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Impacts of interval measurement on studies of economic variability: Evidence from stock market variability forecasting

  • Ling T. He
  • Chenyi Hu
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    Purpose – The purpose of this study is to investigate the impacts of interval measured data, rather than traditional point data, on economic variability studies. Design/methodology/approach – The study uses interval measured data to forecast the variability of future stock market changes. The variability (interval) forecasts are then compared with point data-based confidence interval forecasts. Findings – Using interval measured data in stock market variability forecasting can significantly increase forecasting accuracy, compared with using traditional point data. Originality/value – An interval forecast for stock prices essentially consists of predicted levels and a predicted variability which can reduce perceived uncertainty or risk embedded in future investments, and therefore, may influence required returns and capital asset prices.

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    Article provided by Emerald Group Publishing in its journal Journal of Risk Finance.

    Volume (Year): 8 (2007)
    Issue (Month): 5 (November)
    Pages: 489-507

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    Handle: RePEc:eme:jrfpps:v:8:y:2007:i:5:p:489-507
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