Measuring Model Risk
AbstractWe propose to interpret distribution model risk as sensitivity of expected loss to changes in the risk factor distribution, and to measure the distribution model risk of a portfolio by the maximum expected loss over a set of plausible distributions defined in terms of some divergence from an estimated distribution. The divergence may be relative entropy, a Bregman distance, or an $f$-divergence. We give formulas for the calculation of distribution model risk and explicitly determine the worst case distribution from the set of plausible distributions. We also give formulas for the evaluation of divergence preferences describing ambiguity averse decision makers.
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Bibliographic InfoPaper provided by arXiv.org in its series Papers with number 1301.4832.
Date of creation: Jan 2013
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Web page: http://arxiv.org/
This paper has been announced in the following NEP Reports:
- NEP-ALL-2013-01-26 (All new papers)
- NEP-RMG-2013-01-26 (Risk Management)
- NEP-UPT-2013-01-26 (Utility Models & Prospect Theory)
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- Kerkhof, Jeroen & Melenberg, Bertrand & Schumacher, Hans, 2010. "Model risk and capital reserves," Journal of Banking & Finance, Elsevier, vol. 34(1), pages 267-279, January.
- Gilboa, Itzhak & Schmeidler, David, 1989. "Maxmin expected utility with non-unique prior," Journal of Mathematical Economics, Elsevier, vol. 18(2), pages 141-153, April.
- Hansen, Lars Peter & Sargent, Thomas J., 2007.
"Recursive robust estimation and control without commitment,"
Journal of Economic Theory,
Elsevier, vol. 136(1), pages 1-27, September.
- Hansen, Lars Peter & Sargent, Thomas J., 2005. "Recursive robust estimation and control without commitment," Discussion Paper Series 1: Economic Studies 2005,28, Deutsche Bundesbank, Research Centre.
- Fabio Maccheroni & Massimo Marinacci & Aldo Rustichini, 2006.
"Ambiguity Aversion, Robustness, and the Variational Representation of Preferences,"
Econometric Society, vol. 74(6), pages 1447-1498, November.
- Fabio Maccheroni & Massimo Marinacci & Aldo Rustichini, 2004. "Ambiguity Aversion, Robustness, and the Variational Representation of Preferences," Carlo Alberto Notebooks 12, Collegio Carlo Alberto, revised 2006.
- Rama Cont, 2006. "Model uncertainty and its impact on the pricing of derivative instruments," Post-Print halshs-00002695, HAL.
- Philippe Artzner & Freddy Delbaen & Jean-Marc Eber & David Heath, 1999. "Coherent Measures of Risk," Mathematical Finance, Wiley Blackwell, vol. 9(3), pages 203-228.
- Thomas J. Sargent & LarsPeter Hansen, 2001. "Robust Control and Model Uncertainty," American Economic Review, American Economic Association, vol. 91(2), pages 60-66, May.
- Barillas, Francisco & Hansen, Lars Peter & Sargent, Thomas J., 2009. "Doubts or variability?," Journal of Economic Theory, Elsevier, vol. 144(6), pages 2388-2418, November.
- Marco Avellaneda & Antonio ParAS, 1996. "Managing the volatility risk of portfolios of derivative securities: the Lagrangian uncertain volatility model," Applied Mathematical Finance, Taylor and Francis Journals, vol. 3(1), pages 21-52.
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