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Temporal aggregation of univariate and multivariate time series models: A survey

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  • SILVESTRINI, Andrea
  • VEREDAS, David

Abstract

We present a unified and up-to-date overview of temporal aggregation techniques for univariate and multivariate time series models explaining in detail how these techniques are employed. Some empirical applications illustrate the main issues.

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File URL: http://dx.doi.org/10.1111/j.1467-6419.2007.00538.x
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Paper provided by Université catholique de Louvain, Center for Operations Research and Econometrics (CORE) in its series CORE Discussion Papers RP with number -2013.

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Handle: RePEc:cor:louvrp:-2013

Note: In : Journal of Economic Surveys, 22(3), 458-497, 2008
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Cited by:
  1. Andres Elberg, 2014. "Temporal Aggregation and Convergence to the Law of One Price: Evidence from Micro Data," Working Papers 53, Facultad de Economía y Empresa, Universidad Diego Portales.
  2. Kourentzes, Nikolaos & Petropoulos, Fotios & Trapero, Juan R., 2014. "Improving forecasting by estimating time series structural components across multiple frequencies," International Journal of Forecasting, Elsevier, vol. 30(2), pages 291-302.
  3. Hui Jun Zhang & Jean-Marie Dufour & John Galbraith, 2013. "Exchange rates and commodity prices: measuring causality at multiple horizons," CIRANO Working Papers 2013s-39, CIRANO.
  4. Götz Thomas & Hecq Alain & Urbain Jean-Pierre, 2012. "Forecasting Mixed Frequency Time Series with ECM-MIDAS Models," Research Memorandum 012, Maastricht University, Maastricht Research School of Economics of Technology and Organization (METEOR).
  5. Helmut Luetkepohl, 2009. "Forecasting Aggregated Time Series Variables: A Survey," Economics Working Papers ECO2009/17, European University Institute.
  6. Sacht, Stephen, 2014. "Analysis of various shocks within the high-frequency versions of the baseline New-Keynesian model," Economics Working Papers 2014-02, Christian-Albrechts-University of Kiel, Department of Economics.
  7. Sbrana, Giacomo & Silvestrini, Andrea, 2013. "Aggregation of exponential smoothing processes with an application to portfolio risk evaluation," Journal of Banking & Finance, Elsevier, vol. 37(5), pages 1437-1450.
  8. Uwe Hassler, 2011. "Estimation of fractional integration under temporal aggregation," Post-Print hal-00815563, HAL.
  9. Giacomo Sbrana & Andrea Silvestrini, 2012. "Temporal aggregation of cyclical models with business cycle applications," Statistical Methods and Applications, Springer, vol. 21(1), pages 93-107, March.
  10. Ramirez, Octavio A., 2011. "Conclusive Evidence on the Benefits of Temporal Disaggregation to Improve the Precision of Time Series Model Forecasts," Faculty Series 113520, University of Georgia, Department of Agricultural and Applied Economics.
  11. Yamin Ahmad & Ivan Paya, 2014. "Temporal Aggregation of Random Walk Processes and Implications for Asset Prices," Working Papers 14-01, UW-Whitewater, Department of Economics.
  12. Qian, Hang, 2013. "Vector Autoregression with Mixed Frequency Data," MPRA Paper 47856, University Library of Munich, Germany.
  13. Ramirez, Octavio A., 2012. "Conclusive Evidence on the Benefits of Temporal Disaggregation to Improve the Precision of Time Series Model Forecasts," 2012 Annual Meeting, August 12-14, 2012, Seattle, Washington 123470, Agricultural and Applied Economics Association.
  14. Steven Clark & T. Coggin, 2011. "Are U.S. stock prices mean reverting? Some new tests using fractional integration models with overlapping data and structural breaks," Empirical Economics, Springer, vol. 40(2), pages 373-391, April.

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