IDEAS home Printed from https://ideas.repec.org/a/eee/pacfin/v71y2022ics0927538x21001906.html
   My bibliography  Save this article

Predicting the Australian equity risk premium

Author

Listed:
  • Jurdi, Doureige J.

Abstract

This paper examines the predictive performance of a range of financial, economic, and sentiment variables that may predict the Australian All Ordinaries index equity risk premium using data for the last 28 years (1992–2020). The methods employed address a range of potential econometric biases that affect inference based on the predictive regression. Results show consistent in-sample and out-of-sample predictability evidence for various predictors, including the dividend yield, interest rates, and sentiment at selected forecasting horizons ranging from one month to one year. The analysis reveals new insights about time-varying predictability patterns in the Australian stock market and identifies phases of predictability in the time series. For several predictors, results show that mean-variance investors may rely on forecasts generated by the predictive regression to derive significant utility gains. Additional tests indicate that the predictability evidence is robust to the microstructure bias and variable selection bias for several predictors used in the analysis.

Suggested Citation

  • Jurdi, Doureige J., 2022. "Predicting the Australian equity risk premium," Pacific-Basin Finance Journal, Elsevier, vol. 71(C).
  • Handle: RePEc:eee:pacfin:v:71:y:2022:i:c:s0927538x21001906
    DOI: 10.1016/j.pacfin.2021.101683
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0927538X21001906
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.pacfin.2021.101683?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. Ivo Welch & Amit Goyal, 2008. "A Comprehensive Look at The Empirical Performance of Equity Premium Prediction," Review of Financial Studies, Society for Financial Studies, vol. 21(4), pages 1455-1508, July.
    2. Dai, Zhifeng & Zhu, Huan, 2020. "Stock return predictability from a mixed model perspective," Pacific-Basin Finance Journal, Elsevier, vol. 60(C).
    3. Malcolm Baker & Jeffrey Wurgler, 2000. "The Equity Share in New Issues and Aggregate Stock Returns," Journal of Finance, American Finance Association, vol. 55(5), pages 2219-2257, October.
    4. Bannigidadmath, Deepa & Narayan, Paresh Kumar, 2016. "Stock return predictability and determinants of predictability and profits," Emerging Markets Review, Elsevier, vol. 26(C), pages 153-173.
    5. 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.
    6. Foster, F Douglas & Smith, Tom & Whaley, Robert E, 1997. "Assessing Goodness-of-Fit of Asset Pricing Models: The Distribution of the Maximal R-Squared," Journal of Finance, American Finance Association, vol. 52(2), pages 591-607, June.
    7. Christopher J. Neely & David E. Rapach & Jun Tu & Guofu Zhou, 2014. "Forecasting the Equity Risk Premium: The Role of Technical Indicators," Management Science, INFORMS, vol. 60(7), pages 1772-1791, July.
    8. Robert Faff & Richard Heaney, 1999. "An examination of the relationship between Australian industry equity returns and expected inflation," Applied Economics, Taylor & Francis Journals, vol. 31(8), pages 915-933.
    9. Zhang, Yaojie & Wei, Yu & Ma, Feng & Yi, Yongsheng, 2019. "Economic constraints and stock return predictability: A new approach," International Review of Financial Analysis, Elsevier, vol. 63(C), pages 1-9.
    10. Stambaugh, Robert F., 1999. "Predictive regressions," Journal of Financial Economics, Elsevier, vol. 54(3), pages 375-421, December.
    11. Amihud, Yakov & Hurvich, Clifford M. & Wang, Yi, 2010. "Predictive regression with order-p autoregressive predictors," Journal of Empirical Finance, Elsevier, vol. 17(3), pages 513-525, June.
    12. Hodrick, Robert J, 1992. "Dividend Yields and Expected Stock Returns: Alternative Procedures for Inference and Measurement," Review of Financial Studies, Society for Financial Studies, vol. 5(3), pages 357-386.
    13. Richardson, Matthew & Stock, James H., 1989. "Drawing inferences from statistics based on multiyear asset returns," Journal of Financial Economics, Elsevier, vol. 25(2), pages 323-348, December.
    14. Devpura, Neluka & Narayan, Paresh Kumar & Sharma, Susan Sunila, 2018. "Is stock return predictability time-varying?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 52(C), pages 152-172.
    15. Yao, Juan & Gao, Jiti & Alles, Lakshman, 2005. "Dynamic investigation into the predictability of Australian industrial stock returns: Using financial and economic information," Pacific-Basin Finance Journal, Elsevier, vol. 13(2), pages 225-245, March.
    16. Rapach, David E. & Wohar, Mark E., 2006. "In-sample vs. out-of-sample tests of stock return predictability in the context of data mining," Journal of Empirical Finance, Elsevier, vol. 13(2), pages 231-247, March.
    17. Newey, Whitney & West, Kenneth, 2014. "A simple, positive semi-definite, heteroscedasticity and autocorrelation consistent covariance matrix," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 33(1), pages 125-132.
