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Practical arbitrage‐free scenario tree reduction methods and their applications in financial optimization
Authors:Zhiping Chen  Zhe Yan
Affiliation:Department of Computing Science, School of Mathematics and Statistics, Xi'an Jiaotong University, Xi'an, Shaanxi, PR China
Abstract:We construct an arbitrage‐free scenario tree reduction model, from which some arbitrage‐free scenario tree reduction algorithms are designed. They ensure that the reduced scenario trees are arbitrage free. Numerical results show the practicality and efficiency of the proposed algorithms. Results for multistage portfolio selection problems demonstrate the necessity and importance for guaranteeing that the reduced scenario trees are arbitrage free, as well as the practicality of the proposed arbitrage‐free scenario tree reduction algorithms for financial optimization.
Keywords:arbitrage free  portfolio selection  scenario tree reduction  stochastic programs
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