Torben G. Andersen () (Department of Finance, Kellogg School of Management, Northwestern University, Evanston, IL 60208, and NBER) Tim Bollerslev () (Department of Economics, Duke University, Durham, NC 27708, and NBER) Peter F. Christoffersen () (Faculty of Management, McGill University, Montreal, Quebec, H3A 1G5, and CIRANO) Francis X. Diebold () (Department of Economics, University of Pennsylvania, Philadelphia, PA 19104, and NBER)
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What do academics have to offer market risk management practitioners in financial institutions? Current industry practice largely follows one of two extremely restrictive approaches: historical simulation or RiskMetrics. In contrast, we favor flexible methods based on recent developments in financial econometrics, which are likely to produce more accurate assessments of market risk. Clearly, the demands of real-world risk management in financial institutions – in particular, real-time risk tracking in very high-dimensional situations – impose strict limits on model complexity. Hence we stress parsimonious models that are easily estimated, and we discuss a variety of practical approaches for high-dimensional covariance matrix modeling, along with what we see as some of the pitfalls and problems in current practice. In so doing we hope to encourage further dialog between the academic and practitioner communities, hopefully stimulating the development of improved market risk management technologies that draw on the best of both worlds.
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Paper provided by Center for Financial Studies in its series CFS Working Paper Series with number
2005/02.
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