IDEAS home Printed from https://ideas.repec.org/a/eee/reveco/v10y2001i4p353-368.html
   My bibliography  Save this article

Nonlinear predictability of stock market returns: Evidence from nonparametric and threshold models

Author

Listed:
  • McMillan, David G.

Abstract

No abstract is available for this item.

Suggested Citation

  • McMillan, David G., 2001. "Nonlinear predictability of stock market returns: Evidence from nonparametric and threshold models," International Review of Economics & Finance, Elsevier, vol. 10(4), pages 353-368, December.
  • Handle: RePEc:eee:reveco:v:10:y:2001:i:4:p:353-368
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1059-0560(01)00093-4
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    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. Campbell, John Y & Hamao, Yasushi, 1992. "Predictable Stock Returns in the United States and Japan: A Study of Long-Term Capital Market Integration," Journal of Finance, American Finance Association, vol. 47(1), pages 43-69, March.
    2. Gabriel Perez‐Quiros & Allan Timmermann, 2000. "Firm Size and Cyclical Variations in Stock Returns," Journal of Finance, American Finance Association, vol. 55(3), pages 1229-1262, June.
    3. K. S. Chan & H. Tong, 1986. "On Estimating Thresholds In Autoregressive Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 7(3), pages 179-190, May.
    4. Terasvirta, T & Anderson, H M, 1992. "Characterizing Nonlinearities in Business Cycles Using Smooth Transition Autoregressive Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 7(S), pages 119-136, Suppl. De.
    5. Pagan, Adrian R. & Schwert, G. William, 1990. "Alternative models for conditional stock volatility," Journal of Econometrics, Elsevier, vol. 45(1-2), pages 267-290.
    6. Pesaran, M Hashem & Timmermann, Allan, 2000. "A Recursive Modelling Approach to Predicting UK Stock Returns," Economic Journal, Royal Economic Society, vol. 110(460), pages 159-191, January.
    7. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
    8. Aman Ullah, 1988. "Non-parametric Estimation of Econometric Functionals," Canadian Journal of Economics, Canadian Economics Association, vol. 21(3), pages 625-658, August.
    9. Campbell, John Y., 1987. "Stock returns and the term structure," Journal of Financial Economics, Elsevier, vol. 18(2), pages 373-399, June.
    10. French, Kenneth R. & Schwert, G. William & Stambaugh, Robert F., 1987. "Expected stock returns and volatility," Journal of Financial Economics, Elsevier, vol. 19(1), pages 3-29, September.
    11. Glosten, Lawrence R & Jagannathan, Ravi & Runkle, David E, 1993. "On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks," Journal of Finance, American Finance Association, vol. 48(5), pages 1779-1801, December.
    12. Qi, Min, 1999. "Nonlinear Predictability of Stock Returns Using Financial and Economic Variables," Journal of Business & Economic Statistics, American Statistical Association, vol. 17(4), pages 419-429, October.
    13. Keim, Donald B. & Stambaugh, Robert F., 1986. "Predicting returns in the stock and bond markets," Journal of Financial Economics, Elsevier, vol. 17(2), pages 357-390, December.
    14. Fama, Eugene F. & French, Kenneth R., 1989. "Business conditions and expected returns on stocks and bonds," Journal of Financial Economics, Elsevier, vol. 25(1), pages 23-49, November.
    15. P. M. Robinson, 1983. "Nonparametric Estimators For Time Series," Journal of Time Series Analysis, Wiley Blackwell, vol. 4(3), pages 185-207, May.
    16. Pesaran, M Hashem & Timmermann, Allan, 1995. "Predictability of Stock Returns: Robustness and Economic Significance," Journal of Finance, American Finance Association, vol. 50(4), pages 1201-1228, September.
    17. Cochrane, John H, 1991. "Production-Based Asset Pricing and the Link between Stock Returns and Economic Fluctuations," Journal of Finance, American Finance Association, vol. 46(1), pages 209-237, March.
    18. Poterba, James M. & Summers, Lawrence H., 1988. "Mean reversion in stock prices : Evidence and Implications," Journal of Financial Economics, Elsevier, vol. 22(1), pages 27-59, October.
    19. Balvers, Ronald J & Cosimano, Thomas F & McDonald, Bill, 1990. "Predicting Stock Returns in an Efficient Market," Journal of Finance, American Finance Association, vol. 45(4), pages 1109-1128, September.
    20. Ferson, Wayne E & Harvey, Campbell R, 1993. "The Risk and Predictability of International Equity Returns," The Review of Financial Studies, Society for Financial Studies, vol. 6(3), pages 527-566.
