模糊环境中具有 w 个风险源的几何分形布朗运动下带有交易成本的几何亚洲电力期权定价

IF 2.1 2区 数学 Q1 MATHEMATICS, APPLIED Journal of Computational and Applied Mathematics Pub Date : 2024-07-24 DOI:10.1016/j.cam.2024.116165
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引用次数: 0

摘要

本文在具有 w 个风险源和模糊参数的分数几何布朗运动模型下,得到了计算具有浮动执行价格和交易成本的几何亚洲力量期权价格的明确公式。首先,通过考虑利兰定理和卡巴诺夫定理,我们推导出一个非线性 PDE 与交易成本公式,从而得到期权价格。然后,利用格林函数求出 PDE 的闭式解,并求得不同模型和期权参数量下的期权价格。接下来,我们将模型参数视为模糊数,并通过一般公式得到不同信念度和幂期权参数量下的期权价格区间。
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Geometric Asian power option pricing with transaction cost under the geometric fractional Brownian motion with w sources of risk in fuzzy environment

In this paper, we obtain an explicit formula to calculate the geometric Asian power option price with floating strike price and transaction cost under the fractional geometric Brownian motion model with w sources of risk and fuzzy parameters. First, by considering the Leland and Kabanov theorems, we derive a non-linear PDE with the transaction cost formula to obtain the option price. Then, using the Green function find a closed form solution for the PDE and achieve the price of the option under different amounts of the model and option parameters. Next, we consider the model’s parameters as fuzzy numbers and acquire a general formula to obtain intervals for the option price under different belief degrees and power option parameter amounts.

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来源期刊
CiteScore
5.40
自引率
4.20%
发文量
437
审稿时长
3.0 months
期刊介绍: The Journal of Computational and Applied Mathematics publishes original papers of high scientific value in all areas of computational and applied mathematics. The main interest of the Journal is in papers that describe and analyze new computational techniques for solving scientific or engineering problems. Also the improved analysis, including the effectiveness and applicability, of existing methods and algorithms is of importance. The computational efficiency (e.g. the convergence, stability, accuracy, ...) should be proved and illustrated by nontrivial numerical examples. Papers describing only variants of existing methods, without adding significant new computational properties are not of interest. The audience consists of: applied mathematicians, numerical analysts, computational scientists and engineers.
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