Abstract
Kernel based estimation of Spectral Risk Measure
by
Suparna Biswas
Spectral risk measures (SRMs) proposed by Acerbi (2002, 2004) belong to the family of coherent risk measures and hence inherit the properties of such measures. SRM is a weighted average of the quantiles of a loss distribution, the weights of which depend on the user's risk aversion. A natural estimator for the class of SRMs has the form of L-statistics. In the literature, properties of the estimator of SRM are obtained using the empirical distribution function. We try to investigate the large sample properties of general L-statistics based on i.i.d cases and apply them to our kernel based estimator of SRM. We prove that the estimator is strongly consistent.
Committee
Workshop
Key Dates
Communication
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