Arbeitspapier
Mean Ratio Statistic for measuring predictability
We propose an alternative Ratio Statistic for measuring predictability of stock prices. Our statistic is based on actual returns rather than logarithmic returns and is therefore better suited to capturing price predictability. It captures not only linear dependence in the same way as the variance ratio statistics of Lo and MacKinlay (1988) but also some nonlinear dependencies. We derive the asymptotic distribution of the statistics under the null hypothesis that simple gross returns are unpredictable after a constant mean adjustment. This represents a test of the weak form of the Efficient Market Hypothesis. We also consider the multivariate extension, in particular, we derive the restrictions implied by the EMH on multiperiod portfolio gross returns. We apply our methodology to test the gross return predictability of various financial series.
- Sprache
-
Englisch
- Erschienen in
-
Series: cemmap working paper ; No. CWP08/15
- Klassifikation
-
Wirtschaft
Econometric and Statistical Methods and Methodology: General
Single Equation Models; Single Variables: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
General Financial Markets: General (includes Measurement and Data)
Information and Market Efficiency; Event Studies; Insider Trading
- Thema
-
Variance Ratio Tests
Martingale
Predictability
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Linton, Oliver
Smetanina, Katja
- Ereignis
-
Veröffentlichung
- (wer)
-
Centre for Microdata Methods and Practice (cemmap)
- (wo)
-
London
- (wann)
-
2015
- DOI
-
doi:10.1920/wp.cem.2015.0815
- Handle
- Letzte Aktualisierung
-
10.03.2025, 11:42 MEZ
Datenpartner
Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Arbeitspapier
Beteiligte
- Linton, Oliver
- Smetanina, Katja
- Centre for Microdata Methods and Practice (cemmap)
Entstanden
- 2015
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