Optimal Posting of Collateral with Recurrent Neural Networks

P. Henry-Labordère
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Abstract

In this paper, we consider the problem of optimal posting of collateral in two assets. The associated stochastic control problem is then solved by parameterizing the optimal control with a (recurrent) neural network. Then, the training of the neural network is achieved with a back-propagation algorithm, possibly complemented with a particle swarm optimization (or simulated annealing). Our algorithm is then illustrated with numerical examples.
递归神经网络优化投寄抵押品
本文研究了两种资产的最优质押问题。然后通过(循环)神经网络参数化最优控制来解决相关的随机控制问题。然后,通过反向传播算法实现神经网络的训练,可能辅以粒子群优化(或模拟退火)。然后用数值算例说明了我们的算法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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