Estimation Risk in Financial Risk Management

Posted: 25 Apr 2005

See all articles by Peter Christoffersen

Peter Christoffersen

University of Toronto - Rotman School of Management; Copenhagen Business School; Aarhus University - CREATES

Sílvia Gonçalves

University of Montreal - Department of Economics; McGill University - Department of Economics

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 that takes into account parameter estimation error in dynamic models of portfolio variance.

Keywords: Value-at-risk, VAR, portfolio risk management, risk capital allocation, performance attribution, expected shortfall

Suggested Citation

Christoffersen, Peter and Goncalves, Silvia, Estimation Risk in Financial Risk Management. Available at SSRN: https://ssrn.com/abstract=708105

Peter Christoffersen (Contact Author)

University of Toronto - Rotman School of Management ( email )

105 St. George Street
Toronto, Ontario M5S 3E6 M5P 3C4
Canada
416-946-5511 (Phone)

Copenhagen Business School

Solbjerg Plads 3
Frederiksberg C, DK - 2000
Denmark

Aarhus University - CREATES

School of Economics and Management
Building 1322, Bartholins Alle 10
DK-8000 Aarhus C
Denmark

Silvia Goncalves

University of Montreal - Department of Economics ( email )

C.P. 6128, succursale Centre-Ville
Montreal, Quebec H3C 3J7
Canada

McGill University - Department of Economics ( email )

855 Sherbrooke Street West
Montreal, QC H3A 2T7
CANADA

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