    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. Daiki Maki & Yasushi Ota, 2019. "Robust tests for ARCH in the presence of the misspecified conditional mean: A comparison of nonparametric approches," Papers 1907.12752, arXiv.org, revised Sep 2019.
    2. Wu-Jen Chuang & Liang-Yuh Ou-Yang & Wen-Chen Lo, 2009. "Nonlinear Market Dynamics Between Stock Returns And Trading Volume: Empirical Evidences From Asian Stock Markets," Analele Stiintifice ale Universitatii "Alexandru Ioan Cuza" din Iasi - Stiinte Economice (1954-2015), Alexandru Ioan Cuza University, Faculty of Economics and Business Administration, vol. 56, pages 621-634, November.
    3. Zheng Guihuan & Shang Yan & Wu Ying & Wang Jue, 2014. "A Study on the Asymmetry in the Role of Monetary Policy by Using STR model," Journal of Systems Science and Information, De Gruyter, vol. 2(3), pages 236-243, June.
    4. Dahmene, Meriam & Boughrara, Adel & Slim, Skander, 2021. "Nonlinearity in stock returns: Do risk aversion, investor sentiment and, monetary policy shocks matter?," International Review of Economics & Finance, Elsevier, vol. 71(C), pages 676-699.
    5. David E. Rapach & Mark E. Wohar, 2005. "Valuation ratios and long‐horizon stock price predictability," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(3), pages 327-344, March.
    6. Songtao Wu & Jianmin He & Chao Wang, 2017. "Effects of Common Factors on Dynamics of Stocks Traded by Investors with Limited Information Capacity," Discrete Dynamics in Nature and Society, Hindawi, vol. 2017, pages 1-15, September.
    7. Sun, Yuying & Han, Ai & Hong, Yongmiao & Wang, Shouyang, 2018. "Threshold autoregressive models for interval-valued time series data," Journal of Econometrics, Elsevier, vol. 206(2), pages 414-446.
    8. Gupta, Rangan & Modise, Mampho P., 2013. "Macroeconomic Variables and South African Stock Return Predictability," Economic Modelling, Elsevier, vol. 30(C), pages 612-622.
    9. Rilwan Sakariyahu & Mohamed Sherif & Audrey Paterson & Eleni Chatzivgeri, 2021. "Sentiment‐Apt investors and UK sector returns," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(3), pages 3321-3351, July.
    10. Chang, Kuang-Liang, 2009. "Do macroeconomic variables have regime-dependent effects on stock return dynamics? Evidence from the Markov regime switching model," Economic Modelling, Elsevier, vol. 26(6), pages 1283-1299, November.
    11. Seyyed Ali Paytakhti Oskooe, 2012. "Nonlinear Adjustment of Emerging Stock Market Returns: Symmetrical or Asymmetrical," International Journal of Economics and Financial Issues, Econjournals, vol. 2(2), pages 179-183.
    12. Liam Gallagher & Mark Hutchinson & John O’Brien, 2018. "Does Convertible Arbitrage Risk Exposure Vary Through Time?," Review of Pacific Basin Financial Markets and Policies (RPBFMP), World Scientific Publishing Co. Pte. Ltd., vol. 21(04), pages 1-25, December.
    13. Andreas Röthig, 2009. "Microeconomic Risk Management and Macroeconomic Stability," Lecture Notes in Economics and Mathematical Systems, Springer, number 978-3-642-01565-6, October.
    14. Babangida, Jamilu Said, 2023. "Nonlinearity in emerging market indices: A comprehensive study of stock exchange market dynamics," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 72, pages 23-37.
    15. Nektarios Aslanidis, 2002. "Smooth Transition Regression Models in UK Stock Returns," Working Papers 0201, University of Crete, Department of Economics.
    16. Angela J. Black & David G. McMillan, 2004. "Non‐linear Predictability of Value and Growth Stocks and Economic Activity," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 31(3‐4), pages 439-474, April.
    17. Tania Morris & Jules Comeau, 2020. "Portfolio creation using artificial neural networks and classification probabilities: a Canadian study," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 34(2), pages 133-163, June.
    18. Hosseini, Seyed Soheil & Wormald, Nick & Tian, Tianhai, 2021. "A Weight-based Information Filtration Algorithm for Stock-correlation Networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 563(C).
    19. David G. McMillan, 2003. "Non‐linear Predictability of UK Stock Market Returns," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 65(5), pages 557-573, December.
    20. Nektarios Aslanidis, 2002. "Regime-switching behaviour in European," Working Papers 0202, University of Crete, Department of Economics.
    21. Kim, Sei-Wan & Mollick, André V. & Nam, Kiseok, 2008. "Common nonlinearities in long-horizon stock returns: Evidence from the G-7 stock markets," Global Finance Journal, Elsevier, vol. 19(1), pages 19-31.
    22. Nektarios Aslanidis & Denise R. Osborn & Marianne Sensier, 2008. "Co-movements between US and UK stock prices: the roles of macroeconomic information and time-varying conditional correlations," Centre for Growth and Business Cycle Research Discussion Paper Series 96, Economics, The University of Manchester.
