Robust time series models with trend and seasonal components
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DOI: 10.1007/s13209-015-0134-1
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References listed on IDEAS
- Harvey,Andrew C., 2013.
"Dynamic Models for Volatility and Heavy Tails,"
Cambridge Books,
Cambridge University Press, number 9781107630024.
- Harvey,Andrew C., 2013. "Dynamic Models for Volatility and Heavy Tails," Cambridge Books, Cambridge University Press, number 9781107034723, November.
- Andrew Harvey & Alessandra Luati, 2014.
"Filtering With Heavy Tails,"
Journal of the American Statistical Association, Taylor & Francis Journals, vol. 109(507), pages 1112-1122, September.
- Harvey, A. & Luati, A., 2012. "Filtering with heavy tails," Cambridge Working Papers in Economics 1255, Faculty of Economics, University of Cambridge.
- ., 2014. "Evaluating the policy options," Chapters, in: Confronting the Shadow Economy, chapter 4, pages iii-iii, Edward Elgar Publishing.
- McDonald, James B. & Newey, Whitney K., 1988. "Partially Adaptive Estimation of Regression Models via the Generalized T Distribution," Econometric Theory, Cambridge University Press, vol. 4(3), pages 428-457, December.
- Durbin, James & Koopman, Siem Jan, 2012.
"Time Series Analysis by State Space Methods,"
OUP Catalogue,
Oxford University Press,
edition 2, number 9780199641178.
- Durbin, James & Koopman, Siem Jan, 2001. "Time Series Analysis by State Space Methods," OUP Catalogue, Oxford University Press, number 9780198523543.
- ., 2014. "Introduction to health care evaluation," Chapters, in: Cost–Benefit Analysis and Health Care Evaluations, Second Edition, chapter 1, pages 3-28, Edward Elgar Publishing.
- Michele Caivano & Andrew Harvey, 2014.
"Time-series models with an EGB2 conditional distribution,"
Journal of Time Series Analysis, Wiley Blackwell, vol. 35(6), pages 558-571, November.
- M. Caivano & A. Harvey, 2013. "Time series models with an EGB2 conditional distribution," Cambridge Working Papers in Economics 1325, Faculty of Economics, University of Cambridge.
- Michele Caivano & Andrew Harvey, 2014. "Time series models with an EGB2 conditional distribution," Temi di discussione (Economic working papers) 947, Bank of Italy, Economic Research and International Relations Area.
- Maravall, Agustin, 1985. "On Structural Time Series Models and the Characterization of Components," Journal of Business & Economic Statistics, American Statistical Association, vol. 3(4), pages 350-355, October.
- Zhu, Dongming & Galbraith, John W., 2011. "Modeling and forecasting expected shortfall with the generalized asymmetric Student-t and asymmetric exponential power distributions," Journal of Empirical Finance, Elsevier, vol. 18(4), pages 765-778, September.
Citations
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Cited by:
- Astrid Ayala & Szabolcs Blazsek, 2019. "Score-driven currency exchange rate seasonality as applied to the Guatemalan Quetzal/US Dollar," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 10(1), pages 65-92, March.
- Astrid Ayala & Szabolcs Blazsek & Adrian Licht, 2022. "Score-driven stochastic seasonality of the Russian rouble: an application case study for the period of 1999 to 2020," Empirical Economics, Springer, vol. 62(5), pages 2179-2203, May.
- Escribano, Álvaro & Licht, Adrian & Blazsek, Szabolcs, 2018. "Seasonal quasi-vector autoregressive models for macroeconomic data," UC3M Working papers. Economics 26316, Universidad Carlos III de Madrid. Departamento de EconomÃa.
- Blasques, Francisco & van Brummelen, Janneke & Gorgi, Paolo & Koopman, Siem Jan, 2024. "Maximum Likelihood Estimation for Non-Stationary Location Models with Mixture of Normal Distributions," Journal of Econometrics, Elsevier, vol. 238(1).
- Blasques, Francisco & Nientker, Marc, 2023. "Stochastic properties of nonlinear locally-nonstationary filters," Journal of Econometrics, Elsevier, vol. 235(2), pages 2082-2095.
- Szabolcs Blazsek & Hector Hernández, 2018. "Analysis of electricity prices for Central American countries using dynamic conditional score models," Empirical Economics, Springer, vol. 55(4), pages 1807-1848, December.
- Blazsek, Szabolcs & Escribano, Álvaro & Licht, Adrian, 2019. "Markov-switching score-driven multivariate models: outlier-robust measurement of the relationships between world crude oil production and US industrial production," UC3M Working papers. Economics 29030, Universidad Carlos III de Madrid. Departamento de EconomÃa.
- Sarlo, Rodrigo & Fernandes, Cristiano & Borenstein, Denis, 2023. "Lumpy and intermittent retail demand forecasts with score-driven models," European Journal of Operational Research, Elsevier, vol. 307(3), pages 1146-1160.
- Escribano, Álvaro & Licht, Adrian & Blazsek, Szabolcs, 2018. "Seasonal Quasi-Vector Autoregressive Models with an Application to Crude Oil Production and Economic Activity in the United States and Canada," UC3M Working papers. Economics 27484, Universidad Carlos III de Madrid. Departamento de EconomÃa.
- Sergio Contreras-Espinoza & Francisco Novoa-Muñoz & Szabolcs Blazsek & Pedro Vidal & Christian Caamaño-Carrillo, 2022. "COVID-19 Active Case Forecasts in Latin American Countries Using Score-Driven Models," Mathematics, MDPI, vol. 11(1), pages 1-17, December.
- Enzo D’Innocenzo & Alessandra Luati & Mario Mazzocchi, 2023.
"A robust score-driven filter for multivariate time series,"
Econometric Reviews, Taylor & Francis Journals, vol. 42(5), pages 441-470, May.
- Enzo D'Innocenzo & Alessandra Luati & Mario Mazzocchi, 2020. "A Robust Score-Driven Filter for Multivariate Time Series," Papers 2009.01517, arXiv.org, revised Aug 2022.
- Martin Weale & Paul Labonne, 2022. "Nowcasting in the presence of large measurement errors and revisions," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2022-05, Economic Statistics Centre of Excellence (ESCoE).
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More about this item
Keywords
Fat tails; EGB2; Score; Robustness; Student’s t; Trimming; Winsorizing;All these keywords.
JEL classification:
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
- G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
Statistics
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