Predicting the future price of a commodity using the OWMA operator: An approximation of the interest rate and inflation in the brown pastusa potato price

Abstract

This main aim of this paper is to propose a methodology for the prediction of the future price of the brown pastusa potato in Colombia, taking into consideration the variables of interest rate, as measured by fixed term deposits (FTDs), and inflation rate, as measured by the consumer price index (CPI). The methodology conducts linear regression analysis and assesses the results using the significance test, the Durbin-Watson statistic, analysis of the variance inflation factor (VIF) and the coefficient of determination. After that, the forecast of the independent variables has been conducted with the ordered weighted moving average (OWMA) operator and new proposed OWA operators using probabilities that are presented in the paper. Using these new methods and the proposed econometric model, it is possible to establish future prices. The results show a greater impact of the interest rate than inflation, as well as the need to include supply and demand variables that have not been included due to the absence of systematic information.

The Impact of Monetary Policy, Transport Costs and Substitute Prices on the Australian Wheat Futures Market Price

“…Fonseca-Cifuentes et al identified the large impact of interest rates on the future price of Colombian brown potatoes by using methods such as significance tests and OWMA. And both potatoes and wheat are bulk commodities with certain common characteristics [10]. Therefore, the model currently developed does not explain 100% of the behaviour of price changes in the wheat futures market.…”

Pythagorean Membership Grade Aggregation Operators: Application in Financial knowledge

“…For example, along the IOWA operator line, many proposals have taken a variety of approaches, which have used linguistic variables [18,19], fuzzy preference [20], intuitionistic fuzzy sets [21][22][23], distance measures [24,25], and heavy and prioritized operators [16,26,27], with others applying means such as Bonferroni means [28], VIKOR [29], Choquet [30], etc. For the OWMA operator, [31] generalized moving averages, distance measures and OWA; [16] proposed induced heavy moving averages, which can be applied in forecasting approaches [17,[32][33][34]. Finally, the Pythagorean membership grade operator has focused on Pythagorean fuzzy sets, which have been extensively studied.…”