经典期权定价及其进一步发展

Victor Olkhov
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引用次数: 7

摘要

本文在修正经典期权定价模型的基础上,对Black-Scholes-Merton方程进行了进一步的推广。我们将价格视为市场交易的成本与交易量之比,并将经典的随机布朗运动假设应用于成本和交易量而不是价格。这种简单的替换产生了具有两个恒定波动率的二维bsm类方程。我们认为,成本和市场交易量的决策是在代理人的预期下做出的。预期的随机扰动影响市场交易,并通过它们诱发基础价格的随机行为。我们导出了由agent期望的布朗运动驱动的类bsm方程。代理人期望可以基于期权交易数据。我们展示了这样的期望如何导致非线性bsm样方程。进一步,我们证明了赫斯顿随机波动率期权定价模型可以应用于我们的逼近,并作为例子推导了三维bsm式方程,该方程描述了随机成本波动率和恒定量波动率的期权定价。2 - 5维或更多维类bsm方程的多样性强调了期权定价问题的复杂性。这种多样性说明了资产和期权价格描述的准确性与所考虑的方程的复杂性之间的合理平衡问题。我们希望本文推导的一些类bsm方程对资产和期权市场建模的进一步发展有所帮助。
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Classical Option Pricing and Some Steps Further
This paper modifies single assumption in the base of classical option pricing model and derives further extensions for the Black-Scholes-Merton equation. We regard the price as the ratio of the cost and the volume of market transaction and apply classical assumptions on stochastic Brownian motion not to the price but to the cost and the volume. This simple replacement leads to 2-dimensional BSM-like equation with two constant volatilities. We argue that decisions on the cost and the volume of market transactions are made under agents expectations. Random perturbations of expectations impact the market transactions and through them induce stochastic behavior of the underlying price. We derive BSM-like equation driven by Brownian motion of agents expectations. Agents expectations can be based on option trading data. We show how such expectations can lead to nonlinear BSM-like equations. Further we show that the Heston stochastic volatility option pricing model can be applied to our approximations and as example derive 3-dimensional BSM-like equation that describes option pricing with stochastic cost volatility and constant volume volatility. Diversity of BSM-like equations with 2 – 5 or more dimensions emphasizes complexity of option pricing problem. Such variety states the problem of reasonable balance between the accuracy of asset and option price description and the complexity of the equations under consideration. We hope that some of BSM-like equations derived in this paper may be useful for further development of assets and option market modeling.
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