Pera J. Linear and Non-linear Relationships Between Shares of the Agri-food Industries of the Warsaw Stock Exchange. Risk Aspect
Autor | Jacek Pera |
Tytuł | Linear and Non-linear Relationships Between Shares of the Agri-food Industries of the Warsaw Stock Exchange. Risk Aspect |
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Słowa kluczowe | shares, risk, causal linear relationship, non- causal linear relationship, agri-food industry |
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Abstrakt | Despite a wide range of research on the agricultural market conducted so far, relatively little attention has been devoted to a comprehensive analysis of linear and non-linear causality in relation to the entire agri-food sector in Poland, in the context of risk. The objective of this study is therefore to analyze the linear and non-linear relationships between shares of WSE's agri-food industry sectors in terms of risk. The study covered three sectors of agri-food sector currently existing on the WSE (29 listed companies): Foods (21 listed companies), Agricultural Production and Fisheries (5 listed companies) and Food and Foodstuffs and fast-trafficking foodstuffs (3 listed companies). The existence of linear relationships was verified using the test procedure proposed by Hong, Liu, Wang and Łęt, while non-linear relationships were verified using the Diks-Panchenko, Orzeszko and Osińska tests’s. The study was carried out on the basis of data from companies of the agri-food industry listed on the Warsaw Stock Exchange in the period from 1 May 2010 to 1 May 2017. The chosen research methodology was dictated by the correlation with investment risk on the WSE. The strongest and most enduring dependencies have been found in the agricultural and fisheries sectors. In the foodstuff sector and the fast-marketable sector, the risk of investment in the listed companies was temporary. |
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Cytowanie | Pera J. (2017) Linear and Non-linear Relationships Between Shares of the Agri-food Industries of the Warsaw Stock Exchange. Risk Aspect.Zeszyty Naukowe SGGW w Warszawie - Problemy Rolnictwa Światowego, t. 17(32), z. 4: 249-262 |
HTML | wersja html |
Pełny tekst | PRS_2017_T17(32)_n4_s249.pdf |
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