摘要
最优投资是期权定价中投资者面对的关键问题,投资者如何选择合适的执行价格和期权的有效期限,以使期权到期日的价格最高,是一个复杂的非线性连续优化问题;文章引入进化计算中的粒子群算法来解决这一问题,提出了一种基于粒子群的期权定价最优投资算法,为投资者提供有效的决策支持;针对Black-Scholes模型进行了算法的设计和实现,并以一个典型算例说明了该算法的有效性。
Investment optimization is a key problem in the option pricing. It is a complicated non-linear continuous optimization problem to select the optimal strike price and expiration time in order to maximize the option price. This paper introduces a kind of evolving calculation method, particle swarm optimization, to solve the problem, and presents an investment optimization algorithm for option pricing, which can provide decision support for investors. Based on the Elack-Scholes model, the algorithm is designed and realized. Finally, a typical simulation study is carried out to illustrate the validity of the algorithm.
出处
《合肥工业大学学报（自然科学版）》
CAS
CSCD
北大核心
2008年第11期1825-1827,1836,共4页
Journal of Hefei University of Technology：Natural Science
基金
国家自然科学基金资助项目(60474035)
安徽省自然科学基金资助项目(070412035)
关键词
期权定价
投资
粒子群算法
option pricing
investment
particle swarm optimization（PSO）
