The fluctuations of agricultural commodity prices can significantly affect the global economies and living standards in many countries. Under COVID-19 crisis pressure, an accurate AI/ML forecast solution has never been more important for business leaders and agricultural authorities to make better decisions. This blog will review the agricultural commodity market and its relationship to the global economy and explain how managers can leverage data to improve forecasting methods using Forecasty.AI solutions.
Agricultural commodities include any crops or animals grown or raised on farmland, either in their original form or have undergone primary processing. They can be divided into six categories: cereal grains (e.g. corn, wheat), dairy (e.g. cheese, milk), oilseeds (e.g. palm oil, soybeans), meat (e.g. live cattle, pork bellies), other soft commodities (e.g. coffee, sugar), and miscellaneous agricultural commodities (e.g. wool, rubber). Not only be an important source of food for human and animals, agricultural commodities also serve as a fundamental ingredient for industrial sections (e.g. chamomile in skincare products, wool in textile industry).
There is no doubt that agricultural commodity prices have a wide range of influences in all parts of the world. High food prices can boost the production from farmers and investment from private sectors that may have financial repercussions in the long term. In contrast, high market prices prevent low-income households, especially in urban areas, to meet their food needs and access to nutritious diets. In some developing countries, the rising of food price can cause riots and political uncertainty. Furthermore, a low movement of the commodity prices is harmful for most of the poor people whose income solely depends on agriculture. Consequently, developing a better understanding of the volatility of agricultural commodity price is essential for both stakeholders and policymakers.
Of all the several factors that drive the price volatility in agricultural commodity market, demand and supply play a prominent role. Over the long term, other key factors vary from income, global intense production competition, new technologies, government policies and economic growths. In the short term, agricultural commodity prices are influenced by weather events, interest rates, biofuel mandates or speculation.
According to FAO (2020), since 1995, international trade in food and agriculture has leapt to more than 50%. However, the growth rate has slipped back since the 2008 financial crisis. Agricultural and food markets change rapidly in emerging economies and developing countries. The World Bank’s Agricultural Price Index increased by 6% in 2020 Q3 and the price rose by 6% compared to the previous year. With the shortfall in oils and meals, together with the increasing demand for raw materials and US dollar depreciation, most agricultural commodity prices have started to pick up. Nevertheless, the severe impact of the COVID-19 pandemic, supply chain disruption and travel restrictions continue to ravage the global economy. This leads to significant price declines for crops and animal proteins.
Agricultural commodity price forecasting refers to the process of making predictions of the future price of an agricultural commodity based on past and present data or trends analysis. The forecasts will take into account risk and uncertainty elements.
As agricultural commodity price has become more volatile in recent years, it is crucial to effectively predict the futures price trend to optimize investment strategies and avoid risks. This is where advanced AI/ML solutions with self-learning capability shine as a powerful tool to handle complex price forecasting task.
Forecasty.AI helps global clients make smarter & more profitable business decisions through smart forecasting modelling, economics and analytics. We create highly accurate predictions by applying advanced AI/ML on established and new data sources via a simple drag and drop solution. Our solution automates forecasting tasks, ensures explainability and further allow scenario simulations to improve management decision making.
To help our customers plan their businesses and prepare future crisis management better, we provide scenario planning solutions specifically to tackle challenges from COVID-19.
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