Mean Reversion Lessens Mean Blur: Evidence from the S&P Composite Index
Luigi Buzzacchi (luigi.buzzacchi@polito.it) and
Luca Ghezzi
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Luigi Buzzacchi: Interuniversity Department of Regional and Urban Studies and Planning & FULL, Politecnico di Torino, Viale Mattioli 39, 10125 Torino, Italy
Luca Ghezzi: Department of Integrated Business Management, Università Carlo Cattaneo, Corso Matteotti 22, 21053 Castellanza, Italy
IJFS, 2023, vol. 11, issue 1, 1-13
Abstract:
This study makes use of a very long time series of the S&P Composite Index, checking once more that the rates of return benefit from aggregational normality. It performs unit root tests as well as elementary statistical tests that take advantage of normality. It finds that mean blur is not consistent with the hypothesis of random walk with constant parameters, because the means of the annual real rates of linear return can be estimated as usual. It gives further evidence that the rates of return on the S&P Composite Index are mean-reverting.
Keywords: stock index; mean reversion; mean blur (search for similar items in EconPapers)
JEL-codes: F2 F3 F41 F42 G1 G2 G3 (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (1)
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Persistent link: https://EconPapers.repec.org/RePEc:gam:jijfss:v:11:y:2023:i:1:p:22-:d:1045692
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