A PRIMAL-DUAL ALGORITHM FOR BSDES

被引：20
|
作者：
Bender, Christian [1 ]
Schweizer, Nikolaus [1 ]
Zhuo, Jia [2 ]
机构：
[1] Saarland Univ, Saarbrucken, Germany
[2] Univ Southern Calif, Los Angeles, CA USA
来源：
MATHEMATICAL FINANCE | 2017年 / 27卷 / 03期
关键词：
BSDE; numerical approximation; Monte Carlo; option pricing; STOCHASTIC DIFFERENTIAL-EQUATIONS; DISCRETE-TIME APPROXIMATION; OPTIMAL STOPPING PROBLEMS; MONTE-CARLO; AMERICAN OPTIONS; BERMUDAN PRODUCTS; BACKWARD SDES; UPPER-BOUNDS; SIMULATION; VALUATION;
D O I：
10.1111/mafi.12100
中图分类号：
F8 [财政、金融];
学科分类号：
0202 ;
摘要：
We generalize the primal-dual methodology, which is popular in the pricing of early-exercise options, to a backward dynamic programming equation associated with time discretization schemes of (reflected) backward stochastic differential equations (BSDEs). Taking as an input some approximate solution of the backward dynamic program, which was precomputed, e.g., by least-squaresMonte Carlo, this methodology enables us to construct a confidence interval for the unknown true solution of the time-discretized (reflected) BSDE at time 0. We numerically demonstrate the practical applicability of our method in two 5-dimensional nonlinear pricing problems where tight price bounds were previously unavailable.
引用
收藏
页码：866 / 901
页数：36
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