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

Author

Listed:
  • Riza Erdugan

    (Victoria University)

  • Nada Kulendran

    (Victoria University)

  • Riccardo Natoli

    (Victoria University)

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.

Suggested Citation

  • Riza Erdugan & Nada Kulendran & Riccardo Natoli, 2019. "Incorporating financial market volatility to improve forecasts of directional changes in Australian share market returns," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 33(4), pages 417-445, December.
    • Handle: RePEc:kap:fmktpm:v:33:y:2019:i:4:d:10.1007_s11408-019-00338-z
    DOI: 10.1007/s11408-019-00338-z
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    More about this item

    Keywords

    Binary regression model; Volatility estimates; Marginal probability; Forecast comparison;
    All these keywords.

    JEL classification:

    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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