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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...
Metropolis sampling is the earliest Markov chain Monte Carlo (MCMC) method and MCMC has been widely used in motif-finding via sequence local alignment. A key issue in the design of MCMC algorithms is to improve the proposal mechanism and the mixing behavior. To overcome these difficulties, it is common either to run a population of chains or incorporate the evolutionary computing techniques into the...
This article is an extension of the work presented earlier, which compared and analyzed the economics of alternative maintenance plans. The proposed model combines genetic algorithms with Monte Carlo simulation to arrive at the most economic investment timing. The approach described earlier was characterized by a very long computing time making it difficult to use. This paper addresses several issues...
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