Long-Range Correlations and Characterization of Financial and Volcanic Time Series
In this study, we use the Diffusion Entropy Analysis (DEA) to analyze and detect the scaling properties of time series from both emerging and well established markets as well as volcanic eruptions recorded by a seismic station, both financial and volcanic time series data have high frequencies. The...
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| Format: | Article |
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MDPI AG
2020-03-01
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| Series: | Mathematics |
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| Online Access: | https://www.mdpi.com/2227-7390/8/3/441 |
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| author | Maria C. Mariani Peter K. Asante Md Al Masum Bhuiyan Maria P. Beccar-Varela Sebastian Jaroszewicz Osei K. Tweneboah |
| author_facet | Maria C. Mariani Peter K. Asante Md Al Masum Bhuiyan Maria P. Beccar-Varela Sebastian Jaroszewicz Osei K. Tweneboah |
| author_sort | Maria C. Mariani |
| collection | DOAJ |
| description | In this study, we use the Diffusion Entropy Analysis (DEA) to analyze and detect the scaling properties of time series from both emerging and well established markets as well as volcanic eruptions recorded by a seismic station, both financial and volcanic time series data have high frequencies. The objective is to determine whether they follow a Gaussian or Lévy distribution, as well as establish the existence of long-range correlations in these time series. The results obtained from the DEA technique are compared with the Hurst R/S analysis and Detrended Fluctuation Analysis (DFA) methodologies. We conclude that these methodologies are effective in classifying the high frequency financial indices and volcanic eruption data—the financial time series can be characterized by a Lévy walk while the volcanic time series is characterized by a Lévy flight. |
| first_indexed | 2024-12-11T23:26:38Z |
| format | Article |
| id | doaj.art-29dc690a9a184359809cf00b180e837f |
| institution | Directory Open Access Journal |
| issn | 2227-7390 |
| language | English |
| last_indexed | 2024-12-11T23:26:38Z |
| publishDate | 2020-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Mathematics |
| spelling | doaj.art-29dc690a9a184359809cf00b180e837f2022-12-22T00:46:09ZengMDPI AGMathematics2227-73902020-03-018344110.3390/math8030441math8030441Long-Range Correlations and Characterization of Financial and Volcanic Time SeriesMaria C. Mariani0Peter K. Asante1Md Al Masum Bhuiyan2Maria P. Beccar-Varela3Sebastian Jaroszewicz4Osei K. Tweneboah5Department of Mathematical Sciences and Computational Science Program, University of Texas at El Paso, El Paso, TX 79968-0514, USAComputational Science Program, University of Texas at El Paso, El Paso, TX 79968-0514, USAComputational Science Program, University of Texas at El Paso, El Paso, TX 79968-0514, USADepartment of Mathematical Sciences, University of Texas at El Paso, El Paso, TX 79968-0514, USAComisión Nacional de Energía Atómica, Buenos Aires, ArgentinaComputational Science Program, University of Texas at El Paso, El Paso, TX 79968-0514, USAIn this study, we use the Diffusion Entropy Analysis (DEA) to analyze and detect the scaling properties of time series from both emerging and well established markets as well as volcanic eruptions recorded by a seismic station, both financial and volcanic time series data have high frequencies. The objective is to determine whether they follow a Gaussian or Lévy distribution, as well as establish the existence of long-range correlations in these time series. The results obtained from the DEA technique are compared with the Hurst R/S analysis and Detrended Fluctuation Analysis (DFA) methodologies. We conclude that these methodologies are effective in classifying the high frequency financial indices and volcanic eruption data—the financial time series can be characterized by a Lévy walk while the volcanic time series is characterized by a Lévy flight.https://www.mdpi.com/2227-7390/8/3/441diffusion entropy analysishurst r/s analysisdetrended fluctuation analysisfractional brownian motionlong-range correlations |
| spellingShingle | Maria C. Mariani Peter K. Asante Md Al Masum Bhuiyan Maria P. Beccar-Varela Sebastian Jaroszewicz Osei K. Tweneboah Long-Range Correlations and Characterization of Financial and Volcanic Time Series Mathematics diffusion entropy analysis hurst r/s analysis detrended fluctuation analysis fractional brownian motion long-range correlations |
| title | Long-Range Correlations and Characterization of Financial and Volcanic Time Series |
| title_full | Long-Range Correlations and Characterization of Financial and Volcanic Time Series |
| title_fullStr | Long-Range Correlations and Characterization of Financial and Volcanic Time Series |
| title_full_unstemmed | Long-Range Correlations and Characterization of Financial and Volcanic Time Series |
| title_short | Long-Range Correlations and Characterization of Financial and Volcanic Time Series |
| title_sort | long range correlations and characterization of financial and volcanic time series |
| topic | diffusion entropy analysis hurst r/s analysis detrended fluctuation analysis fractional brownian motion long-range correlations |
| url | https://www.mdpi.com/2227-7390/8/3/441 |
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