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Non-linear Predictability of UK Stock Market Returns

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  • David G. McMillan
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    Abstract

    Linear predictability of stock market returns has been widely reported. However, recently developed theoretical research has suggested that due to the interaction of noise and arbitrage traders, stock returns are inherently non-linear, whereby market dynamics differ between small and large returns. This paper examines whether an exponential smooth transition threshold model, which is capable of capturing this non-linear behaviour, can provide a better characterization of UK stock market returns than either a linear model or an alternate non-linear model. The results of both in-sample and out-of-sample specification tests support the exponential smooth transition threshold model and hence the belief that investor behaviour does differ between large and small returns. Copyright 2003 Blackwell Publishing Ltd.

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    Bibliographic Info

    Article provided by Department of Economics, University of Oxford in its journal Oxford Bulletin of Economics & Statistics.

    Volume (Year): 65 (2003)
    Issue (Month): 5 (December)
    Pages: 557-573

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    Handle: RePEc:bla:obuest:v:65:y:2003:i:5:p:557-573

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    Cited by:
    1. Kellard, Neil M. & Nankervis, John C. & Papadimitriou, Fotios I., 2010. "Predicting the equity premium with dividend ratios: Reconciling the evidence," Journal of Empirical Finance, Elsevier, Elsevier, vol. 17(4), pages 539-551, September.
    2. David G. McMillan, 2009. "Non-linear interest rate dynamics and forecasting: evidence for US and Australian interest rates," International Journal of Finance & Economics, John Wiley & Sons, Ltd., John Wiley & Sons, Ltd., vol. 14(2), pages 139-155.
    3. McMillan, David G., 2007. "Bubbles in the dividend-price ratio? Evidence from an asymmetric exponential smooth-transition model," Journal of Banking & Finance, Elsevier, Elsevier, vol. 31(3), pages 787-804, March.
    4. 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, Alexandru Ioan Cuza University, Faculty of Economics and Business Administration, Alexandru Ioan Cuza University, Faculty of Economics and Business Administration, vol. 56, pages 621-634, November.
    5. Rahman, Abdul & Saadi, Samir, 2008. "Random walk and breaking trend in financial series: An econometric critique of unit root tests," Review of Financial Economics, Elsevier, Elsevier, vol. 17(3), pages 204-212, August.
    6. Massimo Guidolin & Stuart Hyde & David McMillan & Sadayuki Ono, 2009. "Non-linear predictability in stock and bond returns: when and where is it exploitable?," Working Papers, Federal Reserve Bank of St. Louis 2008-010, Federal Reserve Bank of St. Louis.
    7. Lee, Chien-Chiang & Chiu, Yi-Bin, 2012. "The impact of real income on insurance premiums: Evidence from panel data," International Review of Economics & Finance, Elsevier, Elsevier, vol. 21(1), pages 246-260.
    8. Bildirici, Melike & Ersin, Özgür, 2012. "Nonlinear volatility models in economics: smooth transition and neural network augmented GARCH, APGARCH, FIGARCH and FIAPGARCH models," MPRA Paper 40330, University Library of Munich, Germany, revised May 2012.
    9. Neil Kellard & John Nankervis & Fotis Papadimitriou, 2007. "Predicting the UK Equity Premium with Dividend Ratios: An Out-Of-Sample Recursive Residuals Graphical Approach," Money Macro and Finance (MMF) Research Group Conference 2006, Money Macro and Finance Research Group 129, Money Macro and Finance Research Group.
    10. Gozbasi, Onur & Kucukkaplan, Ilhan & Nazlioglu, Saban, 2014. "Re-examining the Turkish stock market efficiency: Evidence from nonlinear unit root tests," Economic Modelling, Elsevier, Elsevier, vol. 38(C), pages 381-384.
    11. Massimo Guidolin & Stuart Hyde & David McMillan & Sadayuki Ono, 2010. "Does the macroeconomy predict U.K. asset returns in a nonlinear fashion? comprehensive out-of-sample evidence," Working Papers, Federal Reserve Bank of St. Louis 2010-039, Federal Reserve Bank of St. Louis.
    12. McMillan, David G., 2005. "Non-linear dynamics in international stock market returns," Review of Financial Economics, Elsevier, Elsevier, vol. 14(1), pages 81-91.
    13. McMillan, David G., 2007. "Non-linear forecasting of stock returns: Does volume help?," International Journal of Forecasting, Elsevier, Elsevier, vol. 23(1), pages 115-126.
    14. Mariano Matilla-García & Manuel Ruiz Marín & Mohammed Dore & Rina Ojeda, 2014. "Nonparametric correlation integral–based tests for linear and nonlinear stochastic processes," Decisions in Economics and Finance, Springer, Springer, vol. 37(1), pages 181-193, April.

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