Estimation risk in financial risk management

Peter Christoffersen, Sílvia Gonçalves

Abstract

ABSTRACT

Value-at-risk (VAR) is increasingly used in portfolio risk measurement, risk capital allocation and performance attribution. Financial risk managers are therefore rightfully concerned with the precision of typical VAR techniques. The purpose of this paper is to assess the precision of common dynamic models and to quantify the magnitude of the estimation error by constructing confidence intervals around the point VAR and expected shortfall (ES) forecasts. A key challenge in constructing proper confidence intervals arises from the conditional variance dynamics that are typically found in speculative returns. Our paper suggests a resampling technique which takes into account parameter estimation error in dynamic models of portfolio variance.