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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… Click to show full 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:
volatility;
value risk;
quality assessment;
regulatory quality
Journal Title: Journal of Economic Dynamics and Control
Year Published: 2018
Link to full text (if available)
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Journal Title: Journal of Economic Dynamics and Control
Year Published: 2018
Link to full text (if available)
Share on Social Media: Sign Up to like & get
recommendations!