Skip to main content
SpringerLink
Log in

Incorporating financial market volatility to improve forecasts of directional changes in Australian share market returns

  • Published:
Financial Markets and Portfolio Management Aims and scope Submit manuscript

Abstract

This study examines whether incorporating volatility improves the forecast of directional changes in the returns of Australia’s banking, industrial and resource sectors. This study first estimates a benchmark non-volatility logit regression model and assesses it against four estimated volatility logit models measured by mean absolute deviation, standard deviation, return squared (U2) and range. An out-of-sample prediction performance, assessed by Brier’s QPS statistic and hit ratio, confirms that volatility improves the prediction of directional changes of returns. A simple trading strategy is utilized to provide practical improvement in investors’ market timing decisions.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1

Similar content being viewed by others

Notes

  1. This work was primarily based on Jagannathan and Wang (1996), although Durack et al. (2004) extend the study by evaluating the influence of US market movements over Australian stock returns.

References

  • Amemiya, T.: Qualitative response models: a survey. J. Econ. Lit. 19, 1483–1536 (1981)

    Google Scholar 

  • Anatolyev, S., Gospodinov, L.: Modelling financial return dynamics via decomposition. J. Bus. Econ. Stat. 28, 232–245 (2010)

    Article  Google Scholar 

  • Anderson, H.M., Vahid, F.: Forecasting the volatility of Australian stock returns: do common factors help? J. Bus. Econ. Stud. 25, 76–90 (2007)

    Article  Google Scholar 

  • Anneart, J., De Ceuster., M., Valckx, N.: Financial market volatility: informative in predicting recessions. Bank of Finland Discussion Papers vol. 14, Helsinki (2001)

  • Beenstock, M., Chan, K.: Economic forces in the London stock market. Oxf. Bull. Econ. Stat. 50, 27–39 (1988)

    Article  Google Scholar 

  • Bekiros, S.D., Georgoutsos, D.: Non-linear dynamics in financial asset returns: the predictive power of the CBOE volatility index. Eur. J. Finance 14, 397–408 (2008)

    Article  Google Scholar 

  • Benson, K., Faff, R., Smith, T.: Fifty years of finance research in the Asia Pacific Basin. Account. Finance 54, 335–363 (2014)

    Article  Google Scholar 

  • Benson, K., Clarkson, P., Smith, T., Tutticci, I.: A review of accounting research in the Asia Pacific region. Australian Journal of Management 40, 36–88 (2015)

    Article  Google Scholar 

  • Bertram, W.K.: An empirical investigation of Australian Stock Exchange data. Physica A 341, 533–546 (2004)

    Article  Google Scholar 

  • Burdekin, R., Siklos, P.: Enter the dragon: Interactions between Chinese, US and Asia-Pacific equity markets 1995–2010. Pac. Basin Finance J. 20, 521–541 (2012)

    Article  Google Scholar 

  • Campbell, J., Thompson, S.: Predicting excess stock returns out of sample: can anything beat the historical average? Rev. Financ. Stud. 21, 1509–1531 (2008)

    Article  Google Scholar 

  • Chaudhuri, K., Smiles, S.: Stock market and aggregate economic activity: evidence from Australia. Appl. Financ. Econ. 14, 121–129 (2004)

    Article  Google Scholar 

  • Chen, N.-F., Roll, R., Ross, S.: Economic forces and the stock market. J. Bus. 59, 383–403 (1986)

    Article  Google Scholar 

  • Chen, C.H., Yu, W.C., Zivot, E.: Predicting stock volatility using after-hours information: evidence from the Nasdaq actively traded stocks. Int. J. Forecast. 28, 366–383 (2012)

    Article  Google Scholar 

  • Cheung, Y.W., Chinn, M., Pascual, G.: Empirical exchange rate models of the nineties: are any fit to survive? University of Santa Cruz, Department of Economics, working paper series qt12z9x4c5, Santa Cruz, CA (2003)

  • Christoffersen, P., Diebold, F.: Financial assets returns, direction of change forecasting, and volatility dynamics. Manag. Sci. 52, 1273–1287 (2006)

    Article  Google Scholar 

  • Christoffersen, P., Diebold, F., Marino, R., Tay, R., Tse, Y.: Direction-of-change forecasts based on conditional variance, skewness and kurtosis dynamics: international evidence. J. Financ. Forecast. 1, 3–24 (2007)

    Google Scholar 

  • Durack, N., Durand, R., Maller, R.: A best choice among asset pricing models? The conditional capital asset pricing model in Australia. Account. Finance 44, 139–162 (2004)

    Article  Google Scholar 

  • Durand, R., Koh, S., Watson, I.: Who moved Asian-Pacific stock markets? A further consideration of the impact of the US and Japan. Aust. J. Manag. 26, 125–146 (2001)

    Article  Google Scholar 

  • Durand, R., Scott, D.: iShares Australia: a clinical study in international behavioral finance. Int. Rev. Financ. Anal. 12, 223–239 (2003)

