Journal Article

No. 2016-9 | March 24, 2016
A Historical Analysis of the US Stock Price Index Using Empirical Mode Decomposition over 1791–2015 PDF Icon

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 long-term returns on investment.

Data Set

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The data set for this article can be found at: http://dx.doi.org/10.7910/DVN/FZUQDM

JEL Classification

C22 G10

Citation

Aviral K. Tiwari, Arif B. Dar, Niyati Bhanja, and Rangan Gupta (2016). A Historical Analysis of the US Stock Price Index Using Empirical Mode Decomposition over 1791–2015. Economics: The Open-Access, Open-Assessment E-Journal, 10 (2016-9): 1—15. http://dx.doi.org/10.5018/economics-ejournal.ja.2016-9

Assessment

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