The Correlation between Agricultural Commodities and Weather Patterns

Agricultural commodities revolve around seasonal growing and harvesting periods where optimal production occurs under certain weather conditions. The long-term demand for agricultural commodities are increasing as the short-term spikes in the stocks are caused by weather problems, crop deterioration, coffee rust, natural disasters, fungus and other growing issues resulting in price volatility. When there is a strain on production it can cause prices to soar as the supply is short of t­he demand. This review focuses on the correlation between weather patterns and the performance of SOYB, CORN, SBUX, HSY, WEAT, CANE and JVA.

The closing prices can be correlated to the production rate for that season. Sugarcane is the most volatile since it grows in locations that are susceptible to hurricanes, monsoons and other weather events. In the fall of 2012, the price fell to 22 cents a pound as it was a good production year. The next sugar boom will be when the production of sugar is scarce causing prices to skyrocket. El Nino and La Nina patterns indirectly alter the performance of agricultural commodities. These patterns occur between latitudes 5 degrees North and 5 degrees South and the coffee belt is located between 25 degrees North and 30 degrees South. The SST product values administrated by NOAA is one set of data that I am utilizing to predict the performance of the market. Consequently, global warming is decreasing the quality and quantity of the agricultural commodities. As the global temperatures increase, coffee bean farms are having to be relocated to higher altitudes in order to sustain production. The demand for commodities is increasing as the global development rate is on an uphill climb.