    Article  Google Scholar 

  • Engle, R.F., Ng, V., Rothschild, M.: Asset pricing with a factor ARCH covariance structure: empirical estimates for Treasury bills. J. Econ. 45, 213–239 (1990)

    Article  Google Scholar 

  • Engle, R.F., Susmel, R.: Common volatility in international equity markets. J. Bus. Econ. Stat. 11, 167–176 (1993)

    Google Scholar 

  • Eun, C., Shim, S.: International transmission of stock market movements. J. Financ. Quant. Anal. 24, 241–256 (1989)

    Article  Google Scholar 

  • Faust, J., Wright, J.: Efficient prediction of excess returns. Rev. Econ. Stat. 93, 647–659 (2011)

    Article  Google Scholar 

  • Fama, E., French, K.: Common risk factors in the returns on stocks and bonds. J. Financ. Econ. 33, 3–56 (1993)

    Article  Google Scholar 

  • Ferson, W., Harvey, C.: The variations of economic risk premium. J. Polit. Econ. 99, 385–415 (1991)

    Article  Google Scholar 

  • Forbes, K., Rigobon, R.: No contagion, only interdependence: measuring stock market comovements. J. Finance 57, 2223–2261 (2002)

    Article  Google Scholar 

  • Gallo, G., Otranto, E.: Volatility spillovers, interdependence and comovements: a Markow switching approach. Comput. Stat. Data Anal. 52, 311–326 (2008)

    Article  Google Scholar 

  • Gencay, R.: Optimization of technical trading strategies and the profitability in security markets. Econ. Lett. 59, 249–254 (1998)

    Article  Google Scholar 

  • Ghosh, A., Saidi, R., Johnson, K.: Who moves the Asia-Pacific stock markets—US or Japan? Empirical evidence based on the theory of cointegration. Financ. Rev. 34, 159–169 (1999)

    Article  Google Scholar 

  • Groenewold, N., Fraser, P.: Share prices and macroeconomic factors. J. Bus. Finance Account. 24, 1367–1383 (1997)

    Article  Google Scholar 

  • Hong, Y., Chung, J.: Are the directions of stock price changes predictable?. Cornell University, Ithaca (2003)

    Google Scholar 

  • Humpe, A., Macmillan, P.: Can macroeconomic variables explain long term stock market movements? A comparison of the US and Japan. Appl. Financ. Econ. 19, 111–119 (2009)

    Article  Google Scholar 

  • Jagannathan, R., Wang, Z.: The conditional CAPM and the cross-section of expected returns. J. Finance 51, 3–53 (1996)

    Article  Google Scholar 

  • Kalev, P., Liu, W.-M., Pham, P., Jarnecic, E.: Public information arrival and volatility of intraday stock returns. J. Bank. Finance 28, 1441–1467 (2004)

    Article  Google Scholar 

  • Kauppi, H., Saikkonen, P.: Predicting US recessions with dynamic binary response models. Rev. Econ. Stat. 90, 777–791 (2008)

    Article  Google Scholar 

  • Kazi, M.: Systematic risk factors for Australian stock market returns: a cointegration analysis. Aust. Account. Bus. Finance J. 2, 89–101 (2008)

    Google Scholar 

  • Knight, F.H.: Risk, uncertainty, and profit. Hart, Schaffner and Marx, Houghton Mifflin Co, Boston (1921)

    Google Scholar 

  • Kuan, C.M., Liu, T.: Forecasting exchange rates using feed-forward and recurrent neural networks. J. Appl. Econ. 10, 347–364 (1995)

    Article  Google Scholar 

  • Kulendran, N., Wong, K.: Determinants versus composite leading indicators in predicting turning points in growth cycle. J. Travel Res. 50, 415–430 (2011)

    Article  Google Scholar 

  • Larsen, G.A., Wozniak, G.: Market timing can work in the real world. J. Portfolio Manag. 21, 74–81 (1995)

    Article  Google Scholar 

  • Lee, S.B., Kim, K.: Does the October 1987 crash strengthen the co-movements among national stock markets? Rev. Financ. Econ. 3, 89–102 (1993)

    Article  Google Scholar 

  • Leitch, G.J., Tanner, J.: Economic forecast evaluation: profit versus the conventional error measures. Am. Econ. Rev. 81, 580–590 (1991)

    Google Scholar 

  • Leung, M., Daouk, H., Chen, A.-S.: Forecasting stock indices: a comparison of classification and level estimation models. Int. J. Forecast. 16, 173–190 (2000)

    Article  Google Scholar 

  • Lo, A.W., MacKinlay, A.G.: Stock market prices do not follow random walks: evidence from a simple specification test. Rev. Financ. Stud. 1, 41–66 (1988)

    Article  Google Scholar 

  • Maddala, G.S.: Introduction to Econometrics. Wiley, Chichester (2001)

