Spectral risk measures are attractive risk measures as they allow the user to obtain risk measures that reflect their subjective risk aversion. This paper examines spectral risk measures based on an exponential utility function, and finds that these risk measures have nice intuitive properties. It also discusses how they can be estimated using numerical quadrature methods, and how confidence intervals can be estimated for them using a parametric bootstrap. Illustrative results suggest that estimated exponential spectral risk measures obtained using such methods are quite precise in the presence of normally distributed losses.
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Volume (Year): V (2007) Issue (Month): 4 (December) Pages: 57-66 Download reference. The following formats are available: HTML
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Handle: RePEc:icf:icfjfe:v:05:y:2007:i:4:p:57-66
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