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Estimating Bank Trading Risk: A Factor Model Approach

  • James O'Brien
  • Jeremy Berkowitz
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    Risk in bank trading portfolios and its management are potentially important to the banks%u2019 soundness and to the functioning of securities and derivatives markets. In this paper, proprietary daily trading revenues of 6 large dealer banks are used to study the bank dealers%u2019 market risks using a market factor model approach. Dealers%u2019 exposures to exchange rate, interest rate, equity, and credit market factors are estimated. A factor model framework for variable exposures is presented and two modeling approaches are used: a random coefficient model and rolling factor regressions. The results indicate small average market exposures with significant but relatively moderate variation in exposures over time. Except for interest rates, there is heterogeneity in market exposures across the dealers. For interest rates, the dealers have small average long exposures and exposures vary inversely with the level of rates. Implications for aggregate bank dealer risk and market stability issues are discussed.

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    File URL: http://www.nber.org/papers/w11608.pdf
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    Paper provided by National Bureau of Economic Research, Inc in its series NBER Working Papers with number 11608.

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    Date of creation: Sep 2005
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    Publication status: published as Carey, Mark and Rene M. Stulz (eds.) The Risks of Financial Institutions. Chicago and London: University of Chicago Press, 2006.
    Handle: RePEc:nbr:nberwo:11608
    Note: AP
    Contact details of provider: Postal: National Bureau of Economic Research, 1050 Massachusetts Avenue Cambridge, MA 02138, U.S.A.
    Phone: 617-868-3900
    Web page: http://www.nber.org
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    1. Morris, Stephen & Shin, Hyun Song, 1999. "Risk Management with Interdependent Choice," Oxford Review of Economic Policy, Oxford University Press, vol. 15(3), pages 52-62, Autumn.
    2. Mark Mitchell, 2001. "Characteristics of Risk and Return in Risk Arbitrage," Journal of Finance, American Finance Association, vol. 56(6), pages 2135-2175, December.
    3. Suleyman Basak & Alexander Shapiro, 1999. "Value-at-Risk Based Risk Management: Optimal Policies and Asset Prices," New York University, Leonard N. Stern School Finance Department Working Paper Seires 99-032, New York University, Leonard N. Stern School of Business-.
    4. Fung, William & Hsieh, David A, 1997. "Empirical Characteristics of Dynamic Trading Strategies: The Case of Hedge Funds," Review of Financial Studies, Society for Financial Studies, vol. 10(2), pages 275-302.
    5. Stephen J. Brown & William N. Goetzmann, 2001. "Hedge Funds With Style," Yale School of Management Working Papers ysm177, Yale School of Management.
    6. Jeremy Berkowitz & James O'Brien, 2002. "How Accurate Are Value-at-Risk Models at Commercial Banks?," Journal of Finance, American Finance Association, vol. 57(3), pages 1093-1111, 06.
    7. Vikas Agarwal, 2004. "Risks and Portfolio Decisions Involving Hedge Funds," Review of Financial Studies, Society for Financial Studies, vol. 17(1), pages 63-98.
    8. Gordon J. Alexander & Alexandre M. Baptista, 2004. "A Comparison of VaR and CVaR Constraints on Portfolio Selection with the Mean-Variance Model," Management Science, INFORMS, vol. 50(9), pages 1261-1273, September.
    9. Leippold, Markus & Trojani, Fabio & Vanini, Paolo, 2006. "Equilibrium impact of value-at-risk regulation," Journal of Economic Dynamics and Control, Elsevier, vol. 30(8), pages 1277-1313, August.
    10. Tobias Adrian & Michael J. Fleming, 2005. "What financing data reveal about dealer leverage," Current Issues in Economics and Finance, Federal Reserve Bank of New York, vol. 11(Mar).
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