Practical arbitrage‐free scenario tree reduction methods and their applications in financial optimization

Zhiping Chen and Zhe Yan

Applied Stochastic Models in Business and Industry, 2018, vol. 34, issue 2, 175-195

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.

Date: 2018
References: Add references at CitEc
Citations:

Downloads: (external link)
https://doi.org/10.1002/asmb.2290

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:wly:apsmbi:v:34:y:2018:i:2:p:175-195

Access Statistics for this article

More articles in Applied Stochastic Models in Business and Industry from John Wiley & Sons
Bibliographic data for series maintained by Wiley Content Delivery ().