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A Hybrid Particle Swarm Optimization-Nelder- Mead Algorithm (PSO-NM) for Nelson-Siegel- Svensson Calibration
| Content Provider | Semantic Scholar |
|---|---|
| Author | Ayouche, Sofia Ellaia, Rachid Aboulaich, Rajae |
| Copyright Year | 2016 |
| Abstract | Today, insurers may use the yield curve as an indicator evaluation of the profit or the performance of their portfolios; therefore, they modeled it by one class of model that has the ability to fit and forecast the future term structure of interest rates. This class of model is the Nelson-Siegel-Svensson model. Unfortunately, many authors have reported a lot of difficulties when they want to calibrate the model because the optimization problem is not convex and has multiple local optima. In this context, we implement a hybrid Particle Swarm optimization and Nelder Mead algorithm in order to minimize by least squares method, the difference between the zero-coupon curve and the NSS curve. Keywords—Optimization, zero-coupon curve, Nelson-SiegelSvensson, Particle Swarm Optimization, Nelder-Mead Algorithm. |
| Starting Page | 1365 |
| Ending Page | 1369 |
| Page Count | 5 |
| File Format | PDF HTM / HTML |
| Volume Number | 10 |
| Alternate Webpage(s) | http://waset.org/publications/10004553/a-hybrid-particle-swarm-optimization-nelder-mead-algorithm-pso-nm-for-nelson-siegel-svensson-calibration |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
