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Preventing Negative Values When Forecasting Non-Negative Time Series Variables

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Listed:
  • Ali TFAILY

    (The Bucharest University of Economic Studies, Bucharest, Romania)

Abstract

Long run time series variables forecasting is of special importance to academics and professionals alike. In this paper, the disadvantage of the Natural Logarithm transformation that prevents generating negative values in the forecast horizon is discussed. An alternative technique that does not suffer from the disadvantage of the Natural Logarithm transformation is presented. Both methods have been applied for forecasting the average USD deposits rate offered in the Lebanese retail banking industry.

Suggested Citation

  • Ali TFAILY, 2018. "Preventing Negative Values When Forecasting Non-Negative Time Series Variables," Business Excellence and Management, Faculty of Management, Academy of Economic Studies, Bucharest, Romania, vol. 8(2), pages 53-65, June.
    • Handle: RePEc:rom:bemann:v:8:y:2018:i:2:p:53-65
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    File URL: https://beman.ase.ro/no82/4.pdf
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    References listed on IDEAS

    as
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    3. Engle, Robert F & Ng, Victor K, 1993. "Measuring and Testing the Impact of News on Volatility," Journal of Finance, American Finance Association, vol. 48(5), pages 1749-1778, December.
    Full references (including those not matched with items on IDEAS)

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