Neural Networks for Estimating Speculative Attacks Models
Currency crises have been analyzed and modeled over the last few decades. These currency crises develop mainly due to a balance of payments crisis, and in many cases, these crises lead to speculative attacks against the price of the currency. Despite the popularity of these models, they are currentl...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2021-01-01
|
| Series: | Entropy |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1099-4300/23/1/106 |
| _version_ | 1797412129107607552 |
|---|---|
| author | David Alaminos Fernando Aguilar-Vijande José Ramón Sánchez-Serrano |
| author_facet | David Alaminos Fernando Aguilar-Vijande José Ramón Sánchez-Serrano |
| author_sort | David Alaminos |
| collection | DOAJ |
| description | Currency crises have been analyzed and modeled over the last few decades. These currency crises develop mainly due to a balance of payments crisis, and in many cases, these crises lead to speculative attacks against the price of the currency. Despite the popularity of these models, they are currently shown as models with low estimation precision. In the present study, estimates are made with first- and second-generation speculative attack models using neural network methods. The results conclude that the Quantum-Inspired Neural Network and Deep Neural Decision Trees methodologies are shown to be the most accurate, with results around 90% accuracy. These results exceed the estimates made with Ordinary Least Squares, the usual estimation method for speculative attack models. In addition, the time required for the estimation is less for neural network methods than for Ordinary Least Squares. These results can be of great importance for public and financial institutions when anticipating speculative pressures on currencies that are in price crisis in the markets. |
| first_indexed | 2024-03-09T04:57:37Z |
| format | Article |
| id | doaj.art-e285b0d2cf964c2294c57f9e8c217687 |
| institution | Directory Open Access Journal |
| issn | 1099-4300 |
| language | English |
| last_indexed | 2024-03-09T04:57:37Z |
| publishDate | 2021-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Entropy |
| spelling | doaj.art-e285b0d2cf964c2294c57f9e8c2176872023-12-03T13:04:32ZengMDPI AGEntropy1099-43002021-01-0123110610.3390/e23010106Neural Networks for Estimating Speculative Attacks ModelsDavid Alaminos0Fernando Aguilar-Vijande1José Ramón Sánchez-Serrano2Department of Financial Management, Universidad Pontificia Comillas, 28015 Madrid, SpainPhD in Economics and Business, Universidad de Málaga, 29071 Málaga, SpainDepartment of Finance and Accounting, Universidad de Málaga, 29071 Málaga, SpainCurrency crises have been analyzed and modeled over the last few decades. These currency crises develop mainly due to a balance of payments crisis, and in many cases, these crises lead to speculative attacks against the price of the currency. Despite the popularity of these models, they are currently shown as models with low estimation precision. In the present study, estimates are made with first- and second-generation speculative attack models using neural network methods. The results conclude that the Quantum-Inspired Neural Network and Deep Neural Decision Trees methodologies are shown to be the most accurate, with results around 90% accuracy. These results exceed the estimates made with Ordinary Least Squares, the usual estimation method for speculative attack models. In addition, the time required for the estimation is less for neural network methods than for Ordinary Least Squares. These results can be of great importance for public and financial institutions when anticipating speculative pressures on currencies that are in price crisis in the markets.https://www.mdpi.com/1099-4300/23/1/106speculative attackscurrency crisisneural networksdeep learningQuantum-Inspired Neural Network |
| spellingShingle | David Alaminos Fernando Aguilar-Vijande José Ramón Sánchez-Serrano Neural Networks for Estimating Speculative Attacks Models Entropy speculative attacks currency crisis neural networks deep learning Quantum-Inspired Neural Network |
| title | Neural Networks for Estimating Speculative Attacks Models |
| title_full | Neural Networks for Estimating Speculative Attacks Models |
| title_fullStr | Neural Networks for Estimating Speculative Attacks Models |
| title_full_unstemmed | Neural Networks for Estimating Speculative Attacks Models |
| title_short | Neural Networks for Estimating Speculative Attacks Models |
| title_sort | neural networks for estimating speculative attacks models |
| topic | speculative attacks currency crisis neural networks deep learning Quantum-Inspired Neural Network |
| url | https://www.mdpi.com/1099-4300/23/1/106 |
| work_keys_str_mv | AT davidalaminos neuralnetworksforestimatingspeculativeattacksmodels AT fernandoaguilarvijande neuralnetworksforestimatingspeculativeattacksmodels AT joseramonsanchezserrano neuralnetworksforestimatingspeculativeattacksmodels |