Abstract
The constructive martingale representation theorem of functional Itô calculus is extended, from the space of square integrable martingales, to the space of local martingales. The setting is that of an augmented filtration generated by a Wiener process.
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References
Bally, V., Caramellino, L., Cont, R., Utzet, F., Vives, J.: Stochastic Integration by Parts and Functional Itô Calculus. Springer, Berlin (2016)
Benth, F.E., Di Nunno, G., Løkka, A., Øksendal, B., Proske, F.: Explicit representation of the minimal variance portfolio in markets driven by Lévy processes. Math. Financ. 13(1), 55–72 (2003)
Cont, R., Fournié, D.-A.: Change of variable formulas for non-anticipative functionals on path space. J. Funct. Anal. 259(4), 1043–1072 (2010)
Cont, R., Fournié, D.-A.: Functional Itô calculus and stochastic integral representation of martingales. Ann. Prob. 41(1), 109–133 (2013)
Cont, R., Lu, Y.: Weak approximation of martingale representations. Stoch. Process. Appl. 126(3), 857–882 (2016)
Detemple, J., Rindisbacher, M.: Closed-form solutions for optimal portfolio selection with stochastic interest rate and investment constraints. Math. Financ. 15(4), 539–568 (2005)
Nunno, Di G., Øksendal, B.: Optimal portfolio, partial information and Malliavin calculus. Stoch.: Int. J. Probab. Stoch. Process. 81(3–4), 303–322 (2009)
Karatzas, I., Ocone, D.L., Li, J.: An extension of Clark’s formula. Stoch.: Int. J. Probab. Stoch. Process. 37(3), 127–131 (1991)
Karatzas, I., Shreve, S.E.: Methods of Mathematical Finance (Stochastic Modelling and Applied Probability). Springer, Berlin (1998)
Lakner, P.: Optimal trading strategy for an investor: the case of partial information. Stoch. Process. Appl. 76(1), 77–97 (1998)
Lakner, P., Nygren, L.M.: Portfolio optimization with downside constraints. Math. Financ. 16(2), 283–299 (2006)
Levental, S., Schroder, M., Sinha, S.: A simple proof of functional Itô’s lemma for semimartingales with an application. Stat. Probab. Lett. 83(9), 2019–2026 (2013)
Lindensjö, K.: Optimal investment and consumption under partial information. Math. Meth. Oper. Res. 83(1), 87–107 (2016)
Lindensjö, K.: An Explicit Formula for Optimal Portfolios in Complete Wiener Driven Markets: a Functional Itô Calculus Approach (2017). arXiv:1610.05018
Malliavin, P.: Stochastic Analysis, Grundlehren der Mathematischen Wissenschaften, vol. 313, pp XII, 347. Springer, Berlin (2015)
Nualart, D.: The Malliavin Calculus and Related Topics (Probability and Its Applications, 2nd edn. Springer, Berlin (2006)
Ocone, D.L., Karatzas, I.: A generalized Clark representation formula, with application to optimal portfolios. Stoch.: Int. J. Probab. Stoch. Process. 34(3–4), 187–220 (1991)
Okur, Y.Y.: White noise generalization of the Clark-Ocone formula under change of measure. Stoch. Anal. Appl. 28(6), 1106–1121 (2010)
Pham, H., Quenez, M.-C.: Optimal portfolio in partially observed stochastic volatility models. Ann. Appl. Probab. 11(1), 210–238 (2001)
Rogers, L.C.G., Williams, D.: Diffusions, Markov Processes and Martingales, vol. 2, Itô calculus. Cambridge University Press, Cambridge (2000)
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The author is grateful to Mathias Lindholm for helpful discussions.
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Lindensjö, K. (2018). Constructive Martingale Representation in Functional Itô Calculus: A Local Martingale Extension. In: Silvestrov, S., Malyarenko, A., Rančić, M. (eds) Stochastic Processes and Applications. SPAS 2017. Springer Proceedings in Mathematics & Statistics, vol 271. Springer, Cham. https://doi.org/10.1007/978-3-030-02825-1_9
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