Arbeitspapier
Additive nonparametric models with time variable and both stationary and nonstationary regressions
This paper considers nonparametric additive models that have a deterministic time trend and both stationary and integrated variables as components. The diverse nature of the regressors caters for applications in a variety of settings. In addition, we extend the analysis to allow the stationary regressor to be instead locally stationary, and we allow the models to include a linear form of the integrated variable. Heteroscedasticity is allowed for in all models. We propose an estimation strategy based on orthogonal series expansion that takes account of the different type of stationarity/nonstationarity possessed by each covariate. We establish pointwise asymptotic distribution theory jointly for all estimators of unknown functions and also show the conventional optimal convergence rates jointly in the L2 sense. In spite of the entanglement of different kinds of regressors, we can separate out the distribution theory for each estimator. We provide Monte Carlo simulations that establish the favourable properties of our procedures in moderate sized samples. Finally, we apply our techniques to the study of a pairs trading strategy.
- Sprache
-
Englisch
- Erschienen in
-
Series: cemmap working paper ; No. CWP59/17
- Klassifikation
-
Wirtschaft
Estimation: General
Information and Market Efficiency; Event Studies; Insider Trading
Single Equation Models; Single Variables: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
- Thema
-
Additive nonparametric models
deterministic trend
pairs trading
seriesestimator
stationary and locally stationary processes
unit root process
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Dong, Chaohua
Linton, Oliver
- Ereignis
-
Veröffentlichung
- (wer)
-
Centre for Microdata Methods and Practice (cemmap)
- (wo)
-
London
- (wann)
-
2017
- DOI
-
doi:10.1920/wp.cem.2017.5917
- Handle
- Letzte Aktualisierung
-
10.03.2025, 11:41 MEZ
Datenpartner
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Arbeitspapier
Beteiligte
- Dong, Chaohua
- Linton, Oliver
- Centre for Microdata Methods and Practice (cemmap)
Entstanden
- 2017
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