Solutions of Backward Stochastic Differential Equations on Markov Chains
By Samuel N. Cohen, Robert J. R. Elliott. 2008
93 citations recorded by the source corpus.
We consider backward stochastic differential equations (BSDEs) related to finite state, continuous time Markov chains. We show that appropriate solutions exist for arbitrary terminal conditions, and are unique up to sets of measure zero. We do not require the generating functions to be monotonic, instead using only an appropriate Lipschitz continuity condition.
Subfields: Demography, Finance
View Paper: https://www.semanticscholar.org/paper/39f3a1795e33d66dfbad439c12cf2cf6374733df
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In Demography
In Finance
- Samuel N. Cohen
- Robert J. R. Elliott
- Tomasz Klimsiak
- Tak Kuen Siu
- Guang-Hua Lian
- Alessandro Ramponi
- Leunglung Chan
- David Nualart
Citations in the corpus
- Comparisons for backward stochastic differential equations on Markov chains and related no-arbitrage conditions (2008, background): “We first extend the results of [4] to include the case where T , the terminal time of our BSDE, is an essentially bounded stopping time.”
- Backward stochastic Volterra integral equations and some related problems (2006, unknown): “Since 1990, there has appeared a large volume of literature published related to the theory and applications for BSDEs ([3,8,9,12,15,18,23] and references cited therein).”
- Existence and Comparisons for BSDEs in general spaces (2010, background): “When the filtration is generated by a Poisson random measure and a Brownian motion, as in [2] and others, or by a Markov chain, as in [4], [6], we have similar a similar reduction.”