DocumentCode
2669096
Title
Using Genetic algorithms and Monte Carlo to price convertible bond
Author
Li, Lin ; Wang, Lele
Author_Institution
Sch. of Bus., East China Univ. of Sci. & Technol., Shanghai, China
fYear
2010
fDate
17-19 Sept. 2010
Firstpage
369
Lastpage
372
Abstract
The aim of paper is to use Genetic algorithm and Monte Carlo to price convertible bond with finite maturity. As we known, Monte Carlo is hardly applied to price the derivatives with optimal items. Combined with Genetic algorithm and Cubic sample function, Monte Carlo not only solves the convertible bond with optimal conversion items, but also prices that with long-range dependence property. By evaluating the controlling points of cubic sample function, the optimal convertible boundary is showed. Furthermore, the proposed method can be applied to price derivatives with optimal items, such as American option and optimal investment with muti-risky assets.
Keywords
Monte Carlo methods; genetic algorithms; investment; pricing; stock markets; Monte Carlo method; cubic sample function; finite maturity; genetic algorithm; long range dependence property; muti-risky asset; optimal investment; price convertible bond; Biological system modeling; Brownian motion; Computational modeling; Genetics; Monte Carlo methods; Pricing; Prototypes; Conversion item; Genetic Algorithm; Monte Carlo; convertible bond;
fLanguage
English
Publisher
ieee
Conference_Titel
Information and Financial Engineering (ICIFE), 2010 2nd IEEE International Conference on
Conference_Location
Chongqing
Print_ISBN
978-1-4244-6927-7
Type
conf
DOI
10.1109/ICIFE.2010.5609380
Filename
5609380
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