Observation-Driven filters for Time- Series with Stochastic Trends and Mixed Causal Non-Causal Dynamics

Francisco Blasques, Siem Jan Koopman and Gabriele Mingoli
Additional contact information
Francisco Blasques: Vrije Universiteit Amsterdam
Gabriele Mingoli: Vrije Universiteit Amsterdam

No 23-065/III, Tinbergen Institute Discussion Papers from Tinbergen Institute

Abstract: This paper proposes a novel time-series model with a non-stationary stochas- tic trend, locally explosive mixed causal non-causal dynamics and fat-tailed innovations. The model allows for a description of financial time-series that is consistent with financial theory, for a decomposition of the time-series in trend and bubble components, and for meaningful real-time forecasts during bubble episodes. We provide sufficient conditions for strong consistency and asymptotic normality of the maximum likelihood estimator. The model-based filter for extracting the trend and bubbles is shown to be invertible and the extracted components converge to the true trend and bubble paths. A Monte Carlo simulation study confirms the good finite sample properties. Finally, we consider an empirical study of Nickel monthly price series and global mean sea level data. We document the forecasting accuracy against competitive alternative methods and conclude that our model-based forecasts outperform all these alternatives.

Keywords: observation-driven filter; non-stationary time-series; mixed causal non- causal models (search for similar items in EconPapers)
JEL-codes: C22 C51 C53 (search for similar items in EconPapers)
Date: 2023-10-22, Revised 2024-03-01
New Economics Papers: this item is included in nep-ecm and nep-ets
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://papers.tinbergen.nl/23065.pdf (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:tin:wpaper:20230065

Access Statistics for this paper

More papers in Tinbergen Institute Discussion Papers from Tinbergen Institute Contact information at EDIRC.
Bibliographic data for series maintained by Tinbergen Office +31 (0)10-4088900 ().