    Google Scholar 

  • Mian, G.M., Adam, C.M.: Volatility dynamics in high frequency financial data: an empirical investigation of the Australian equity returns. Appl. Financ. Econ. 11, 341–352 (2001)

    Article  Google Scholar 

  • Mukherjee, T.K., Naka, A.: Dynamic relations between macroeconomic variables and the Japanese stock market: an application of a vector error correction model. J. Financ. Res. 18, 223–237 (1995)

    Article  Google Scholar 

  • Nyberg, H.: Forecasting the direction of the US stock market with dynamic binary probit models. Int. J. Forecast. 27, 561–578 (2011)

    Article  Google Scholar 

  • Nyberg, H., Ponka, H.: International sign predictability of stock returns: the role of the United States. Econ. Model. 58, 323–338 (2016)

    Article  Google Scholar 

  • Peirson, G., Brown, R., Easton, S., Howard, P., Pinder, S.: Business Finance, 12th edn. McGraw-Hill, New York City (2015)

    Google Scholar 

  • Pesaran, M.H., Timmerman, A.: Predictability of stock return: robustness and economic significance. J. Finance 50, 1201–1228 (1995)

    Article  Google Scholar 

  • Pesaran, M.H., Timmerman, A.: Recursive modelling approach to predicting UK stock returns. Econ. J. 110, 159–191 (2000)

    Article  Google Scholar 

  • Pindyck, S.R., Rubinfeld, L.: Econometric Models and Economic Forecasts. McGraw-Hill, New York City (1998)

    Google Scholar 

  • Phylaktis, K.: Capital markets integration in the pacific-based region: an analysis of real interest rate linkage. Pac. Basin Finance J. 5, 195–213 (1997)

    Article  Google Scholar 

  • Ponka, H.: Real oil prices and the international sign predictability of stock returns. Finance Res. Lett. 17, 79–87 (2016)

    Article  Google Scholar 

  • Ragunathan, V., Faff, R., Brooks, R.D.: Correlations, business cycles and integration. J. Int. Financ. Mark. Inst. Money 9, 75–95 (1999)

    Article  Google Scholar 

  • Rapach, D.E., Strauss, J.K., Zhou, G.: International stock return predictability: what is the role of the United States? J. Finance 68, 1633–1662 (2013)

    Article  Google Scholar 

  • Rydberg, T.H., Shephard, N.: Dynamics of trade-by-trade price movements: decomposition and models. J. Financ. Econ. 1, 2–25 (2003)

    Google Scholar 

  • Shamsuddin, F.M.: Interest rate and exchange rate risk exposure of Australian banks: a note. Int. J. Bank. Finance 6, 128–138 (2009)

    Google Scholar 

  • Taylor, N.: A note on the importance of overnight information in risk management models. J. Bank. Finance 31, 161–180 (2007)

    Article  Google Scholar 

  • Theodossiou, P., Lee, U.: Mean and volatility spillovers across major national stock markets: further empirical evidence. J. Financ. Res. 16, 337–350 (1993)

    Article  Google Scholar 

  • Todorova, T., Soucek, M.: Overnight information flow and realized volatility forecasting. Finance Res. Lett. 11, 1–9 (2014)

    Article  Google Scholar 

  • Tsiakas, I.: Overnight information and stochastic volatility: a study of European and US stock exchanges. J. Bank. Finance 32, 251–268 (2008)

    Article  Google Scholar 

  • Wagner, J., Shellacs, S., Paul, R.: Market timing works where it matters most: in real the world. J. Portf. Manag. 18, 86–90 (1992)

    Article  Google Scholar 

  • White, H.: A reality check for data snooping. Econometrica 68, 1097–1126 (2000)

    Article  Google Scholar 

  • Womack, K.L.: Do brokerage analysts’ recommendations have investment value? J. Finance 51, 137–167 (1996)

    Article  Google Scholar 

Download references

Acknowledgements

We would like to thank the editor Markus Schmid and the anonymous referees for their constructive recommendations, which helped to improve the quality of this paper. In addition, we would like to thank the feedback received during prior drafts from colleagues Dr. Guneratne Wickremasinghe and Dr. Ranjtih Ihalanayake.

Author information

Authors and Affiliations

  1. Victoria University Business School, Victoria University, PO Box 14428, Melbourne, VIC, 8001, Australia

    Riza Erdugan, Nada Kulendran & Riccardo Natoli

Authors
  1. Riza Erdugan
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Nada Kulendran
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Riccardo Natoli
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Riccardo Natoli.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Erdugan, R., Kulendran, N. & Natoli, R. Incorporating financial market volatility to improve forecasts of directional changes in Australian share market returns. Financ Mark Portf Manag 33, 417–445 (2019). https://doi.org/10.1007/s11408-019-00338-z

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11408-019-00338-z

Keywords

JEL Classification

Search

Navigation