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, 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.

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Publication Details

Journal
AppliedMath
Published
2024-10-16
DOI
https://doi.org/10.3390/appliedmath4040071
Primary Topic
Complex Systems and Time Series Analysis
Type
article
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article

Investigating System Dynamics of Vegetable Prices Using Complex Network Analysis and Temporal Variation Methods

Loukas Zachilas, Avraam Charakopoulos, Sofia Karakasidou
AppliedMath
Complex Systems and Time Series Analysis
article

Investigating System Dynamics of Vegetable Prices Using Complex Network Analysis and Temporal Variation Methods

Loukas Zachilas, Avraam Charakopoulos, Sofia Karakasidou
article en

Abstract

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.

AppliedMathVol. 4(4)
University of Thessaly (GR)
Openalex Percentile: Top 78%
Complex Systems and Time Series Analysis
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Investigating System Dynamics of Vegetable Prices Using Complex Network Analysis and Temporal Variation Methods — Loukas Zachilas, Avraam Charakopoulos, et al. · AppliedMath (2024) | TGRS Research Map | TGRS