Cuckoo Search Optimization for Black Scholes Option Pricing

Manas Shah

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Cuckoo Search Optimization for Black Scholes Option Pricing

机译：布谷鸟搜索为Black Scholes期权定价优化

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Black Scholes option pricing model is one of the most important concepts in modern world of computational finance. However, its practical use can be challenging as one of the input parameters must be estimated; implied volatility of the underlying security. The more precisely these values are estimated, the more accurate their corresponding estimates of theoretical option prices would be. Here, we present a novel model based on Cuckoo Search Optimization (CS) which finds more precise estimates of implied volatility than Particle Swarm Optimization (PSO) and Genetic Algorithm (GA).

机译：Black Scholes期权定价模型是现代计算金融领域最重要的概念之一。但是，由于必须估计其中一个输入参数，因此其实际使用可能具有挑战性。隐含证券的波动性。这些值估计得越精确，它们对理论期权价格的相应估计就越准确。在这里，我们提出了一种基于杜鹃搜索优化（CS）的新颖模型，该模型比粒子群优化（PSO）和遗传算法（GA）可以找到更精确的隐含波动率估计。

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《International Journal of Swarm Intelligence and Evolutionary Computation》 |2015年第2期|共4页
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Manas Shah;
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中图分类自动化技术、计算机技术;
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Cuckoo Search Optimization for Black Scholes Option Pricing

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