    23. Tao You & Paweł Fiedor & Artur Hołda, 2015. "Network Analysis of the Shanghai Stock Exchange Based on Partial Mutual Information," JRFM, MDPI, vol. 8(2), pages 1-19, June.
    24. Yener Coskun & Nicholas Apergis & Esra Alp Coskun, 2022. "Nonlinear responses of consumption to wealth, income, and interest rate shocks," Empirical Economics, Springer, vol. 63(3), pages 1293-1335, September.
    25. repec:grz:wpaper:2012-02 is not listed 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. Angela J. Black & David G. McMillan, 2004. "Non‐linear Predictability of Value and Growth Stocks and Economic Activity," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 31(3‐4), pages 439-474, April.
    2. David McMillan, 2004. "Non-linear predictability of UK stock market returns," Money Macro and Finance (MMF) Research Group Conference 2003 63, Money Macro and Finance Research Group.
    3. David G. McMillan, 2003. "Non‐linear Predictability of UK Stock Market Returns," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 65(5), pages 557-573, December.
    4. David McMillan & Mark Wohar, 2011. "Sum of the parts stock return forecasting: international evidence," Applied Financial Economics, Taylor & Francis Journals, vol. 21(12), pages 837-845.
    5. Christos Avdoulas & Stelios Bekiros & Sabri Boubaker, 2018. "Evolutionary-based return forecasting with nonlinear STAR models: evidence from the Eurozone peripheral stock markets," Annals of Operations Research, Springer, vol. 262(2), pages 307-333, March.
    6. Klein, B. D. & Rossin, D. F., 1999. "Data quality in neural network models: effect of error rate and magnitude of error on predictive accuracy," Omega, Elsevier, vol. 27(5), pages 569-582, October.
    7. Massimo Guidolin & Stuart Hyde & David McMillan & Sadayuki Ono, 2014. "Does the Macroeconomy Predict UK Asset Returns in a Nonlinear Fashion? Comprehensive Out-of-Sample Evidence," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 76(4), pages 510-535, August.
    8. McMillan, David G., 2007. "Non-linear forecasting of stock returns: Does volume help?," International Journal of Forecasting, Elsevier, vol. 23(1), pages 115-126.
    9. Angela J. Black & David G. McMillan, 2004. "Non‐linear Predictability of Value and Growth Stocks and Economic Activity," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 31(3‐4), pages 439-474, April.
    10. Thomas D. Tallarini, Jr. & Harold H. Zhang, 2005. "External Habit and the Cyclicality of Expected Stock Returns," The Journal of Business, University of Chicago Press, vol. 78(3), pages 1023-1048, May.
    11. Smith, Simon C., 2021. "International stock return predictability," International Review of Financial Analysis, Elsevier, vol. 78(C).
    12. 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.
    13. Guidolin, Massimo & Hyde, Stuart & McMillan, David & Ono, Sadayuki, 2009. "Non-linear predictability in stock and bond returns: When and where is it exploitable?," International Journal of Forecasting, Elsevier, vol. 25(2), pages 373-399.
    14. Nektarios Aslanidis & Denise Osborn & Marianne Sensier, 2003. "Explaining movements in UK stock prices:," Working Papers 0302, University of Crete, Department of Economics.
    15. Priestley, Richard, 2001. "Time-varying persistence in expected returns," Journal of Banking & Finance, Elsevier, vol. 25(7), pages 1271-1286, July.
    16. Chauvet, Marcelle & Potter, Simon, 2001. "Nonlinear Risk," Macroeconomic Dynamics, Cambridge University Press, vol. 5(4), pages 621-646, September.
    17. Leland E. Farmer & Lawrence Schmidt & Allan Timmermann, 2023. "Pockets of Predictability," Journal of Finance, American Finance Association, vol. 78(3), pages 1279-1341, June.
    18. Tania Morris & Jules Comeau, 2020. "Portfolio creation using artificial neural networks and classification probabilities: a Canadian study," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 34(2), pages 133-163, June.
    19. Michael Cooper & Huseyin Gulen, 2006. "Is Time-Series-Based Predictability Evident in Real Time?," The Journal of Business, University of Chicago Press, vol. 79(3), pages 1263-1292, May.
    20. Najeeb, Faiq & Masih, Mansur, 2016. "Macroeconomic variables and stock returns: evidence from Singapore," MPRA Paper 98778, University Library of Munich, Germany.

    More about this item

    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:reveco:v:10:y:2001:i:4:p:353-368. 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/inca/620165 .

    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.