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We propose a numerical recipe for risk evaluation defined by a backward stochastic differential equation.
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Detlefsen, K., Scandolo, G., Conditional and Dynamic Convex Risk Measures, Finance and Stochastics, volume 9, 539-561, 2005
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Gobet, E., Lemor, J.-P., and Warin, X., A regression-based Monte Carlo method to solve backward stochastic differential equations , The Annals of Applied Probability 15.3 (2005): 2172-2202
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Convex risk measures and the dynamics of their penalty functions,
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Composition of time-consistent dynamic monetary risk measures in discrete time ,
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BSDEs with jumps, optimization and applications to dynamic risk measures,
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Robust portfolio choice and indifference valuation ,
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Ruszczyński, A., Yao, J., A Risk-Averse Analog of the Hamilton-Jacobi-Bellman Equation, SIAM Control and Its Application Conference Proceedings, 2015
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Gobet, E., and Turkedjiev, P., Linear regression MDP scheme for discrete backward stochastic differential equations under general conditions , Mathematics of Computation, 85(299), 1359-1391, 2016
2016
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Zhang, J., Backward Stochastic Differential Equations, Springer, New York, 2017
2017
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Hu, Y., Ni, B., Ruszczyński, A., Yao, J., Numerical Methods for Forward-Backward Stochastic Differential Equations with Application to Risk-Averse Option Portfolio Valuation , technical report, Rutgers University, November, 2018
2018
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