From bilateral trade to centralized markets: A search model for commodity exchanges in Africa

The research goal presented in this paper was to determine the strength of the relationship between the price of coffee traded on ICE Futures US and Consumer Price Indices in the major urban agglomerations of the United States—New York, Chicago, and Los Angeles—and to predict the future development. The results obtained using the Pearson correlation coefficient confirmed a very close direct correlation (r = 0.61 for New York and Chicago; r = 0.57 for Los Angeles) between the price of coffee and inflation. The prediction made using the SARIMA model disrupted the mutual correlation. The price of coffee is likely to anchor at a new level where it will fluctuate; on the other hand, the CPIs showed strong unilateral pro-growth trends. The results could be beneficial for the analysis and creation of policies and further analyses of market structures at the technical level.

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Maki̇ne Öğrenmesi̇nde Regresyon Modelleri̇ni̇n Tahmi̇n Performanslarinin Karşilaştirilmasi: Türki̇ye Ürün İhti̇sas Borsasi Buğday Endeksi̇ Üzeri̇ne Bi̇r Uygulama

BURHAN

2023

Nişantaşı Üniversitesi Sosyal Bilimler Dergisi

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Agricultural commodity prices have significant impacts on economies by leading to changes and regulations in both fiscal and monetary policies. These also have effects on household economies and consumer purchasing power particularly in developing countries. Thereby, instability and variability in these prices constitute adverse effects on these economies. On the other hand, assets of the commodity markets become popular just as bonds and stocks. Because of this growing interest, needs for managing risks, stable prices and lowering transaction costs has led to establishment of the commodity exchanges. In this context, Turkey put the licensed warehousing system into operation by founding the Turkish Mercantile Exchange (TMEX) to operate trades of Electronic Warehouse Receipts (EWRs). In this study, a model including US Dollar-Turkish Lira exchange rate (USD/TRY), Brent crude-oil prices, overnight interest rate and a daily dataset for the 01/04/2021-20/02/2023 period were used to assess several machine learning regression methods in predicting the TMEX Wheat Index (TMXWHT). As verified by comparisons with actual values and considering performance evaluation criteria, all methods yielded successful outcomes, furthermore, tree-based methods revealed better overall performance.

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From bilateral trade to centralized markets: A search model for commodity exchanges in Africa

Cited by 3 publications

References 29 publications

Combating Trade-Based Money Laundering: Do the Financial Action Task Force Recommendations Bite?

Combating Trade-Based Money Laundering: Do the Financial Action Task Force Recommendations Bite?

Coffee as an Identifier of Inflation in Selected US Agglomerations

Maki̇ne Öğrenmesi̇nde Regresyon Modelleri̇ni̇n Tahmi̇n Performanslarinin Karşilaştirilmasi: Türki̇ye Ürün İhti̇sas Borsasi Buğday Endeksi̇ Üzeri̇ne Bi̇r Uygulama

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