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Estimation and Forecasting of Locally Stationary Processes

Author

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  • Wilfredo Palma
  • Ricardo Olea
  • Guillermo Ferreira

Abstract

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Suggested Citation

  • Wilfredo Palma & Ricardo Olea & Guillermo Ferreira, 2013. "Estimation and Forecasting of Locally Stationary Processes," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 32(1), pages 86-96, January.
    • Handle: RePEc:wly:jforec:v:32:y:2013:i:1:p:86-96
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    Cited by:

    1. Pourkhanali, Armin & Tafakori, Laleh & Bee, Marco, 2023. "Forecasting Value-at-Risk using functional volatility incorporating an exogenous effect," International Review of Financial Analysis, Elsevier, vol. 89(C).
    2. Ferreira, Guillermo & Rodríguez, Alejandro & Lagos, Bernardo, 2013. "Kalman filter estimation for a regression model with locally stationary errors," Computational Statistics & Data Analysis, Elsevier, vol. 62(C), pages 52-69.
    3. Kley, Tobias & Preuss, Philip & Fryzlewicz, Piotr, 2019. "Predictive, finite-sample model choice for time series under stationarity and non-stationarity," LSE Research Online Documents on Economics 101748, London School of Economics and Political Science, LSE Library.
    4. Guillermo Ferreira & Jorge Mateu & Emilio Porcu, 2018. "Spatio-temporal analysis with short- and long-memory dependence: a state-space approach," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 27(1), pages 221-245, March.
    5. Armin Pourkhanali & Jonathan Keith & Xibin Zhang, 2021. "Conditional Heteroscedasticity Models with Time-Varying Parameters: Estimation and Asymptotics," Monash Econometrics and Business Statistics Working Papers 15/21, Monash University, Department of Econometrics and Business Statistics.
    6. Javier Contreras-Reyes & Wilfredo Palma, 2013. "Statistical analysis of autoregressive fractionally integrated moving average models in R," Computational Statistics, Springer, vol. 28(5), pages 2309-2331, October.

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