.2018.03.016

Access Statistics for this article

Journal of Economic Dynamics and Control is currently edited by J. Bullard, C. Chiarella, H. Dawid, C. H. Hommes, P. Klein and C. Otrok

More articles in Journal of Economic Dynamics and Control from Elsevier
Bibliographic data for series maintained by Nithya Sathishkumar ().

Page updated 2021-05-04
Handle: RePEc:eee:dyncon:v:92:y:2018:i:c:p:30-46