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Martingale decomposition of an L2 space with nonlinear stochastic integrals

Published online by Cambridge University Press:  11 December 2019

Clarence Simard*
Affiliation:
Université du Québec à Montréal
*
* Postal address: Département de Mathématiques, Université du Québec à Montréal, C.P. 8888, succ. Centre-ville, Montréal (Québec), H3C 3P8, Canada.

Abstract

This paper generalizes the Kunita–Watanabe decomposition of an $L^2$ space. The generalization comes from using nonlinear stochastic integrals where the integrator is a family of continuous martingales bounded in $L^2$ . This result is also the solution of an optimization problem in $L^2$ . First, martingales are assumed to be stochastic integrals. Then, to get the general result, it is shown that the regularity of the family of martingales with respect to its spatial parameter is inherited by the integrands in the integral representation of the martingales. Finally, an example showing how the results of this paper, with the Clark–Ocone formula, can be applied to polynomial functions of Brownian integrals.

Type
Research Papers
Copyright
© Applied Probability Trust 2019 

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References

Bank, P. and Baum, D. (2004). Hedging and portfolio optimization in illiquid financial markets with a large trader. Math. Finance 14, 118.CrossRefGoogle Scholar
Carmona, R. and Nualart, D. (1990). Nonlinear Stochastic Integrators, Equations and Flows, Vol. 6, Stochastic Monographs. Gordon and Breach, London.Google Scholar
Cetin, U., Jarrow, R. and Protter, P. (2004). Liquidity risk and arbitrage pricing theory. Finance Stoch. 8, 311341.CrossRefGoogle Scholar
Chitashvili, R. (1983). Martingale ideology in the theory of controlled stochastic processes. In Probability and Mathematical Statistics, eds. Prokhorov, J. V. and Itô, K., Springer, New York, pp. 7392.CrossRefGoogle Scholar
Chitashvili, R. and Mania, M. (1996). Characterization of a regular family of semimartingales by line integrals. Georgian Math. J. 3, 525542.CrossRefGoogle Scholar
Chitashvili, R. and Mania, M. (1999). Stochastic line integrals with respect to local martingales and semimartingales. Proc. Tbilisi A. Razmadze Math. Inst. 120, 126.Google Scholar
Kühn, C. (2012). Nonlinear stochastic integration with a non-smooth family of integrators. Stochastics 84, 3753.CrossRefGoogle Scholar
Kunita, H. (1990). Stochastic Flows and Stochastic Differential Equations, Vol. 24 of Cambridge Studies in Advanced Mathematics. Cambridge University Press.Google Scholar
Kunita, H. and Watanabe, S. (1967). On square integrable martingales. Nagoya Math. J. 30, 209245.CrossRefGoogle Scholar
Nualart, D. (2006). The Malliavin Calculus and Related Topics, 2nd edn. Springer, Berlin.Google Scholar
Schweizer, M. (1994). Approximating random variables by stochastic integrals. Ann. Prob. 22, 15361575.CrossRefGoogle Scholar
Williams, D. (1991). Probability with Martingales. Cambridge University Press.CrossRefGoogle Scholar