Abstract:
In this paper, the dynamics of Standard and Poor's 500 (S&P 500) stock price index is analysed
within a time-frequency framework over a monthly period 1791:08–2015:05. Using the Empirical
Mode Decomposition technique, the S&P 500 stock price index is divided into different frequencies
known as intrinsic mode functions (IMFs) and one residual. The IMFs and the residual are then
reconstructed into high frequency, low frequency and trend components using the hierarchical
clustering method. Using different measures, it is shown that the low frequency and trend
components of stock prices are relatively important drivers of the S&P 500 index. These results
are also robust across various subsamples identified based on structural break tests. Therefore, US
stock prices have been driven mostly by fundamental laws rooted in economic growth and longterm
returns on investment.
