Investigating System Dynamics of Vegetable Prices Using Complex Network Analysis and Temporal Variation Methods
In the present study, we analyze the price time series behavior of selected vegetable products, using complex network analysis in two approaches: (a) correlation complex networks and (b) visibility complex networks based on transformed time series. Additionally, we apply time variability methods, in...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2024-10-01
|
| Series: | AppliedMath |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2673-9909/4/4/71 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1846106128250830848 |
|---|---|
| author | Sofia Karakasidou Avraam Charakopoulos Loukas Zachilas |
| author_facet | Sofia Karakasidou Avraam Charakopoulos Loukas Zachilas |
| author_sort | Sofia Karakasidou |
| collection | DOAJ |
| description | In the present study, we analyze the price time series behavior of selected vegetable products, using complex network analysis in two approaches: (a) correlation complex networks and (b) visibility complex networks based on transformed time series. Additionally, we apply time variability methods, including Hurst exponent and Hjorth parameter analysis. We have chosen products available throughout the year from the Central Market of Thessaloniki (Greece) as a case study. To the best of our knowledge, this kind of study is applied for the first time, both as a type of analysis and on the given dataset. Our aim was to investigate alternative ways of classifying products into groups that could be useful for management and policy issues. The results show that the formed groups present similarities related to their use as plates as well as price variation mode and variability depending on the type of analysis performed. The results could be of interest to government policies in various directions, such as products to develop greater stability, identify fluctuating prices, etc. This work could be extended in the future by including data from other central markets as well as with data with missing data, as is the case for products not available throughout the year. |
| format | Article |
| id | doaj-art-4e013a8b2b1a4c3ca3d773fe16c40d94 |
| institution | Kabale University |
| issn | 2673-9909 |
| language | English |
| publishDate | 2024-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | AppliedMath |
| spelling | doaj-art-4e013a8b2b1a4c3ca3d773fe16c40d942024-12-27T14:07:08ZengMDPI AGAppliedMath2673-99092024-10-01441328135710.3390/appliedmath4040071Investigating System Dynamics of Vegetable Prices Using Complex Network Analysis and Temporal Variation MethodsSofia Karakasidou0Avraam Charakopoulos1Loukas Zachilas2Department of Economics, University of Thessaly, 38334 Volos, GreeceDepartment of Physics, University of Thessaly, 35100 Lamia, GreeceDepartment of Economics, University of Thessaly, 38334 Volos, GreeceIn the present study, we analyze the price time series behavior of selected vegetable products, using complex network analysis in two approaches: (a) correlation complex networks and (b) visibility complex networks based on transformed time series. Additionally, we apply time variability methods, including Hurst exponent and Hjorth parameter analysis. We have chosen products available throughout the year from the Central Market of Thessaloniki (Greece) as a case study. To the best of our knowledge, this kind of study is applied for the first time, both as a type of analysis and on the given dataset. Our aim was to investigate alternative ways of classifying products into groups that could be useful for management and policy issues. The results show that the formed groups present similarities related to their use as plates as well as price variation mode and variability depending on the type of analysis performed. The results could be of interest to government policies in various directions, such as products to develop greater stability, identify fluctuating prices, etc. This work could be extended in the future by including data from other central markets as well as with data with missing data, as is the case for products not available throughout the year.https://www.mdpi.com/2673-9909/4/4/71vegetable pricestemporal variation methodscorrelation complex networkvisibility graphs |
| spellingShingle | Sofia Karakasidou Avraam Charakopoulos Loukas Zachilas Investigating System Dynamics of Vegetable Prices Using Complex Network Analysis and Temporal Variation Methods AppliedMath vegetable prices temporal variation methods correlation complex network visibility graphs |
| title | Investigating System Dynamics of Vegetable Prices Using Complex Network Analysis and Temporal Variation Methods |
| title_full | Investigating System Dynamics of Vegetable Prices Using Complex Network Analysis and Temporal Variation Methods |
| title_fullStr | Investigating System Dynamics of Vegetable Prices Using Complex Network Analysis and Temporal Variation Methods |
| title_full_unstemmed | Investigating System Dynamics of Vegetable Prices Using Complex Network Analysis and Temporal Variation Methods |
| title_short | Investigating System Dynamics of Vegetable Prices Using Complex Network Analysis and Temporal Variation Methods |
| title_sort | investigating system dynamics of vegetable prices using complex network analysis and temporal variation methods |
| topic | vegetable prices temporal variation methods correlation complex network visibility graphs |
| url | https://www.mdpi.com/2673-9909/4/4/71 |
| work_keys_str_mv | AT sofiakarakasidou investigatingsystemdynamicsofvegetablepricesusingcomplexnetworkanalysisandtemporalvariationmethods AT avraamcharakopoulos investigatingsystemdynamicsofvegetablepricesusingcomplexnetworkanalysisandtemporalvariationmethods AT loukaszachilas investigatingsystemdynamicsofvegetablepricesusingcomplexnetworkanalysisandtemporalvariationmethods |