Various Seasonality

Seasonality of Price Changes for the US Agricultural Commodities

Elena Berseneva 24 january 2022 199 4

The USA is the country with a well-developed and effective agricultural sector. Many agricultural commodities, produced in the territory of the country, were exported (in particular, to China). Wheat, corn, soybeans represent the most widespread cereal and pulse in the US agricultural sector. Due to the development of the market infrastructure, futures for the crops mentioned above are related to the traditional, available and highly-liquidity exchange-traded instruments. In this research we try to identify seasonal trends in the price changes for wheat, corn and soybeans.

Hypothesis
To conclusion

The price changes for US agricultural commodities have well-pronounced seasonal manifestations.

To conclusion


We suggest using the following criteria to assess the seasonality:


  1. The share of cases of unidirectional increments of daily deltas within one month for the period of at least 10 years must be more than 53%.
  2. The ratio of the average value of positive daily increments to the average value of negative daily increments must comply with the direction of monthly price increments. So, this condition is fulfilled if this value is more than 1 with the share of positive daily increments more than 50%.
  3. The linear trend of distribution of monthly delta values must have a direction towards increase of unidirectional increments.


If all the three conditions mentioned above are met, we can prove seasonality in price changes of the financial instrument.

Data used
  • The historical data of quotes’ futures for wheat since January 1990 until April 2019. The sample is 7428 values.
  • The historical data of quotes’ futures for corn since December 1979 until April 2019. The sample is 10109 values.
  • The historical data of quotes’ futures for soybeans since January 1990 until April 2019. The sample is 7569 values.



The seasonal price changes for the US wheat

(the price increments for the month are shown in %)

Description of the bottom lines:


  • for the first bottom line the share of cases of unidirectional increments was calculated based on the analysis of daily price changes. With the example of January, it is done the following way: we take all days of this month for all 29 years and get 590 days. The growth of prices was estimated from these 590 days based on 291 days. So, the share of growth is 49%.


  • for the second bottom line we compare the average value of all positive daily increments of every month and the average value of negative increments.
  1. If the obtained value is >1, it means that on days of growth the price goes through a greater number of points than on days of falls.
  2. If the obtained value is <1, it means that on days of falls the price goes through a greater number of points that on days of growth.


The assessment of seasonality on the basis of daily increments is a more sensitive method that can filtrate extremely high values of growth and falls of quotes on some days.


The ontained results show the lack of seasonality in change of the price.




The seasonal price changes for the US corn

(the price increments for the month are demonstrated in %)

Having analyzed data on the price of corn, the “bullish” seasonality in March and December has been identified according to two first criteria. Now we will test them according to the third criterion.

In March on the chart with the period of 10 years there is the “bullish” increment that completely meets the last criteria of seasonality.


The linear downward trend of December increments allows us to think with some certainty of the lack of the well-pronounced seasonality of prices for these commodities.




Now turn to the assessment of seasonality for the price of the US soya.


The seasonal price changes for the US soya

(the price increments for the month are demonstrated in %)



In the charts of the linear trend of February, March, April and May we can notice that these months are characterized by attenuation of the bullish increments. And this does not fit the third criterion.


In November, we find proof for the trends of price increase, which satisfies the last criterion of seasonality.

Conclusion

We have identified that the prices for the US agricultural commodities have the following manifestations of seasonality:


  • The seasonal regularities in changes of the cost of wheat are missing.
  • The data on changes of the corn’s cost indicate the seasonal trend of quotes’ growing in March.
  • The soya’s cost notes the seasonal trend of the growth in November.


The influence of seasonality on the direction of futures contract rates for the US agricultural commodities has been identified.

XLSX (0.10 MB)Wheat.xlsxXLSX (0.31 MB)Corn.xlsxXLSX (0.43 MB)Soybean.xlsx

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