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Financial Risk Measurement for Financial Risk Management

  • Torben G. Andersen

    ()

    (Kellogg School of Management, Northwestern University)

  • Tim Bollerslev

    ()

    (Department of Economics, Duke University)

  • Peter F. Christoffersen

    ()

    (Rotman School of Management, University of Toronto)

  • Francis X. Diebold

    ()

    (Department of Economics, University of Pennsylvania)

Current practice largely follows restrictive approaches to market risk measurement, such as historical simulation or RiskMetrics. In contrast, we propose flexible methods that exploit recent developments in financial econometrics and are likely to produce more accurate risk assessments, treating both portfolio-level and asset-level analysis. Asset-level analysis is particularly challenging because 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 powerful yet parsimonious models that are easily estimated. In addition, we emphasize the need for deeper understanding of the links between market risk and macroeconomic fundamentals, focusing primarily on links among equity return volatilities, real growth, and real growth volatilities. Throughout, we strive not only to deepen our scientific understanding of market risk, but also cross-fertilize the academic and practitioner communities, promoting improved market risk measurement technologies that draw on the best of both.

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Paper provided by Penn Institute for Economic Research, Department of Economics, University of Pennsylvania in its series PIER Working Paper Archive with number 11-037.

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Length: 126 pages
Date of creation: 02 Nov 2011
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Handle: RePEc:pen:papers:11-037
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