Sunspots and Market Prediction

NASA image of a sunspot up close.

The appearance of dark spots on the Sun occurs on average once per decade. There is evidence dating back thousands of years that suggest the appearance of sunspots coincide with observable changes in human behavior. Recent research asks the question: Can sunspot activity also predict the markets?

Sunspots are caused by intense magnetic activity in and around the Sun. This phenomenon reduces the surface temperature temporarily and creates a series of dark spots. These spots quickly rise and more slowly fall on an irregular cycle of about 11 years.

The first written record of sunspots was made by Chinese astronomer Gan De in 364 B.C.  In the centuries that followed, the Chinese linked sunspot activity to human activity and started incorporating this information into the timing of important decisions, such as when to have children and when to go to war.

Today, a group of investors believe the Chinese were on to something. They linked sunspot activity to economic activity and, in some degree, to stock market prices. Theorist Michael Wells Mandeville considered sunspot activity in 2003 when he wrote The Coming Economic Collapse of 2006. His timing wasn’t far off.  In 2007, Charles Nenner cited sunspot activity as a specific key indicator for bearish market calls during an interview on Bloomberg television.

Is there any reliable relationship between sunspot activity and stock market returns? Research firm CXO Advisory Group decided to look into this matter.

Using monthly averages of daily sunspot counts from the Solar Influences Data Analysis Center and monthly closing levels of the Dow Jones Industrial Average (DJIA) for September 1928 through September 2011 (997 months) and the S&P 500 Index for January 1950 through September 2011 (741 months), CXO compared the returns of the sunspot activity to changes in market return.

Figure 1, courtesy of CXO, compares the monthly average of daily sunspot counts to contemporaneous monthly DJIA closing levels (log scale) over the entire sample period. This comprises roughly 7.5 sunspot cycles. A visual inspection reveals no consistent relationship between the two series.

Figure 1: Historic sunspot activity and the price level of the DJIA

Historic sunspot activity and the price level of the DJIA

The next question asked by CXO was if the monthly change in sunspot count explained future stock market return. Figure 2 relates DJIA monthly return to the average daily sunspot count during that month over the entire sample period.

Figure 2: Changes in sunspot count to the DJIA price change

The near zero correlation in Figure 2 indicated that variation in monthly average sunspot counts explains practically none of contemporaneous variation in monthly DJIA returns. CXO found that the results for the S&P 500 Index since 1950 were similar.

The CXO research continues with an analysis of sunspots versus index returns using various lead and lag periods. They found no meaningful correlation in the data.

In summary, the results from an array of simple tests do not support a meaningful relationship between sunspot activity and stock market returns.