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Run length and the predictability of stock price reversals

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  • Juan Yao
  • Graham Partington
  • Max Stevenson

Abstract

Survival analysis is used to estimate time‐varying probabilities of price reversals using daily data for the Australian All Ordinaries Price Index. Lagged price changes lead to persistence (shortening) in a price run if they are of the same (opposite) sign as the run. An increase in the number of runs observed in the previous 30 days also increases the probability of price reversal. The predictive accuracy of the models is assessed using a probability scoring rule. Consistent with market efficiency, the estimated models are less accurate than the random walk model in predicting the length of individual price runs out‐of‐sample.

Suggested Citation

  • Juan Yao & Graham Partington & Max Stevenson, 2005. "Run length and the predictability of stock price reversals," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 45(4), pages 653-671, December.
    • Handle: RePEc:bla:acctfi:v:45:y:2005:i:4:p:653-671
    DOI: 10.1111/j.1467-629X.2005.00156.x
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    References listed on IDEAS

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    1. Juan Yao & Graham Partington & Max Stevenson, 2013. "Predicting the directional change in consumer sentiment," Australian Journal of Management, Australian School of Business, vol. 38(1), pages 67-80, April.
    2. Huong Dang & Graham Partington, 2014. "Rating Migrations: The Effect of History and Time," Abacus, Accounting Foundation, University of Sydney, vol. 50(2), pages 174-202, June.
    3. Huong Dang, 2014. "A Competing Risks Dynamic Hazard Approach to Investigate the Insolvency Outcomes of Property-Casualty Insurers," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 39(1), pages 42-76, January.

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