金融资产定价双边过滤模型中的瞬时和平均波动性

Pavel Levin
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引用次数: 0

摘要

提出了一种基于边际投资者信念和羊群行为定义的平均历史波动率和瞬时波动率的双因素资产定价方法。对于双侧过滤,风险中性概率测度下的后向SDE定义的随机动力学由给定水平的目标价格分布确定,参数在活跃市场主体的子集上平均。对于市场均衡和瞬时波动的当前价格,得到了风险可接受价格的分布。所发现的隐含波动率对行权和到期日的依赖性与Carr和Wu(2016)的期权历史数据相对应。得出债券和期权的流动性折扣。给出了FBSDE的广义解和随机终端条件的部分解。所开发的双因素方法非常适合于深度学习定价算法。
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Instantaneous and Averaged Volatility in Two-Side Filtration Model of Financial Asset Pricing
A two-factor approach to asset pricing based on averaged historical and instantaneous volatility defined by a marginal investor’s beliefs and herding behaviour is proposed. For the two-side filtration, backward SDE-defined stochastic dynamics under the risk-neutral probability measure are determined by a target price distribution at given horizon with parameters averaged over a subset of active market agents. For the current price at market equilibrium and instantaneous volatility, the distribution of acceptable price of risk is obtained. The found implied volatility dependencies on strike and maturity are corresponding to the historical data for options by Carr and Wu (2016). The liquidity discount for bonds and options is derived. A generalized solution for the FBSDE and a partial solution for the stochastic terminal conditions are found. The developed two-factor approach is well-suited to deep learning pricing algorithms.
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审稿时长
24 weeks
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