Loading...
Please wait, while we are loading the content...
Similar Documents
EasyChair Preprint No 301 Evolutionary Computation to Estimate Volatility
| Content Provider | Semantic Scholar |
|---|---|
| Author | Huamańı, Luis A. Navarro |
| Abstract | A performance evaluation study is implemented among the methods of Genetic Algorithms with Floating Point representation and some traditional optimization methods in the task of estimating the parameters of a GARCH (1,1) Normal process using artificial data obtained by simulation. The results show that the approximate solutions obtained by means of Genetic Algorithms present a better stability and precision with respect to the traditional optimization methods. The choice of the initial point in the numerical optimization methods is not a critical condition in the use of the Genetic Algorithms as a method to find the solution. Finally, the use of the method of Genetic Algorithms in the finding of the solution of the vector of parameters of the likelihood function of a model GARCH (1,1) t-Student for data of rates of exchange returns of the Sol versus the Dollar. keywords Genetic Algorithms, Statistical Inference, GARCH |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | https://easychair.org/publications/preprint_download/whc2 |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
