Applying Wavelets to Cyclic Processes. Change in Coherence of Stock Market and Sunspots

In the present Master Thesis we attempt to confirm the hypothesis about the correlation between the Economy and Sunspots by constructing a cross-wavelet spectrum on the daily data. In this paper, we use the software Matlab 2011, MS Excel 2010, Eviews 7. In particular, we examine the relationship between frequencies of two time series. With regard to economy, fluctuations are measured by stock index Dow-Jones Industrial Average, S&P500, RTS and the oil prices. The number of sunspots describes the solar activity. It was found that a significant period for the S&P500 and Sunspots is 4,000 days, or 11 years. The connection in the short term between the stock market and solar activity could not be established, significant general periods were not found. As a further research in this area of studies we want to set direction to increasing the number of macroeconomic variables, to compare them with the Wolf numbers, ignoring the daily dynamics and using monthly averages.