具有特殊噪声的金融资产定价的正反向随机模型

Pavel Levin
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引用次数: 0

摘要

考虑边际投资者的信念和行为,提出了一种新的可接受价格方法来确定给定水平下的随机端点。对于风险中性概率测度下的可接受资产价格,建立了FBSDE定义随机动力学的双边过滤,其中目标价格分布以活跃市场主体子集参数的平均值为特征。对于市场均衡时的当前价格,找到了风险分配的可接受价格。确定了均衡条件下的隐含波动率与预测效用和流动性溢价的依赖关系。得到了正反向随机问题的一般解和期权随机终端条件公式的部分解。对模拟特殊噪声的深度学习算法进行了测试。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Forward Backward Stochastic Model of Financial Asset Pricing with Idiosyncratic Noise
A new acceptable price approach to stochastic endpoint determination at given horizon accounting for the marginal investor beliefs and behaviour was proposed. Two-sided filtration with FBSDE defined stochastic dynamics was formulated for acceptable asset price under the risk-neutral probability measure, at that the target price distribution is characterized by the averaged over active market agent subset parameters. For the current price at market equilibrium, the acceptable price of risk distribution was found. The implied volatility dependencies for the equilibrium conditions and with predicted utility and liquidity premiums were determined. A generalized solution for the forward-backward stochastic problem and a partial solution for the formulated for options stochastic terminal conditions were found. The deep learning algorithm with simulated idiosyncratic noise was tested.
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