Permutation Entropy and Information Recovery in Nonlinear Dynamic Economic Time Series
The focus of this paper is an information theoretic-symbolic logic approach to extract information from complex economic systems and unlock its dynamic content. Permutation Entropy (PE) is used to capture the permutation patterns-ordinal relations among the individual values of a given time series;...
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| Format: | Article |
| Language: | English |
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MDPI AG
2019-03-01
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| Series: | Econometrics |
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| Online Access: | http://www.mdpi.com/2225-1146/7/1/10 |
| _version_ | 1828150150274482176 |
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| author | Miguel Henry George Judge |
| author_facet | Miguel Henry George Judge |
| author_sort | Miguel Henry |
| collection | DOAJ |
| description | The focus of this paper is an information theoretic-symbolic logic approach to extract information from complex economic systems and unlock its dynamic content. Permutation Entropy (PE) is used to capture the permutation patterns-ordinal relations among the individual values of a given time series; to obtain a probability distribution of the accessible patterns; and to quantify the degree of complexity of an economic behavior system. Ordinal patterns are used to describe the intrinsic patterns, which are hidden in the dynamics of the economic system. Empirical applications involving the Dow Jones Industrial Average are presented to indicate the information recovery value and the applicability of the PE method. The results demonstrate the ability of the PE method to detect the extent of complexity (irregularity) and to discriminate and classify admissible and forbidden states. |
| first_indexed | 2024-04-11T21:40:15Z |
| format | Article |
| id | doaj.art-6100b1a7c6fc421da3a36c7641ff6680 |
| institution | Directory Open Access Journal |
| issn | 2225-1146 |
| language | English |
| last_indexed | 2024-04-11T21:40:15Z |
| publishDate | 2019-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Econometrics |
| spelling | doaj.art-6100b1a7c6fc421da3a36c7641ff66802022-12-22T04:01:37ZengMDPI AGEconometrics2225-11462019-03-01711010.3390/econometrics7010010econometrics7010010Permutation Entropy and Information Recovery in Nonlinear Dynamic Economic Time SeriesMiguel Henry0George Judge1Economist at Greylock McKinnon Associates, 75 Park Plaza, 4th Floor, Boston, MA 02116, USAGraduate School and Giannini Foundation, 207 Giannini Hall, University of California Berkeley, Berkeley, CA 94720, USAThe focus of this paper is an information theoretic-symbolic logic approach to extract information from complex economic systems and unlock its dynamic content. Permutation Entropy (PE) is used to capture the permutation patterns-ordinal relations among the individual values of a given time series; to obtain a probability distribution of the accessible patterns; and to quantify the degree of complexity of an economic behavior system. Ordinal patterns are used to describe the intrinsic patterns, which are hidden in the dynamics of the economic system. Empirical applications involving the Dow Jones Industrial Average are presented to indicate the information recovery value and the applicability of the PE method. The results demonstrate the ability of the PE method to detect the extent of complexity (irregularity) and to discriminate and classify admissible and forbidden states.http://www.mdpi.com/2225-1146/7/1/10Cressie-Read divergenceinformation theoretic methodscomplexitynonparametric econometricspermutation entropynonlinear time seriessymbolic logic |
| spellingShingle | Miguel Henry George Judge Permutation Entropy and Information Recovery in Nonlinear Dynamic Economic Time Series Econometrics Cressie-Read divergence information theoretic methods complexity nonparametric econometrics permutation entropy nonlinear time series symbolic logic |
| title | Permutation Entropy and Information Recovery in Nonlinear Dynamic Economic Time Series |
| title_full | Permutation Entropy and Information Recovery in Nonlinear Dynamic Economic Time Series |
| title_fullStr | Permutation Entropy and Information Recovery in Nonlinear Dynamic Economic Time Series |
| title_full_unstemmed | Permutation Entropy and Information Recovery in Nonlinear Dynamic Economic Time Series |
| title_short | Permutation Entropy and Information Recovery in Nonlinear Dynamic Economic Time Series |
| title_sort | permutation entropy and information recovery in nonlinear dynamic economic time series |
| topic | Cressie-Read divergence information theoretic methods complexity nonparametric econometrics permutation entropy nonlinear time series symbolic logic |
| url | http://www.mdpi.com/2225-1146/7/1/10 |
| work_keys_str_mv | AT miguelhenry permutationentropyandinformationrecoveryinnonlineardynamiceconomictimeseries AT georgejudge permutationentropyandinformationrecoveryinnonlineardynamiceconomictimeseries |