Option pricing with the product constrained hybrid neural network

被引:0
|
作者
Lajbcygier, P [1 ]
机构
[1] Monash Univ, Sch Business Syst, Clayton, Vic 3168, Australia
关键词
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
It is well known that conventional option pricing models have systematic, statistically and economically significant errors or residuals. In this work an artificial neural network (ANN), which estimates the residuals from the most accurate conventional option pricing model, so as to improve option pricing accuracy, is constrained in such a way so that pricing must be rational at the option-pricing boundaries. These constraints lead to statistically and economically significant out-performance relative to both the most accurate conventional and non-constrained ANN option pricing models.
引用
收藏
页码:615 / 621
页数:7
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