IDEAS home Printed from https://ideas.repec.org/a/eee/finlet/v13y2015icp196-204.html
   My bibliography  Save this article

Predicting severe simultaneous bear stock markets using macroeconomic variables as leading indicators

Author

Listed:
  • Wu, Shue-Jen
  • Lee, Wei-Ming

Abstract

This paper investigates the predictability of severe simultaneous bear stock markets in 10 industrialized countries. Based on a set of US macroeconomic variables, all of the in-sample and out-of-sample results from probit models with a single macroeconomic variable and with more than one macroeconomic variables confirm that severe simultaneous bear stock markets are indeed predictable. In particular, while the inflation rate is the strongest predictor at longer forecast horizons, the relative long-term government bond yield and the stock return perform best at shorter forecast horizons.

Suggested Citation

  • Wu, Shue-Jen & Lee, Wei-Ming, 2015. "Predicting severe simultaneous bear stock markets using macroeconomic variables as leading indicators," Finance Research Letters, Elsevier, vol. 13(C), pages 196-204.
    • Handle: RePEc:eee:finlet:v:13:y:2015:i:c:p:196-204
    DOI: 10.1016/j.frl.2015.01.003
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1544612315000045
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.frl.2015.01.003?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Todd E. Clark, 2004. "Can out-of-sample forecast comparisons help prevent overfitting?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 23(2), pages 115-139.
    2. Arturo Estrella & Frederic S. Mishkin, 1998. "Predicting U.S. Recessions: Financial Variables As Leading Indicators," The Review of Economics and Statistics, MIT Press, vol. 80(1), pages 45-61, February.
    3. Hui Chen, 2010. "Macroeconomic Conditions and the Puzzles of Credit Spreads and Capital Structure," Journal of Finance, American Finance Association, vol. 65(6), pages 2171-2212, December.
    4. Christiansen, Charlotte, 2013. "Predicting severe simultaneous recessions using yield spreads as leading indicators," Journal of International Money and Finance, Elsevier, vol. 32(C), pages 1032-1043.
    5. Wright, Jonathan H, 2000. "Alternative Variance-Ratio Tests Using Ranks and Signs," Journal of Business & Economic Statistics, American Statistical Association, vol. 18(1), pages 1-9, January.
    6. Bekaert, Geert & Harvey, Campbell R, 1995. "Time-Varying World Market Integration," Journal of Finance, American Finance Association, vol. 50(2), pages 403-444, June.
    7. Martin Lettau & Sydney Ludvigson, 2001. "Consumption, Aggregate Wealth, and Expected Stock Returns," Journal of Finance, American Finance Association, vol. 56(3), pages 815-849, June.
    8. Diebold, Francis X & Rudebusch, Glenn D, 1989. "Scoring the Leading Indicators," The Journal of Business, University of Chicago Press, vol. 62(3), pages 369-391, July.
    9. Clark, Todd E. & West, Kenneth D., 2007. "Approximately normal tests for equal predictive accuracy in nested models," Journal of Econometrics, Elsevier, vol. 138(1), pages 291-311, May.
    10. Chauvet, Marcelle & Potter, Simon, 2000. "Coincident and leading indicators of the stock market," Journal of Empirical Finance, Elsevier, vol. 7(1), pages 87-111, May.
    11. Leung, Mark T. & Daouk, Hazem & Chen, An-Sing, 2000. "Forecasting stock indices: a comparison of classification and level estimation models," International Journal of Forecasting, Elsevier, vol. 16(2), pages 173-190.
    12. Candelon, Bertrand & Piplack, Jan & Straetmans, Stefan, 2008. "On measuring synchronization of bulls and bears: The case of East Asia," Journal of Banking & Finance, Elsevier, vol. 32(6), pages 1022-1035, June.