    18. John Y. Campbell & Samuel B. Thompson, 2008. "Predicting Excess Stock Returns Out of Sample: Can Anything Beat the Historical Average?," Review of Financial Studies, Society for Financial Studies, vol. 21(4), pages 1509-1531, July.
    19. Afsaneh Bahrami & Abul Shamsuddin & Katherine Uylangco, 2018. "Out‐of‐sample stock return predictability in emerging markets," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 58(3), pages 727-750, September.
    20. Dong-Hyun Ahn & Jacob Boudoukh & Matthew Richardson & Robert F. Whitelaw, 2002. "Partial Adjustment or Stale Prices? Implications from Stock Index and Futures Return Autocorrelations," Review of Financial Studies, Society for Financial Studies, vol. 15(2), pages 655-689, March.
    21. Walter Boudry & Philip Gray, 2003. "Assessing the Economic Significance of Return Predictability: A Research Note," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 30(9-10), pages 1305-1326.
    22. Wayne E. Ferson & Sergei Sarkissian & Timothy T. Simin, 2003. "Spurious Regressions in Financial Economics?," Journal of Finance, American Finance Association, vol. 58(4), pages 1393-1413, August.
    23. Walter Boudry & Philip Gray, 2003. "Assessing the Economic Significance of Return Predictability: A Research Note," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 30(9‐10), pages 1305-1326, December.
    24. Lo, Andrew W & MacKinlay, A Craig, 1990. "Data-Snooping Biases in Tests of Financial Asset Pricing Models," Review of Financial Studies, Society for Financial Studies, vol. 3(3), pages 431-467.
    25. Timmermann, Allan, 2008. "Reply to the discussion of Elusive Return Predictability," International Journal of Forecasting, Elsevier, vol. 24(1), pages 29-30.
    26. Dangl, Thomas & Halling, Michael, 2012. "Predictive regressions with time-varying coefficients," Journal of Financial Economics, Elsevier, vol. 106(1), pages 157-181.
    27. Bossaerts, Peter & Hillion, Pierre, 1999. "Implementing Statistical Criteria to Select Return Forecasting Models: What Do We Learn?," Review of Financial Studies, Society for Financial Studies, vol. 12(2), pages 405-428.
    28. Granger, C. W. J. & Newbold, P., 1974. "Spurious regressions in econometrics," Journal of Econometrics, Elsevier, vol. 2(2), pages 111-120, July.
    29. Wayne E. Ferson & Sergei Sarkissian & Timothy T. Simin, 2003. "Spurious Regressions in Financial Economics?," Journal of Finance, American Finance Association, vol. 58(4), pages 1393-1414, August.
    30. Jamie Alcock & Philip Gray, 2005. "Forecasting Stock Returns Using Model‐Selection Criteria," The Economic Record, The Economic Society of Australia, vol. 81(253), pages 135-151, June.
    31. Mele, Antonio, 2007. "Asymmetric stock market volatility and the cyclical behavior of expected returns," Journal of Financial Economics, Elsevier, vol. 86(2), pages 446-478, November.
    32. Yiwen (Paul) Dou & David R. Gallagher & David Schneider & Terry S. Walter, 2012. "Out-of-sample stock return predictability in Australia," Australian Journal of Management, Australian School of Business, vol. 37(3), pages 461-479, December.
    33. Cenesizoglu, Tolga & Timmermann, Allan, 2012. "Do return prediction models add economic value?," Journal of Banking & Finance, Elsevier, vol. 36(11), pages 2974-2987.
    34. Charles, Amélie & Darné, Olivier & Kim, Jae H., 2017. "International stock return predictability: Evidence from new statistical tests," International Review of Financial Analysis, Elsevier, vol. 54(C), pages 97-113.
    35. Li, Bob & Stork, Thomas & Chai, Daniel & Ee, Mong Shan & Ang, Hong Nee, 2014. "Momentum effect in Australian equities: Revisit, armed with short-selling ban and risk factors," Pacific-Basin Finance Journal, Elsevier, vol. 27(C), pages 19-31.
    36. Nelson, Charles R & Kim, Myung J, 1993. "Predictable Stock Returns: The Role of Small Sample Bias," Journal of Finance, American Finance Association, vol. 48(2), pages 641-661, June.
    37. 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.
    38. Philip Gray, 2008. "Economic significance of predictability in Australian equities," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 48(5), pages 783-805, December.
    39. Timmermann, Allan, 2008. "Elusive return predictability," International Journal of Forecasting, Elsevier, vol. 24(1), pages 1-18.
    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. Francesco Cesarone & Raffaello Cesetti & Giuseppe Orlando & Manuel Luis Martino & Jacopo Maria Ricci, 2022. "Comparing SSD-Efficient Portfolios with a Skewed Reference Distribution," Mathematics, MDPI, vol. 11(1), pages 1-20, December.
    2. Pankaj Agrrawal, 2023. "The Gibbons, Ross, and Shanken Test for Portfolio Efficiency: A Note Based on Its Trigonometric Properties," Mathematics, MDPI, vol. 11(9), pages 1-19, May.
    3. Renata G. Alcoforado & Alfredo D. Egídio dos Reis & Wilton Bernardino & José António C. Santos, 2023. "Modelling Risk for Commodities in Brazil: An Application for Live Cattle Spot and Futures Prices," Commodities, MDPI, vol. 2(4), pages 1-19, November.

