存在非流动性和跳跃风险的不灵活套期保值

Yuan Gao, Yuheng Wu, Mingrui Duan
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引用次数: 2

摘要

现实世界中的市场不可避免地是不完整的,许多在完全市场假设下的精致模型在这种情况下都失败了。本文研究不完全市场下的套期保值问题。它处理不完备性的三个来源:不连续的资产价格、非流动性和离散的交易日期。提出了一个跳跃-扩散模型来描述资产动态。在此模型下,实现了三种具有三种损失函数的神经网络模型(RNN、LSTM、Mogrifier-LSTM)并进行了比较。所有的神经网络都显示出良好的结果,其中Mogrifier-LSTM是发散速度最快的模型。
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Inflexible Hedging in the Presence of Illiquidity and Jump Risks
Market in the real world is inevitably incomplete, and a lot of delicate models under the complete market assumption fails in such a scenario. This paper deals with the hedging problem in incomplete market. It deals with three sources of incompleteness: non-continuous asset prices, illiquidity, and discrete transaction dates. It proposes a jump-diffusion model to describe asset dynamics. Under this model, three neutral network models (RNN, LSTM, Mogrifier-LSTM) with three types of loss functions are implemented and compared. All neutral networks show promising results, and the Mogrifier-LSTM is the fastest model in diverging speed.
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