Practical Volatility and Correlation Modeling for Financial Market Risk Management
Torben G. Andersen
Northwestern University - Kellogg School of Management; National Bureau of Economic Research (NBER); University of Aarhus - CREATES
Duke University - Finance; Duke University - Department of Economics; National Bureau of Economic Research (NBER)
University of Toronto - Rotman School of Management; Copenhagen Business School; University of Aarhus - CREATES
Francis X. Diebold
University of Pennsylvania - Department of Economics; National Bureau of Economic Research (NBER)
January 11, 2005
PIER Working Paper No. 05-007, CFS Working Paper 2005/02
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.
Number of Pages in PDF File: 41
JEL Classification: G10
Date posted: January 21, 2005
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