Influence of Transfer Entropy in the Short-Term Prediction of Financial Time Series Using an ∊-Machine
Predicting the values of a financial time series is mainly a function of its price history, which depends on several factors, internal and external. With this history, it is possible to build an ∊-machine for predicting the financial time series. This work proposes considering the influence of a fin...
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| Language: | English |
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MDPI AG
2022-07-01
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| Series: | Entropy |
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| Online Access: | https://www.mdpi.com/1099-4300/24/8/1049 |
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| author | José Crispín Zavala-Díaz Joaquín Pérez-Ortega Nelva Nely Almanza-Ortega Rodolfo Pazos-Rangel José María Rodríguez-Lelís |
| author_facet | José Crispín Zavala-Díaz Joaquín Pérez-Ortega Nelva Nely Almanza-Ortega Rodolfo Pazos-Rangel José María Rodríguez-Lelís |
| author_sort | José Crispín Zavala-Díaz |
| collection | DOAJ |
| description | Predicting the values of a financial time series is mainly a function of its price history, which depends on several factors, internal and external. With this history, it is possible to build an ∊-machine for predicting the financial time series. This work proposes considering the influence of a financial series through the transfer of entropy when the values of the other financial series are known. A method is proposed that considers the transfer of entropy for breaking the ties that occur when calculating the prediction with the ∊-machine. This analysis is carried out using data from six financial series: two American, the S&P 500 and the Nasdaq; two Asian, the Hang Seng and the Nikkei 225; and two European, the CAC 40 and the DAX. This work shows that it is possible to influence the prediction of the closing value of a series if the value of the influencing series is known. This work showed that the series that transfer the most information through entropy transfer are the American S&P 500 and Nasdaq, followed by the European DAX and CAC 40, and finally the Asian Nikkei 225 and Hang Seng. |
| first_indexed | 2024-03-09T04:30:14Z |
| format | Article |
| id | doaj.art-cf7a280f9bde465d8fd8031148d746b7 |
| institution | Directory Open Access Journal |
| issn | 1099-4300 |
| language | English |
| last_indexed | 2024-03-09T04:30:14Z |
| publishDate | 2022-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Entropy |
| spelling | doaj.art-cf7a280f9bde465d8fd8031148d746b72023-12-03T13:36:54ZengMDPI AGEntropy1099-43002022-07-01248104910.3390/e24081049Influence of Transfer Entropy in the Short-Term Prediction of Financial Time Series Using an ∊-MachineJosé Crispín Zavala-Díaz0Joaquín Pérez-Ortega1Nelva Nely Almanza-Ortega2Rodolfo Pazos-Rangel3José María Rodríguez-Lelís4Faculty of Accounting, Administration and Informatics, Universidad Autónoma del Estado de Morelos, Cuernavaca 62209, MexicoTecnológico Nacional de México/CENIDET, Cuernavaca 62490, MexicoTecnológico Nacional de México/IT de Tlalnepantla, Tlalnepantla de Baz 54070, MexicoTecnológico Nacional de México/IT de Cd. Madero, Ciudad Madero 89440, MexicoTecnológico Nacional de México/CENIDET, Cuernavaca 62490, MexicoPredicting the values of a financial time series is mainly a function of its price history, which depends on several factors, internal and external. With this history, it is possible to build an ∊-machine for predicting the financial time series. This work proposes considering the influence of a financial series through the transfer of entropy when the values of the other financial series are known. A method is proposed that considers the transfer of entropy for breaking the ties that occur when calculating the prediction with the ∊-machine. This analysis is carried out using data from six financial series: two American, the S&P 500 and the Nasdaq; two Asian, the Hang Seng and the Nikkei 225; and two European, the CAC 40 and the DAX. This work shows that it is possible to influence the prediction of the closing value of a series if the value of the influencing series is known. This work showed that the series that transfer the most information through entropy transfer are the American S&P 500 and Nasdaq, followed by the European DAX and CAC 40, and finally the Asian Nikkei 225 and Hang Seng.https://www.mdpi.com/1099-4300/24/8/1049financial seriesShannon entropytransfer entropy |
| spellingShingle | José Crispín Zavala-Díaz Joaquín Pérez-Ortega Nelva Nely Almanza-Ortega Rodolfo Pazos-Rangel José María Rodríguez-Lelís Influence of Transfer Entropy in the Short-Term Prediction of Financial Time Series Using an ∊-Machine Entropy financial series Shannon entropy transfer entropy |
| title | Influence of Transfer Entropy in the Short-Term Prediction of Financial Time Series Using an ∊-Machine |
| title_full | Influence of Transfer Entropy in the Short-Term Prediction of Financial Time Series Using an ∊-Machine |
| title_fullStr | Influence of Transfer Entropy in the Short-Term Prediction of Financial Time Series Using an ∊-Machine |
| title_full_unstemmed | Influence of Transfer Entropy in the Short-Term Prediction of Financial Time Series Using an ∊-Machine |
| title_short | Influence of Transfer Entropy in the Short-Term Prediction of Financial Time Series Using an ∊-Machine |
| title_sort | influence of transfer entropy in the short term prediction of financial time series using an ∊ machine |
| topic | financial series Shannon entropy transfer entropy |
| url | https://www.mdpi.com/1099-4300/24/8/1049 |
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