IDEAS home Printed from https://ideas.repec.org/p/arx/papers/2305.05762.html
   My bibliography  Save this paper

A spectral approach to stock market performance

Author

Listed:
  • 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.

Suggested Citation

  • 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
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/2305.05762
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    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.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Cristi Spulbar & Ramona Birau & Lucian Florin Spulbar, 2021. "A Critical Survey on Efficient Market Hypothesis (EMH), Adaptive Market Hypothesis (AMH) and Fractal Markets Hypothesis (FMH) Considering Their Implication on Stock Markets Behavior," Ovidius University Annals, Economic Sciences Series, Ovidius University of Constantza, Faculty of Economic Sciences, vol. 0(2), pages 1161-1165, December.
    2. Saqib Farid & Rubeena Tashfeen & Tahseen Mohsan & Arsal Burhan, 2023. "Forecasting stock prices using a data mining method: Evidence from emerging market," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(2), pages 1911-1917, April.
    3. Brice Corgnet & Cary Deck & Mark DeSantis & David Porter, 2022. "Forecasting Skills in Experimental Markets: Illusion or Reality?," Management Science, INFORMS, vol. 68(7), pages 5216-5232, July.
    4. 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.
    5. Rompotis, Gerasimos G., 2011. "Testing weak-form efficiency of exchange traded funds market," MPRA Paper 36020, University Library of Munich, Germany.
    6. Ushna Akber & Nabeel Muhammad, 2014. "Is Pakistan Stock Market Moving towards Weak-Form Efficiency? Evidence from The Karachi Stock Exchange and the Random Walk Nature of Free-Float of Shares of KSE 30 Index," Asian Economic and Financial Review, Asian Economic and Social Society, vol. 4(6), pages 808-836, June.
    7. Akber, Ushna & Muhammad, Nabeel, 2013. "Is Pakistan Stock Market moving towards Weak-form efficiency? Evidence from the Karachi Stock Exchange and the Random Walk Nature of free-float of shares of KSE 30 Index," MPRA Paper 49128, University Library of Munich, Germany.
    8. repec:idn:journl:v:1:y:2019:i:sp1:p:1-26 is not listed on IDEAS
    9. Firat Melih Yilmaz & Engin Yildiztepe, 2024. "Statistical Evaluation of Deep Learning Models for Stock Return Forecasting," Computational Economics, Springer;Society for Computational Economics, vol. 63(1), pages 221-244, January.
    10. Deniz Erer & Elif Erer & Selim Güngör, 2023. "The aggregate and sectoral time-varying market efficiency during crisis periods in Turkey: a comparative analysis with COVID-19 outbreak and the global financial crisis," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-25, December.
    11. Ashok Chanabasangouda Patil & Shailesh Rastogi, 2019. "Time-Varying Price–Volume Relationship and Adaptive Market Efficiency: A Survey of the Empirical Literature," JRFM, MDPI, vol. 12(2), pages 1-18, June.
    12. Stéphane Goutte & David Guerreiro & Bilel Sanhaji & Sophie Saglio & Julien Chevallier, 2019. "International Financial Markets," Post-Print halshs-02183053, HAL.
    13. Kim, Jae H. & Shamsuddin, Abul & Lim, Kian-Ping, 2011. "Stock return predictability and the adaptive markets hypothesis: Evidence from century-long U.S. data," Journal of Empirical Finance, Elsevier, vol. 18(5), pages 868-879.
    14. Perry Sadorsky, 2021. "A Random Forests Approach to Predicting Clean Energy Stock Prices," JRFM, MDPI, vol. 14(2), pages 1-20, January.
    15. Bernard Njindan Iyke, 2019. "A Test Of The Efficiency Of The Foreign Exchange Market In Indonesia," Bulletin of Monetary Economics and Banking, Bank Indonesia, vol. 21(12th BMEB), pages 439-464, January.
    16. Sensoy, Ahmet & Aras, Guler & Hacihasanoglu, Erk, 2015. "Predictability dynamics of Islamic and conventional equity markets," The North American Journal of Economics and Finance, Elsevier, vol. 31(C), pages 222-248.
    17. Sensoy, Ahmet & Tabak, Benjamin M., 2015. "Time-varying long term memory in the European Union stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 436(C), pages 147-158.
    18. Bell, Peter N, 2013. "New Testing Procedures to Assess Market Efficiency with Trading Rules," MPRA Paper 46701, University Library of Munich, Germany.
    19. Jitka Veselá & Alžběta Zíková, 2022. "Are the Czech, Polish, German and Dutch markets taking a random walk? [Konají český, polský, německý a nizozemský trh náhodnou procházku?]," Český finanční a účetní časopis, Prague University of Economics and Business, vol. 2022(2), pages 19-38.
    20. Ziliotto, Arianna & Serati, Massimiliano, 2015. "The semi-strong efficiency debate: In search of a new testing framework," Research in International Business and Finance, Elsevier, vol. 34(C), pages 412-438.
    21. Angelini, Giovanni & De Angelis, Luca & Singleton, Carl, 2022. "Informational efficiency and behaviour within in-play prediction markets," International Journal of Forecasting, Elsevier, vol. 38(1), pages 282-299.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:arx:papers:2305.05762. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.