    13. François Longin & Bruno Solnik, 2001. "Extreme Correlation of International Equity Markets," Journal of Finance, American Finance Association, vol. 56(2), pages 649-676, April.
    14. Rapach, David E. & Wohar, Mark E. & Rangvid, Jesper, 2005. "Macro variables and international stock return predictability," International Journal of Forecasting, Elsevier, vol. 21(1), pages 137-166.
    15. Chen, Shiu-Sheng, 2009. "Predicting the bear stock market: Macroeconomic variables as leading indicators," Journal of Banking & Finance, Elsevier, vol. 33(2), pages 211-223, February.
    16. Simon Gilchrist & Egon Zakrajsek, 2012. "Credit Spreads and Business Cycle Fluctuations," American Economic Review, American Economic Association, vol. 102(4), pages 1692-1720, June.
    17. David E. Rapach & Jack K. Strauss & Guofu Zhou, 2013. "International Stock Return Predictability: What Is the Role of the United States?," Journal of Finance, American Finance Association, vol. 68(4), pages 1633-1662, August.
    18. Rapach, David & Zhou, Guofu, 2013. "Forecasting Stock Returns," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 328-383, Elsevier.
    19. M. N. Hasan & R. W. Koenker, 1997. "Robust Rank Tests of the Unit Root Hypothesis," Econometrica, Econometric Society, vol. 65(1), pages 133-162, January.
    20. Nyberg, Henri, 2013. "Predicting bear and bull stock markets with dynamic binary time series models," Journal of Banking & Finance, Elsevier, vol. 37(9), pages 3351-3363.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Yongming Shi & Khalid Ahmed & Sudharshan Reddy Paramati, 2021. "Determinants of stock market development and price volatility in ASEAN plus three countries: The role of institutional quality," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(1), pages 560-572, January.
    2. Wu, Shue-Jen, 2023. "The role of the past long-run oil price changes in stock market," International Review of Economics & Finance, Elsevier, vol. 84(C), pages 274-291.
    3. Levent Bulut, 2017. "Does Statistical Significance Help to Evaluate Predictive Performance of Competing Models?," Journal of Economics and Financial Analysis, Tripal Publishing House, vol. 1(1), pages 1-13.
    4. Rui Menezes & Sonia Bentes, 2016. "Hysteresis and Duration Dependence of Financial Crises in the US: Evidence from 1871-2016," Papers 1610.00259, arXiv.org.
    5. Kim, Hyun-Seok & Min, Hong-Ghi & McDonald, Judith A., 2016. "Returns, correlations, and volatilities in equity markets: Evidence from six OECD countries during the US financial crisis," Economic Modelling, Elsevier, vol. 59(C), pages 9-22.
    6. Bentes, Sónia R., 2021. "On the hysteresis of financial crises in the US: Evidence from S&P 500," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 565(C).
    7. Salisu, Afees A. & Swaray, Raymond & Oloko, Tirimisiyu F., 2019. "Improving the predictability of the oil–US stock nexus: The role of macroeconomic variables," Economic Modelling, Elsevier, vol. 76(C), pages 153-171.
    8. Ardila, Diego & Sornette, Didier, 2016. "Dating the financial cycle with uncertainty estimates: a wavelet proposition," Finance Research Letters, Elsevier, vol. 19(C), pages 298-304.
    9. Alqaralleh, Huthaifa & Canepa, Alessandra & Chini, Zanetti, 2021. "Financial Contagion During the Covid-19 Pandemic: A Wavelet-Copula-GARCH Approach," Department of Economics and Statistics Cognetti de Martiis. Working Papers 202110, University of Turin.
    10. Borjigin, Sumuya & Yang, Yating & Yang, Xiaoguang & Sun, Leilei, 2018. "Econometric testing on linear and nonlinear dynamic relation between stock prices and macroeconomy in China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 493(C), pages 107-115.
    11. Hanna, Alan J., 2018. "A top-down approach to identifying bull and bear market states," International Review of Financial Analysis, Elsevier, vol. 55(C), pages 93-110.

