TAC Method for Fitting Exponential Autoregressive Models and Others: Applications in Economy and Finance
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arXiv
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| Autores principales: | , , |
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| Formato: | Preprint |
| Publicado: |
2024
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| _version_ | 1866913225034956800 |
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| author | Sánchez, Javier Cabello Torvisco, Juan Antonio Fernández Arias, Mariano R. |
| author_facet | Sánchez, Javier Cabello Torvisco, Juan Antonio Fernández Arias, Mariano R. |
| contents | There are a couple of purposes in this paper: to study a problem of approximation with exponential functions and to show its relevance for the economic science. We present results that completely solve the problem of the best approximation by means of exponential functions and we will be able to determine what kind of data is suitable to be fitted. Data will be approximated using TAC (implemented in the R-package nlstac), a numerical algorithm for fitting data by exponential patterns without initial guess designed by the authors. We check one more time the robustness of this algorithm by successfully applying it to two very distant areas of economy: demand curves and nonlinear time series. This shows TAC's utility and highlights how far this algorithm could be used. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2402_04138 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | TAC Method for Fitting Exponential Autoregressive Models and Others: Applications in Economy and Finance Sánchez, Javier Cabello Torvisco, Juan Antonio Fernández Arias, Mariano R. Numerical Analysis Statistical Finance There are a couple of purposes in this paper: to study a problem of approximation with exponential functions and to show its relevance for the economic science. We present results that completely solve the problem of the best approximation by means of exponential functions and we will be able to determine what kind of data is suitable to be fitted. Data will be approximated using TAC (implemented in the R-package nlstac), a numerical algorithm for fitting data by exponential patterns without initial guess designed by the authors. We check one more time the robustness of this algorithm by successfully applying it to two very distant areas of economy: demand curves and nonlinear time series. This shows TAC's utility and highlights how far this algorithm could be used. |
| title | TAC Method for Fitting Exponential Autoregressive Models and Others: Applications in Economy and Finance |
| topic | Numerical Analysis Statistical Finance |
| url | https://arxiv.org/abs/2402.04138 |