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Backward stochastic differential equations on manifolds. (English) Zbl 1085.60037

The main problem of the paper is to find a martingale on a manifold with a fixed random terminal value; this can be done by solving a backward SDE with quadratic growth (which means, that classical Lipschitz conditions etc.for existence and uniqueness of solutions fail). Let \(M\) be a manifold with connection \(\Gamma\) and a related exponential map \(\exp\). The author considers the following backward stochastic differential equation (in infinitesimal form):
\[ X_{t+dt} = \exp_{X_t}(Z_t dW_t + f(B_t^y, X_t, Z_t)dt), \quad X_T = U, \]
where \(W_t\) is \(d\)-dimensional Brownian motion. Assuming that \(M\) can be represented by a global chart, this becomes \[ dX_t = Z_t dW_t + (-\tfrac 12 \Gamma_{jk}(X_t)\langle [Z_t]^k , [Z_t]^j\rangle + f(B_t^y, X_t, Z_t)\,dt), \quad X_T =U, \] \([Z_t]^k\) denotes the \(k\)th row of the matrix \(Z_t\). The main result of the paper is the following: Let \(\omega\) be a relatively compact open subset of an open set \(O\subset M\), where \(O\) is such that there is a unique \(O\)-valued geodesic between any two points of \(O\). If \(f\) is outward pointing on the boundary of \(\bar\omega\), if \(U\in\bar\omega = \{\chi\leq c\}\) with a strictly convex \(\chi\) and if \(f\) satisfies some further technical conditions, then (i) the above backward SDE has a unique solution \((Z_t,X_t)_{0\leq t\leq T}\) such that \(X_t\) remains in \(\bar \omega\) if \(f\) does not depend on \(z\); (ii) if \(M\) is a Cartan-Hadamard manifold and if the Levi-Cività connection is being used, then the solution of the backward SDE has a unique solution \((Z_t,X_t)_{0\leq t\leq T}\) with \(X\) in \(\bar\omega\).

MSC:

60H10 Stochastic ordinary differential equations (aspects of stochastic analysis)
58J65 Diffusion processes and stochastic analysis on manifolds
60J60 Diffusion processes
60J65 Brownian motion

References:

[1] Arnaudon, Probab. Theory Relat. Fields, 108, 219 (1997) · Zbl 0883.60043 · doi:10.1007/s004400050108
[2] Barles, G.; Lesigne, E., SDE, BSDE and PDE. Backward stochastic differential equations (Paris 1995-1996), Pitman Res. Notes Math. Ser., 364, 47-80 (1997) · Zbl 0886.60049
[3] Boothby, W.M.: An introduction to differentiable manifolds and Riemannian geometry, vol 120 of Pure and Applied Mathematics, Academic Press, 1986 · Zbl 0596.53001
[4] Briand, Appl. Math. Stochastic Anal., 13, 207 (2000) · Zbl 0979.60046
[5] Darling, R.W.R.: Martingales in manifolds - definition, examples and behaviour under maps. In: Séminaire de Probabilités XVI, vol 921 of Lecture Notes in Mathematics, Springer-Verlag, 1982 · Zbl 0482.58035
[6] Darling, The Annals of Probability, 23, 1234 (3)
[7] Darling, The Annals of Probability, 25, 1135 (3)
[8] Eells, The Bulletin of the London Mathematical Society, 10, 1 (1978) · Zbl 0401.58003
[9] Eells, J.; Sampson, J. H., Harmonic mappings of Riemannian manifolds, Am. J. Math., LXXXVI, 109-160 (1964) · Zbl 0122.40102
[10] Emery, M.: Stochastic calculus in manifolds. Universitext Springer-Verlag, New York/Berlin, 1989 · Zbl 0697.60060
[11] Estrade, A., Pontier, M.: Backward stochastic differential equations in a Lie group. In: Séminaire de Probabilités XXXV, vol 1755 of Lecture Notes in Mathematics, Springer-Verlag, 2001 · Zbl 0980.60085
[12] Hamadene, Ann. Inst. H. Poincaré Probab. Statist., 32, 645 (5) · Zbl 0893.60031
[13] Hélein, F.: Applications harmoniques, lois de conservation et repères mobiles. Nouveaux essais. Diderot Editeur Arts et Sciences, 1996 · Zbl 0920.58022
[14] Hsu, E.P.: Stochastic analysis on manifolds, vol 38, of Graduate Studies in Mathematics. American Mathematical Society, 2002 · Zbl 0994.58019
[15] Kendall, W.S.: Probability, convexity and harmonic maps with small image I: uniqueness and fine existence. Proceedings of the London Mathematical Society (3), 61, 371-406 (1990) · Zbl 0675.58042
[16] Kendall, W. S., Convexity and the hemisphere, Journal of the London Mathematical Society (2), 43, 567-576 (1991) · Zbl 0688.58001
[17] Kendall, Journal of Functional Analysis, 126, 228 (1994) · Zbl 0808.60058 · doi:10.1006/jfan.1994.1147
[18] Kobylanski, The Annals of Probability, 28, 558 (2) · Zbl 1044.60045 · doi:10.1214/aop/1019160253
[19] Lee, J.M.: Riemannian manifolds : an introduction to curvature, vol 176, of Graduate Texts in Mathematics, Springer, 1997 · Zbl 0905.53001
[20] Lepeltier, Statistics & Probability Letters,, 32, 425 (1997) · Zbl 0904.60042
[21] Peng, Math. Finance, 7, 1 (1)
[22] Hu, Stochastic Process. Appl., 108, 109 (1)
[23] Pardoux, E.: BSDEs, weak convergence and homogenization of semilinear PDEs. Nonlinear analysis differential equations and control (Montreal QC 1998), 1999, pp. 503-549 · Zbl 0959.60049
[24] Pardoux, Systems & Control Letters, 14, 55 (1990) · Zbl 0692.93064
[25] Pardoux, Lecture Notes in CIS, 176, 200 (1992)
[26] Peng, Stochastics and Stochastics Reports, 37, 61 (1991) · Zbl 0739.60060
[27] Picard, J.: Martingales sur le cercle. In: Séminaire de Probabilités XXIII, vol 1372, of Lecture Notes in Mathematics, Springer-Verlag, 1989 · Zbl 0743.60047
[28] Picard, J.: Martingales on Riemannian manifolds with prescribed limit. Journal of Functional Analysis 99 (2), August 1991 · Zbl 0758.60051
[29] Picard, Ann. Inst. H. Poincaré Probab. Statist., 30, 647 (4) · Zbl 0817.58047
[30] Tang, SIAM J. Control Optim., 42, 53 (2003) · Zbl 1035.93065 · doi:10.1137/S0363012901387550
[31] Thalmaier, Probab. Theory Relat. Fields, 105, 335 (1996) · Zbl 0846.58056
[32] Thalmaier, A.: Martingales on Riemannian manifolds and the nonlinear heat equation. In: Stochastic Analysis and Applications. Proc. of the Fifth Gregynog Symposium, 1996 pp. 429-440 · Zbl 0927.58020
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