Response of Ethiopian coffee price to the world coffee price: Evidence from dynamic ARDL simulations and nonlinear ARDL cointegration

Most market players have found great significance in price projections for basic agricultural commodities for a substantial duration. We look at the daily price of coffee that is released in this research in order to tackle the issue. The analytical sample runs from 2 January 2013 to 10 April 2024, a period of more than 12 years. A significant influence on the business sector comes from the price series under investigation. Specifically, in this particular situation, Gaussian process regression models are developed using Bayesian optimization techniques and cross-validation processes. Thus, this circumstance prompts the development of price forecasting methodologies. Using our empirical forecasting technique, we produce relatively accurate price projections for the out-of-sample assessment period, which runs from 3 January 2022 to 10 April 2024. It was found that price forecasts of coffee had a relative root mean square error of 2.0500%. With the availability of price forecasting models, investors and governments can make educated decisions about the coffee market given that they have access to the required data.

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Response of Ethiopian coffee price to the world coffee price: Evidence from dynamic ARDL simulations and nonlinear ARDL cointegration

Cited by 4 publications

References 62 publications

Exploring the consequence of ecological and agronomic determinants on wheat production instabilities in Khyber Pakhtunkhwa, Pakistan: Perspectives from dynamic autoregressive distributed lag analysis

Exploring the consequence of ecological and agronomic determinants on wheat production instabilities in Khyber Pakhtunkhwa, Pakistan: Perspectives from dynamic autoregressive distributed lag analysis

Organizational innovation in the relationship between total quality management and business financial performance: case of coffee processing firms in Guji zone, Ethiopia

Machine Learning Coffee Price Predictions

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