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A historical analysis of the US stock price index using empirical mode decomposition over 1791-2015


  • Tiwari, Aviral K.
  • Dar, Arif B.
  • Bhanja, Niyati
  • Gupta, Rangan


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.

Suggested Citation

  • Tiwari, Aviral K. & Dar, Arif B. & Bhanja, Niyati & Gupta, Rangan, 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, Kiel Institute for the World Economy (IfW), vol. 10, pages 1-15.
  • Handle: RePEc:zbw:ifweej:20169

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    References listed on IDEAS

    1. Tiwari, Aviral Kumar & Dar, Arif Billah & Bhanja, Niyati, 2013. "Oil price and exchange rates: A wavelet based analysis for India," Economic Modelling, Elsevier, vol. 31(C), pages 414-422.
    2. Cheng, Ching-Hsue & Wei, Liang-Ying, 2014. "A novel time-series model based on empirical mode decomposition for forecasting TAIEX," Economic Modelling, Elsevier, vol. 36(C), pages 136-141.
    3. Tsangyao Chang & Xiao-lin Li & Stephen M. Miller & Mehmet Balcilar & Rangan Gupta, 2013. "The Co-Movement and Causality between the U.S. Real Estate and Stock Markets in the Time and Frequency Domains," Working Papers 201365, University of Pretoria, Department of Economics.
    4. Zhang, Xun & Lai, K.K. & Wang, Shou-Yang, 2008. "A new approach for crude oil price analysis based on Empirical Mode Decomposition," Energy Economics, Elsevier, vol. 30(3), pages 905-918, May.
    5. Bangzhu Zhu & Ping Wang & Julien Chevallier & Yiming Wei, 2015. "Carbon Price Analysis Using Empirical Mode Decomposition," Computational Economics, Springer;Society for Computational Economics, vol. 45(2), pages 195-206, February.
    6. Rapach, David & Zhou, Guofu, 2013. "Forecasting Stock Returns," Handbook of Economic Forecasting, Elsevier.
    7. Kumar Tiwari, Aviral & Billah Dar, Arif & Bhanja, Niyati & Shah, Aasif, 2013. "Stock Market Integration in Asian Countries: evidence from Wavelet multiple correlations," Journal of Economic Integration, Center for Economic Integration, Sejong University, vol. 28, pages 441-456.
    8. Jushan Bai & Pierre Perron, 2003. "Computation and analysis of multiple structural change models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(1), pages 1-22.
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    More about this item


    Empirical Mode Decomposition; stock prices; S&P 500 Index; United States;

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)


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