    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. Chen, Nan-Kuang & Chen, Shiu-Sheng & Chou, Yu-Hsi, 2017. "Further evidence on bear market predictability: The role of the external finance premium," International Review of Economics & Finance, Elsevier, vol. 50(C), pages 106-121.
    2. Haase, Felix & Neuenkirch, Matthias, 2023. "Predictability of bull and bear markets: A new look at forecasting stock market regimes (and returns) in the US," International Journal of Forecasting, Elsevier, vol. 39(2), pages 587-605.
    3. Nyberg, Henri, 2013. "Predicting bear and bull stock markets with dynamic binary time series models," Journal of Banking & Finance, Elsevier, vol. 37(9), pages 3351-3363.
    4. Straetmans, S.T.M. & Candelon, B. & Ahmed, J., 2012. "Predicting and capitalizing on stock market bears in the U.S," Research Memorandum 019, Maastricht University, Maastricht Research School of Economics of Technology and Organization (METEOR).
    5. Nyberg, Henri & Pönkä, Harri, 2016. "International sign predictability of stock returns: The role of the United States," Economic Modelling, Elsevier, vol. 58(C), pages 323-338.
    6. Erik Kole & Dick Dijk, 2017. "How to Identify and Forecast Bull and Bear Markets?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(1), pages 120-139, January.
    7. Fernandez-Perez, Adrian & Fernández-Rodríguez, Fernando & Sosvilla-Rivero, Simón, 2014. "The term structure of interest rates as predictor of stock returns: Evidence for the IBEX 35 during a bear market," International Review of Economics & Finance, Elsevier, vol. 31(C), pages 21-33.
    8. Faria, Gonçalo & Verona, Fabio, 2018. "The equity risk premium and the low frequency of the term spread," Research Discussion Papers 7/2018, Bank of Finland.
    9. Shue-Jen Wu & Wei-Ming Lee, 2012. "Predicting the U.S. bear stock market using the consumption-wealth ratio," Economics Bulletin, AccessEcon, vol. 32(4), pages 3174-3181.
    10. , & Stein, Tobias, 2021. "Equity premium predictability over the business cycle," CEPR Discussion Papers 16357, C.E.P.R. Discussion Papers.
    11. repec:zbw:bofrdp:2018_007 is not listed on IDEAS
    12. Chen, Shiu-Sheng, 2009. "Predicting the bear stock market: Macroeconomic variables as leading indicators," Journal of Banking & Finance, Elsevier, vol. 33(2), pages 211-223, February.
    13. Nan-Kuang Chen & Han-Liang Cheng & Ching-Sheng Mao, 2014. "Identifying and forecasting house prices: a macroeconomic perspective," Quantitative Finance, Taylor & Francis Journals, vol. 14(12), pages 2105-2120, December.
    14. Faria, Gonçalo & Verona, Fabio, 2020. "The yield curve and the stock market: Mind the long run," Journal of Financial Markets, Elsevier, vol. 50(C).
    15. Wu, Shue-Jen, 2023. "The role of the past long-run oil price changes in stock market," International Review of Economics & Finance, Elsevier, vol. 84(C), pages 274-291.
    16. Kuntz, Laura-Chloé, 2020. "Beta dispersion and market timing," Journal of Empirical Finance, Elsevier, vol. 59(C), pages 235-256.
    17. Nuno Silva, 2013. "Equity Premia Predictability in the EuroZone," GEMF Working Papers 2013-22, GEMF, Faculty of Economics, University of Coimbra.
    18. Cakici, Nusret & Zaremba, Adam, 2023. "Misery on Main Street, victory on Wall Street: Economic discomfort and the cross-section of global stock returns," Journal of Banking & Finance, Elsevier, vol. 149(C).
    19. Hashmat Khan & Santosh Upadhayaya, 2020. "Does business confidence matter for investment?," Empirical Economics, Springer, vol. 59(4), pages 1633-1665, October.
    20. Tsiakas, Ilias & Li, Jiahan & Zhang, Haibin, 2020. "Equity premium prediction and the state of the economy," Journal of Empirical Finance, Elsevier, vol. 58(C), pages 75-95.
    21. Møller, Stig V. & Rangvid, Jesper, 2015. "End-of-the-year economic growth and time-varying expected returns," Journal of Financial Economics, Elsevier, vol. 115(1), pages 136-154.

    More about this item

    Keywords

    Severe simultaneous bear markets; Macroeconomic variables; Probit model; Predictability;
    All these keywords.

    JEL classification:

    • G01 - Financial Economics - - General - - - Financial Crises
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

    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:eee:finlet:v:13:y:2015:i:c:p:196-204. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/frl .

    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.