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A spectral approach to stock market performance

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  • Ignacio Escanuela Romana
  • Clara Escanuela Nieves

Abstract

We pose the estimation and predictability of stock market performance. Three cases are taken: US, Japan, Germany, the monthly index of the value of realized investment in stocks, prices plus the value of dividend payments (OECD data). Once deflated and trend removed, harmonic analysis is applied. The series are taken with and without the periods with evidence of exogenous shocks. The series are erratic and the random walk hypothesis is reasonably falsified. The estimation reveals relevant hidden periodicities, which approximate stock value movements. From July 2008 onwards, it is successfully analyzed whether the subsequent fall in share value would have been predictable. Again, the data are irregular and scattered, but the sum of the first five harmonics in relevance anticipates the fall in stock market values that followed.

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  • Ignacio Escanuela Romana & Clara Escanuela Nieves, 2023. "A spectral approach to stock market performance," Papers 2305.05762, arXiv.org.
    • Handle: RePEc:arx:papers:2305.05762
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    1. Adam, Klaus & Merkel, Sebastian, 2019. "Stock Price Cycles and Business Cycles," CEPR Discussion Papers 13866, C.E.P.R. Discussion Papers.
    2. Uebele, Martin & Ritschl, Albrecht, 2009. "Stock markets and business cycle comovement in Germany before World War I: Evidence from spectral analysis," Journal of Macroeconomics, Elsevier, vol. 31(1), pages 35-57, March.
    3. Min Shu & Wei Zhu, 2019. "Diagnosis and Prediction of the 2015 Chinese Stock Market Bubble," Papers 1905.09633, arXiv.org, revised Jun 2019.
    4. Paul Beaudry & Dana Galizia & Franck Portier, 2020. "Putting the Cycle Back into Business Cycle Analysis," American Economic Review, American Economic Association, vol. 110(1), pages 1-47, January.
    5. Basak, Suryoday & Kar, Saibal & Saha, Snehanshu & Khaidem, Luckyson & Dey, Sudeepa Roy, 2019. "Predicting the direction of stock market prices using tree-based classifiers," The North American Journal of Economics and Finance, Elsevier, vol. 47(C), pages 552-567.
    6. Barro, Robert J. & Ursúa, José F., 2017. "Stock-market crashes and depressions," Research in Economics, Elsevier, vol. 71(3), pages 384-398.
    7. Burton G. Malkiel, 2003. "The Efficient Market Hypothesis and Its Critics," Working Papers 111, Princeton University, Department of Economics, Center for Economic Policy Studies..
    8. Burton G. Malkiel, 2003. "The Efficient Market Hypothesis and Its Critics," Working Papers 111, Princeton University, Department of Economics, Center for Economic Policy Studies..
    9. Robert J. Shiller, 1987. "Investor Behavior in the October 1987 Stock Market Crash: Survey Evidence," NBER Working Papers 2446, National Bureau of Economic Research, Inc.
    10. repec:pri:cepsud:91malkiel is not listed on IDEAS
    11. Peter F. Christoffersen & Francis X. Diebold, 2006. "Financial Asset Returns, Direction-of-Change Forecasting, and Volatility Dynamics," Management Science, INFORMS, vol. 52(8), pages 1273-1287, August.
    12. Andrew W. Lo & Harry Mamaysky & Jiang Wang, 2000. "Foundations of Technical Analysis: Computational Algorithms, Statistical Inference, and Empirical Implementation," Journal of Finance, American Finance Association, vol. 55(4), pages 1705-1765, August.
    13. Fama, Eugene F, 1970. "Efficient Capital Markets: A Review of Theory and Empirical Work," Journal of Finance, American Finance Association, vol. 25(2), pages 383-417, May.
    14. Andrew W. Lo, A. Craig MacKinlay, 1988. "Stock Market Prices do not Follow Random Walks: Evidence from a Simple Specification Test," The Review of Financial Studies, Society for Financial Studies, vol. 1(1), pages 41-66.
    15. Caporin, Massimiliano & Ranaldo, Angelo & Santucci de Magistris, Paolo, 2013. "On the predictability of stock prices: A case for high and low prices," Journal of Banking & Finance, Elsevier, vol. 37(12), pages 5132-5146.
    16. Metcalf, Gilbert E. & Hassett, Kevin A., 1995. "Investment under alternative return assumptions Comparing random walks and mean reversion," Journal of Economic Dynamics and Control, Elsevier, vol. 19(8), pages 1471-1488, November.
    17. Burton G. Malkiel, 2003. "The Efficient Market Hypothesis and Its Critics," Journal of Economic Perspectives, American Economic Association, vol. 17(1), pages 59-82, Winter.
    18. Rui Dias & Nuno Teixeira & Veronika Machova & Pedro Pardal & Jakub Horak & Marek Vochozka, 2020. "Random walks and market efficiency tests: evidence on US, Chinese and European capital markets within the context of the global Covid-19 pandemic," Oeconomia Copernicana, Institute of Economic Research, vol. 11(4), pages 585-608, December.
    19. Ashley, Richard A & Patterson, Douglas M, 1989. "Linear versus Nonlinear Macroeconomies: A Statistical Test," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 30(3), pages 685-704, August.
    20. Fischer, Thomas & Krauss, Christopher, 2018. "Deep learning with long short-term memory networks for financial market predictions," European Journal of Operational Research, Elsevier, vol. 270(2), pages 654-669.
    21. Ludwig O. Dittrich & Pavel Srbek, 2020. "Is Violation of the Random Walk Assumption an Exception or a Rule in Capital Markets?," Atlantic Economic Journal, Springer;International Atlantic Economic Society, vol. 48(4), pages 491-501, December.
    22. Akgiray, Vedat, 1989. "Conditional Heteroscedasticity in Time Series of Stock Returns: Evidence and Forecasts," The Journal of Business, University of Chicago Press, vol. 62(1), pages 55-80, January.
    23. Chen Ping, 1996. "A Random Walk or Color Chaos on the Stock Market? Time-Frequency Analysis of S&P Indexes," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 1(2), pages 1-19, July.
    24. Kian‐Ping Lim & Robert Brooks, 2011. "The Evolution Of Stock Market Efficiency Over Time: A Survey Of The Empirical Literature," Journal of Economic Surveys, Wiley Blackwell, vol. 25(1), pages 69-108, February.
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