Improving daily Value-at-Risk forecasts: The relevance of short-run volatility for regulatory quality assessment
Theo Berger and
Journal of Economic Dynamics and Control, 2018, vol. 92, issue C, 30-46
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)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:dyncon:v:92:y:2018:i:c:p:30-46
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