    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. 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.
    2. 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 129, Money Macro and Finance Research Group.
    3. Daniel Mantilla-García & Vijay Vaidyanathan, 2017. "Predicting stock returns in the presence of uncertain structural changes and sample noise," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 31(3), pages 357-391, August.
    4. Boudoukh, Jacob & Israel, Ronen & Richardson, Matthew, 2022. "Biases in long-horizon predictive regressions," Journal of Financial Economics, Elsevier, vol. 145(3), pages 937-969.
    5. Shamsi Zamenjani, Azam, 2021. "Do financial variables help predict the conditional distribution of the market portfolio?," Journal of Empirical Finance, Elsevier, vol. 62(C), pages 327-345.
    6. Afsaneh Bahrami & Abul Shamsuddin & Katherine Uylangco, 2018. "Out‐of‐sample stock return predictability in emerging markets," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 58(3), pages 727-750, September.
    7. Chen, Long, 2009. "On the reversal of return and dividend growth predictability: A tale of two periods," Journal of Financial Economics, Elsevier, vol. 92(1), pages 128-151, April.
    8. Yiwen (Paul) Dou & David R. Gallagher & David Schneider & Terry S. Walter, 2012. "Out-of-sample stock return predictability in Australia," Australian Journal of Management, Australian School of Business, vol. 37(3), pages 461-479, December.
    9. Dichtl, Hubert & Drobetz, Wolfgang & Neuhierl, Andreas & Wendt, Viktoria-Sophie, 2021. "Data snooping in equity premium prediction," International Journal of Forecasting, Elsevier, vol. 37(1), pages 72-94.
    10. Bätje, Fabian & Menkhoff, Lukas, 2016. "Predicting the equity premium via its components," VfS Annual Conference 2016 (Augsburg): Demographic Change 145789, Verein für Socialpolitik / German Economic Association.
    11. Rapach, David E. & Wohar, Mark E., 2006. "In-sample vs. out-of-sample tests of stock return predictability in the context of data mining," Journal of Empirical Finance, Elsevier, vol. 13(2), pages 231-247, March.
    12. Jiang, Fuwei & Lee, Joshua & Martin, Xiumin & Zhou, Guofu, 2019. "Manager sentiment and stock returns," Journal of Financial Economics, Elsevier, vol. 132(1), pages 126-149.
    13. Yin, Anwen, 2020. "Equity premium prediction and optimal portfolio decision with Bagging," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).
    14. Puneet Handa, 2006. "Does Stock Return Predictability Imply Improved Asset Allocation and Performance? Evidence from the U.S. Stock Market (1954–2002)," The Journal of Business, University of Chicago Press, vol. 79(5), pages 2423-2468, September.
    15. 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.
    16. Ferreira, Miguel A. & Santa-Clara, Pedro, 2011. "Forecasting stock market returns: The sum of the parts is more than the whole," Journal of Financial Economics, Elsevier, vol. 100(3), pages 514-537, June.
    17. Christopher J. Neely & David E. Rapach & Jun Tu & Guofu Zhou, 2014. "Forecasting the Equity Risk Premium: The Role of Technical Indicators," Management Science, INFORMS, vol. 60(7), pages 1772-1791, July.
    18. Gupta, Rangan & Hammoudeh, Shawkat & Modise, Mampho P. & Nguyen, Duc Khuong, 2014. "Can economic uncertainty, financial stress and consumer sentiments predict U.S. equity premium?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 33(C), pages 367-378.
    19. Wachter, Jessica A. & Warusawitharana, Missaka, 2009. "Predictable returns and asset allocation: Should a skeptical investor time the market?," Journal of Econometrics, Elsevier, vol. 148(2), pages 162-178, February.
    20. Phan, Dinh Hoang Bach & Sharma, Susan Sunila & Tran, Vuong Thao, 2018. "Can economic policy uncertainty predict stock returns? Global evidence," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 55(C), pages 134-150.

    More about this item

    Keywords

    Return premium predictability; Time-varying predictability; Out-of-sample forecasting; Asset allocation; Econometric bias; Financial and economic predictors; Sentiment;
    All these keywords.

    JEL classification:

    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • 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:pacfin:v:71:y:2022:i:c:s0927538x21001906. 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/pacfin .

    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.