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Forecast Comparison in L2

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Author Info

  • Bruce Mizrach

    ()
    (Rutgers University)

Abstract

This paper provides a comprehensive framework for comparing predictors of univariate time series in the mean square norm. Initially, the forecast errors are assumed to be unbiased, independent, and normally distributed. Each of these is progressively relaxed. A new heteroscedasticity and autocorrelation consistent statistic for forecast comparison is derived. Finite sample distributions are tabulated in a sequence of Monte Carlo exercises. Power is examined by comparing forecast errors from a moving average model with misspecified autoregressive alternatives.

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File URL: ftp://snde.rutgers.edu/Rutgers/wp/1995-24.pdf
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Bibliographic Info

Paper provided by Rutgers University, Department of Economics in its series Departmental Working Papers with number 199524.

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Date of creation: 01 Aug 1996
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Handle: RePEc:rut:rutres:199524

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Related research

Keywords: Mean squared prediction error; robust forecast comparison;

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References

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  1. Meese, R. & Rogoff, K., 1988. "Was It Real? The Exchange Rate-Interest Differential Ralation Over The Modern Floating-Rate Period," Working papers 368, Wisconsin Madison - Social Systems.
  2. Clements, M.P. & Hendry, D., 1992. "On the Limitations of Comparing Mean Square Forecast Errors," Economics Series Working Papers 99138, University of Oxford, Department of Economics.
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Citations

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Cited by:
  1. Swanson, Norman R. & White, Halbert, 1997. "Forecasting economic time series using flexible versus fixed specification and linear versus nonlinear econometric models," International Journal of Forecasting, Elsevier, vol. 13(4), pages 439-461, December.
  2. Randall E. Parker & Philip Rothman, . "The Current Depth of Recession and Unemployment Rate Forecasts," Working Papers 9729, East Carolina University, Department of Economics.
  3. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-44, January.
  4. Alfonso Dufour & Robert F Engle, 2000. "The ACD Model: Predictability of the Time Between Concecutive Trades," ICMA Centre Discussion Papers in Finance icma-dp2000-05, Henley Business School, Reading University.
  5. Chan, Tze-Haw & Lye, Chun Teck & Hooy, Chee-Wooi, 2010. "Forecasting Malaysian Exchange Rate: Do Artificial Neural Networks Work?," MPRA Paper 26326, University Library of Munich, Germany.
  6. Norman R. Swanson & Halbert White, 1995. "A Model Selection Approach to Real-Time Macroeconomic Forecasting Using Linear Models and Artificial Neural Networks," Macroeconomics 9503004, EconWPA.
  7. Ahmad Baharumshah & Venus Liew, 2006. "Forecasting Performance of Exponential Smooth Transition Autoregressive Exchange Rate Models," Open Economies Review, Springer, vol. 17(2), pages 235-251, April.
  8. Lisi, Francesco & Medio, Alfredo, 1997. "Is a random walk the best exchange rate predictor?," International Journal of Forecasting, Elsevier, vol. 13(2), pages 255-267, June.

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