Impacts of Interval Computing on Stock Market Variability Forecasting
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DOI: 10.1007/s10614-008-9159-x
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References listed on IDEAS
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Cited by:
- Henning Fischer & Ángela Blanco‐FERNÁndez & Peter Winker, 2016. "Predicting Stock Return Volatility: Can We Benefit from Regression Models for Return Intervals?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 35(2), pages 113-146, March.
- Javier Arroyo & Rosa Espínola & Carlos Maté, 2011. "Different Approaches to Forecast Interval Time Series: A Comparison in Finance," Computational Economics, Springer;Society for Computational Economics, vol. 37(2), pages 169-191, February.
- Černý, Michal & Hladík, Milan, 2014. "The complexity of computation and approximation of the t-ratio over one-dimensional interval data," Computational Statistics & Data Analysis, Elsevier, vol. 80(C), pages 26-43.
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More about this item
Keywords
Interval forecast; Interval computing; The OLS lower and upper bound forecasting; Accuracy ratio; C53; C82;All these keywords.
JEL classification:
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
- C82 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Macroeconomic Data; Data Access
Statistics
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