Statistical Inference on a Black-Scholes Model with Jumps. Application in Hydrology

J. Césars, S. P. Nuiro, J. Vaillant
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引用次数: 2

Abstract

We consider a Stochastic Differential Equation (SDE) driven by a Wiener process and a Poisson measure. This latter measure is associated with a sequence of identically distributed jump amplitudes. Properties of the SDE solution are presented with respect to the associated Wiener and Poisson processes. An algorithm is provided allowing exact numerical simulations of such SDE and implementable within R environment. Statistical inference tools are presented and applied to hydrology data.
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具有跳跃的Black-Scholes模型的统计推断。在水文学中的应用
我们考虑一个由维纳过程和泊松测度驱动的随机微分方程。后一种测量方法与一系列相同分布的跳跃幅度相关联。关于相关的维纳过程和泊松过程,给出了SDE解的性质。提供了一种算法,可以精确地对这种SDE进行数值模拟,并在R环境中实现。提出了统计推断工具,并将其应用于水文数据。
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CiteScore
0.70
自引率
33.30%
发文量
0
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