Name
Title | ||
|---|---|---|
An auto-realignment method in quasi-Monte Carlo for pricing financial derivatives with jump structures. |
Abstract | ||
|---|---|---|
•The idea of machine learning is introduced to the QMC area.•A new path generation method called the auto-realignment method is proposed.•The k-means clustering algorithm is used to select representative normal vectors.•Experiments demonstrate the efficiency and robustness of the proposed method. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1016/j.ejor.2016.03.034 | European Journal of Operational Research |
Keywords | Field | DocType |
Pricing,QMC,OT method,QR decomposition,Auto-realignment method | Mathematical optimization,Classification of discontinuities,Discontinuity (linguistics),Quasi-Monte Carlo method,Cluster analysis,Jump,Derivative (finance),Mathematics,QR decomposition | Journal |
Volume | Issue | ISSN |
254 | 1 | 0377-2217 |
Citations | PageRank | References |
1 | 0.40 | 6 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Chengfeng Weng | 1 | 5 | 0.91 |
| Xiaoqun Wang | 2 | 404 | 34.39 |
| Zhijian He | 3 | 13 | 2.94 |