Global Journal of Research in Management

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Predicting Shrimp Prices in India:A Forecast using Random Walk Model


Affiliations
1 Veer Narmad South Gujarat University, Surat, India
2 Department of Business and Industrial Management, VNSGU, Surat, India
     

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Shrimp continues to be one of the most traded food commodities in the world. Due to its taste and nutritional benefits, there has been a major growth in the demand of shrimps from the developed nations in the world. Changing demographic pattern of the world population has caused shrimps to be a preferred species in the developing country to fulfill their food requirement. With the marine resources continuously depleting, aquaculture emerges as an industry, capable to fulfill the rising demand of shrimps in the world. The aim of this paper is to study the pattern of the shrimp prices in India. Further an attempt has been made to predict the future movement of the shrimp prices in India using the random walk model.

Keywords

Shrimp, Forecast, Time Series, Trend Analysis, Random Walk.
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  • Predicting Shrimp Prices in India:A Forecast using Random Walk Model

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Authors

Vatsal B. Patel
Veer Narmad South Gujarat University, Surat, India
Vinod B. Patel
Department of Business and Industrial Management, VNSGU, Surat, India

Abstract


Shrimp continues to be one of the most traded food commodities in the world. Due to its taste and nutritional benefits, there has been a major growth in the demand of shrimps from the developed nations in the world. Changing demographic pattern of the world population has caused shrimps to be a preferred species in the developing country to fulfill their food requirement. With the marine resources continuously depleting, aquaculture emerges as an industry, capable to fulfill the rising demand of shrimps in the world. The aim of this paper is to study the pattern of the shrimp prices in India. Further an attempt has been made to predict the future movement of the shrimp prices in India using the random walk model.

Keywords


Shrimp, Forecast, Time Series, Trend Analysis, Random Walk.

References