Arbeitspapier
The Variance Ratio Statistic at Large Horizons
We make three contributions to using the variance ratio statistic at large horizons. Allowing for general heteroscedasticity in the data, we obtain the asymptotic distribution of the statistic when the horizon k is increasing with the sample size n but at a slower rate so that k=n ! 0. The test is shown to be consistent against a variety of relevant mean reverting alternatives when k=n ! 0. This is in contrast to the case when k=n ! – > 0; where the statistic has been recently shown to be inconsistent against such alternatives. Secondly, we provide and justify a simple power transformation of the statistic which yields almost perfectly normally distributed statistics in finite samples, solving the well known right skewness problem. Thirdly, we provide a more powerful way of pooling information from different horizons to test for mean reverting alternatives. Monte Carlo simulations illustrate the theoretical improvements provided.
- Sprache
-
Englisch
- Erschienen in
-
Series: Papers ; No. 2004,04
- Klassifikation
-
Wirtschaft
Hypothesis Testing: General
Single Equation Models; Single Variables: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
- Thema
-
Mean reversion
Frequency domain
Power transformation
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Deo, Rohit S.
Chen, Willa W.
- Ereignis
-
Veröffentlichung
- (wer)
-
Humboldt-Universität zu Berlin, Center for Applied Statistics and Economics (CASE)
- (wo)
-
Berlin
- (wann)
-
2003
- Handle
- Letzte Aktualisierung
-
10.03.2025, 11:44 MEZ
Datenpartner
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Arbeitspapier
Beteiligte
- Deo, Rohit S.
- Chen, Willa W.
- Humboldt-Universität zu Berlin, Center for Applied Statistics and Economics (CASE)
Entstanden
- 2003
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