Hostname: page-component-586b7cd67f-tf8b9 Total loading time: 0 Render date: 2024-11-24T11:06:17.488Z Has data issue: false hasContentIssue false

Convex Duality in Mean-Variance Hedging Under Convex Trading Constraints

Published online by Cambridge University Press:  04 January 2016

Christoph Czichowsky*
Affiliation:
University of Vienna
Martin Schweizer*
Affiliation:
ETH Zürich and Swiss Finance Institute
*
Postal address: Faculty of Mathematics, University of Vienna, Nordbergstrasse 15, A–1090 Vienna, Austria. Email address: [email protected]
∗∗ Postal address: Department of Mathematics, ETH Zürich, Rämistrasse 101, CH–8092, Zürich, Switzerland. Email address: [email protected]
Rights & Permissions [Opens in a new window]

Abstract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.

We study mean-variance hedging under portfolio constraints in a general semimartingale model. The constraints are formulated via predictable correspondences, meaning that the trading strategy is restricted to lie in a closed convex set which may depend on the state and time in a predictable way. To obtain the existence of a solution, we first establish the closedness in L2 of the space of all gains from trade (i.e. the terminal values of stochastic integrals with respect to the price process of the underlying assets). This is a first main contribution which enables us to tackle the problem in a systematic and unified way. In addition, using the closedness allows us to explain and generalise in a systematic way the convex duality results obtained previously by other authors via ad-hoc methods in specific frameworks.

Type
General Applied Probability
Copyright
© Applied Probability Trust 

References

Aliprantis, C. D. and Border, K. C. (2006). Infinite Dimensional Analysis, 3rd edn. Springer, Berlin.Google Scholar
Aubin, J.-P. (2000). Applied Functional Analysis, 2nd edn. Wiley-Interscience, New York.CrossRefGoogle Scholar
Bielecki, T. R., Jin, H., Pliska, S. R. and Zhou, X. Y. (2005). Continuous-time mean-variance portfolio selection with bankruptcy prohibition. Math. Finance 15, 213244.CrossRefGoogle Scholar
Choulli, T., Krawczyk, L. and Stricker, C. (1998). E-martingales and their applications in mathematical finance. Ann. Prob. 26, 853876.CrossRefGoogle Scholar
Cvitanić, J. and Karatzas, I. (1992). Convex duality in constrained portfolio optimization. Ann. Appl. Prob. 2, 767818.CrossRefGoogle Scholar
Czichowsky, C. and Schweizer, M. (2011). Closedness in the semimartingale topology for spaces of stochastic integrals with constrained integrands. In Séminaire de Probabilités XLIII (Lecture Notes Math. 2006), Springer, Berlin, pp. 413436 CrossRefGoogle Scholar
Czichowsky, C. and Schweizer, M. (2012). Cone-constrained continuous-time Markowitz problems. To appear in Ann. Appl. Prob. CrossRefGoogle Scholar
Delbaen, F. (2006). The structure of m-stable sets and in particular of the set of risk neutral measures. In In memoriam Paul-André Meyer: Séminaire de Probabilités XXXIX (Lecture Notes Math. 1874), Springer, Berlin, pp. 215258.CrossRefGoogle Scholar
Delbaen, F. et al. (1997). Weighted norm inequalities and hedging in incomplete markets. Finance Stoch. 1, 181227.CrossRefGoogle Scholar
Ekeland, I. and Temam, R. (1976). Convex Analysis and Variational Problems. North-Holland, Amsterdam.Google Scholar
Föllmer, H. and Kramkov, D. (1997). Optional decompositions under constraints. Prob. Theory Relat. Fields 109, 125.CrossRefGoogle Scholar
Hou, C. and Karatzas, I. (2004). Least-squares approximation of random variables by stochastic integrals. In Stochastic Analysis and Related Topics in Kyoto (Adv. Stud. Pure Math. 41), Mathematical Society, Japan, Tokyo, pp. 141166.Google Scholar
Hu, Y. and Zhou, X. Y. (2005). Constrained stochastic LQ control with random coefficients, and application to portfolio selection. SIAM J. Control Optimization 44, 444466.CrossRefGoogle Scholar
Jin, H. and Zhou, X. Y. (2007). Continuous-time Markowitz's problems in an incomplete market, with no-shorting portfolios. In Stochastic Analysis and Applications (Abel Symp. 2), Springer, Berlin, pp. 435459.CrossRefGoogle Scholar
Karatzas, I. and Kardaras, C. (2007). The numéraire portfolio in semimartingale financial models. Finance Stoch. 11, 447493.CrossRefGoogle Scholar
Karatzas, I. and Shreve, S. E. (1998). Methods of Mathematical Finance (Appl. Math. 39). Springer, New York.Google Scholar
Karatzas, I. and Žitković, G. (2003). Optimal consumption from investment and random endowment in incomplete semimartingale markets. Ann. Prob. 31, 18211858.CrossRefGoogle Scholar
Kramkov, D. and Schachermayer, W. (1999). The asymptotic elasticity of utility functions and optimal investment in incomplete markets. Ann. Appl. Prob. 9, 904950.CrossRefGoogle Scholar
Labbé, C. and Heunis, A. J. (2007). Convex duality in constrained mean-variance portfolio optimization. Adv. Appl. Prob. 39, 77104.CrossRefGoogle Scholar
Mémin, J. (1980). Espaces de semi martingales et changement de probabilité. Z. Wahrscheinlichkeitsth. 52, 939.CrossRefGoogle Scholar
Mnif, M. and Pham, H. (2001). Stochastic optimization under constraints. Stoch. Process. Appl. 93, 149180.CrossRefGoogle Scholar
Pham, H. (2000). Dynamic L p -hedging in discrete time under cone constraints. SIAM J. Control Optimization 38, 665682.CrossRefGoogle Scholar
Pham, H. (2002). Minimizing shortfall risk and applications to finance and insurance problems. Ann. Appl. Prob. 12, 143172.CrossRefGoogle Scholar
Protter, P. E. (2005). Stochastic Integration and Differential Equations (Stoch. Modelling Appl. Prob. 21). Springer, Berlin.CrossRefGoogle Scholar
Rockafellar, R. T. (1970). Convex Analysis. (Princeton Math. Ser. 28). Princeton University Press, Princeton, NJ.CrossRefGoogle Scholar
Rockafellar, R. T. (1976). Integral functionals, normal integrands and measurable selections. In Nonlinear Operators and the Calculus of Variations (Lecture Notes Math. 543), Springer, Berlin, pp. 157207 CrossRefGoogle Scholar
Schweizer, M. (2001). A guided tour through quadratic hedging approaches. In Option Pricing, Interest Rates and Risk Management. Cambridge University Press, pp. 538574.CrossRefGoogle Scholar
Schweizer, M. (2010). Mean-variance hedging. In Encyclopedia of Quantitative Finance, ed. Cont, R., John Wiley, pp. 11771181.Google Scholar
Sun, W. G. and Wang, C. F. (2006). The mean-variance investment problem in a constrained financial market. J. Math. Econom. 42, 885895.CrossRefGoogle Scholar