用神经网络增强非线性扩散的路径积分近似法

Anna Knezevic
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引用次数: 0

摘要

在 Black-Karasinski 模型结构下,利用神经网络在不同参数化点上增强固定收益工具定价的现有解决方案,以证明该方法能够在扩展投影范围内的多重校准中取得更佳结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Enhancing path-integral approximation for non-linear diffusion with neural network
Enhancing the existing solution for pricing of fixed income instruments within Black-Karasinski model structure, with neural network at various parameterisation points to demonstrate that the method is able to achieve superior outcomes for multiple calibrations across extended projection horizons.
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