Robust Stochastic Discount Factors
AbstractWhen the market is incomplete, a new non-redundant derivative security cannot be priced by no-arbitrage arguments alone. Moreover, there will be a multiplicity of stochastic discount factors and each of them may give a different price for the new derivative security. This paper develops an approach to the selection of a stochastic discount factor for pricing a new derivative security. The approach is based on the idea that the price of a derivative security should not vary too much when the payoff of the primitive security is slightly perturbed, i.e., the price of the derivative should be robust to model misspecification. The paper develops two metrics of robustness. The first is based on robustness in expectation. The second is based on robustness in probability and draws on tools from the theory of large deviations. We show that in a stochastic volatility model, the two metrics yield analytically tractable bounds for the derivative price, as the underlying stochastic volatility model is perturbed. The bounds can be readily used for numerical examination of the sensitivity of the price of the derivative to model misspecification. The Author 2007. Published by Oxford University Press on behalf of The Society for Financial Studies. All rights reserved. For Permissions, please email: email@example.com, Oxford University Press.
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Bibliographic InfoArticle provided by Society for Financial Studies in its journal The Review of Financial Studies.
Volume (Year): 21 (2008)
Issue (Month): 3 (May)
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- Nina, Boyarchenko & Mario, Cerrato & John, Crosby & Stewart, Hodges, 2013.
"No Good Deals - No Bad Models,"
SIRE Discussion Papers
2013-20, Scottish Institute for Research in Economics (SIRE).
- Nina Boyarchenko & Mario Cerrato & John Crosby & Stewart Hodges, 2012. "No good deals—no bad models," Staff Reports 589, Federal Reserve Bank of New York.
- Nina Boyarchenko & Mario Cerrato & John Crosby & Stewart Hodges, 2013. "No Good Deals - No Bad Models," Working Papers 2013_04, Business School - Economics, University of Glasgow.
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