Does the Sunspot Cycle Predict Energy and Grain Prices?
Posted in Calendar Effects, Commodity Futures
October 24, 2011
As a follow-up to “Sunspot Cycle and Stock Returns” reader asked: “Sunspot activity does have a direct relationship to weather. Could one speculate on the natural gas market or the agriculture market using the sunspot cycles?” Using monthly averages of daily sunspot counts from the Solar Influences Data Analysis Center and monthly U.S. wheat prices for September 1928 through August 2011 (996 months) and monthly U.S. wellhead natural gas prices for January 1976 through July 2011 (427 months), we find that:
The National Weather Service notes:
“…[T] the jury is still out on how much sunspots can (or do) affect the Earth’s climate. Times of maximum sunspot activity are associated with a very slight increase in the energy output from the sun. Ultraviolet radiation increases dramatically during high sunspot activity, which can have a large effect on the Earth’s atmosphere. From the mid 1600s to early 1700s, a period of very low sunspot activity (known as the Maunder Minimum) coincided with a number of long winters and severe cold temperatures in Western Europe, called the Little Ice Age. It is not known whether the two phenomena are linked or if it was just coincidence. The reason it is hard to relate maximum and minimum solar activity (sunspots) to the Earth’s climate, is due to the complexity of the Earth’s climate itself.”
If there were a sunspot-weather relationship, we might hypothesize that a high sunspot count (warm weather) would depress natural gas price (lower heating demand) and depress wheat price (support good crops).
The following chart compares the monthly average of daily sunspot counts to the contemporaneous monthly U.S. wellhead natural gas price (log scale) during January 1976 through July 2011. Visual inspection reveals no consistent relationship between the two series. It does not appear that natural gas price has valleys (peaks) at sunspot peaks (valleys).
For a more precise measurement, we investigate whether changes in sunspot activity relate to changes in the price of natural gas.
The following scatter plot relates the change in U.S. wellhead natural gas price over three-month intervals to change in monthly average sunspot count over the same intervals. We have winnowed the sample such that the three-month periods do not overlap (142 surviving observations). The Pearson correlation is 0.01 and the R-squared statistic is 0.000, indicating no relationship.
When we offset such that changes in sunspot activity lead changes in natural gas price by three months, the Pearson correlation is -0.02 and the R-squared statistic 0.000. There is no significant leading relationship.
What about a longer-term relationship?
The next scatter plot relates the change in U.S. wellhead natural gas price over 12-month intervals to change in monthly average sunspot count over the same intervals. We have further winnowed the sample such that the 12-month periods do not overlap (only 35 surviving observations). The Pearson correlation is -0.08 (negative, as hypothesized) and the R-squared statistic is 0.01, indicating that change in sunspot activity explains about 1% (hardly any) of the variation in spot natural gas price over a year. Sample size is small, so this conclusion is not reliable.
When we offset such that changes in sunspot activity lead changes in natural gas price by 12 months, the Pearson correlation is 0.22 and the R-squared statistic 0.05, indicating that change in sunspot activity this year explains about 5% of the variation in spot natural gas price next year. However, the correlation is positive (opposite the hypothesis). Again, sample size is small, so this conclusion is not reliable.
How about sunspots and wheat?
The next chart compares the monthly average of daily sunspot counts to the contemporaneous monthly U.S. wheat price (log scale) during September 1928 through August 2011. Visual inspection reveals no consistent relationship between the two series. There are some cases in which wheat prices are high (low) when sunspot activity is low (high), but there are also contradictory data.
For a more precise measurement, we investigate whether changes in sunspot activity relate to changes in the price of wheat.
The following scatter plot relates the change in U.S. wheat price over three-month intervals to change in sunspot count over the intervals. We have winnowed the sample such that the three-month periods do not overlap (331 surviving observations). The Pearson correlation is 0.02 and the R-squared statistic is 0.001, indicating no relationship.
When we offset such that changes in sunspot activity lead changes in wheat price by three months, the Pearson correlation is 0.09 and the R-squared statistic 0.01, indicating that change in sunspot activity this quarter explains about 1% (hardly any) of the variation in wheat price next quarter.
What about a longer-term relationship?
The final scatter plot relates the change in U.S. wheat price over 12-month intervals to change in sunspot count over the same intervals. We have further winnowed the sample such that the 12-month periods do not overlap (82 surviving observations). The Pearson correlation is 0.14 and the R-squared statistic is 0.02, indicating that change in sunspot activity explains 2% of the variation in wheat price during a year. Given sample size and variability, this indication is not meaningful.
When we offset such that changes in sunspot activity lead changes in wheat price by 12 months, the Pearson correlation is 0.02 and the R-squared statistic 0.001, indicating that change in sunspot activity this year explains practically none of the variation in wheat price next year.
In summary, evidence from simple tests does not support using sunspot activity to speculate on natural gas and wheat prices over periods of a quarter or a year.
Other aggregations of data may produce different results.
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