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Predicting Japanese bank stock performance with a composite relative efficiency metric: A new investment tool

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  • Avkiran, Necmi K.
  • Morita, Hiroshi
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    Abstract

    The paper's main objective is to predict bank stock performance one year ahead with a composite efficiency metric from relative contextual financial analysis. We bring together financial ratios, generalized data envelopment analysis and simulated annealing to rank Japanese banks on stock performance predicted from relative efficiency scores. An application of this ranking in a profitable investment strategy by designating long and short portfolios underscores the potential commercial value of the method. The method can also be used to monitor the effectiveness of ratios in forecasting stock performance and it is conducive to selecting predictive ratios when markets are changing rapidly.

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    Bibliographic Info

    Article provided by Elsevier in its journal Pacific-Basin Finance Journal.

    Volume (Year): 18 (2010)
    Issue (Month): 3 (June)
    Pages: 254-271

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    Handle: RePEc:eee:pacfin:v:18:y:2010:i:3:p:254-271

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    Web page: http://www.elsevier.com/locate/pacfin

    Related research

    Keywords: Stock performance Contextual analysis Generalized DEA Simulated annealing Japanese banks;

    References

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    1. Per Andersen & Niels Christian Petersen, 1993. "A Procedure for Ranking Efficient Units in Data Envelopment Analysis," Management Science, INFORMS, vol. 39(10), pages 1261-1264, October.
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    14. Beneish, Messod D., 1997. "Detecting GAAP violation: implications for assessing earnings management among firms with extreme financial performance," Journal of Accounting and Public Policy, Elsevier, vol. 16(3), pages 271-309.
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    17. Banker, Rajiv D. & Cooper, William W. & Seiford, Lawrence M. & Thrall, Robert M. & Zhu, Joe, 2004. "Returns to scale in different DEA models," European Journal of Operational Research, Elsevier, vol. 154(2), pages 345-362, April.
    18. R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
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    Cited by:
    1. Avkiran, Necmi K. & Goto, Mika, 2011. "A tool for scrutinizing bank bailouts based on multi-period peer benchmarking," Pacific-Basin Finance Journal, Elsevier, vol. 19(5), pages 447-469, November.
    2. Avkiran, Necmi K., 2011. "Association of DEA super-efficiency estimates with financial ratios: Investigating the case for Chinese banks," Omega, Elsevier, vol. 39(3), pages 323-334, June.
    3. Necmi Avkiran & Alan McCrystal, 2014. "Intertemporal analysis of organizational productivity in residential aged care networks: scenario analyses for setting policy targets," Health Care Management Science, Springer, vol. 17(2), pages 113-125, June.
    4. Chrysovalantis Gaganis & Iftekhar Hasan & Fotios Pasiouras, 2013. "Efficiency and stock returns: evidence from the insurance industry," Journal of Productivity Analysis, Springer, vol. 40(3), pages 429-442, December.

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