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This paper derives a statistical test, based on the first-order autocorrelation, to ascertain whether a stochastic process evolving within reflecting barriers is mean reverting. Under these conditions the standard unit root analysis does not apply. Since the presence of reflecting barriers per se will induce mean reverting behaviour, the detection of mean reversion inside the two boundaries requires that the effect of reflection be properly accounted for. This statistical procedure may be useful in a number of economic applications which involve an assesment on the dynamics of bounded variables: e.g. the estimation of the mean reversion of ratios in capital structure theory, market share analysis, or the empirical testing of target zones models for exchange rates. We exemplify the inappropriateness of standard unit root analysis in these situations using European Monetary System exchange rate data. Our methodology is helpful in deciding whether the mean reverting behaviour of these exchange rates is due solely to local behaviour at the barriers, or whether a more complex interpretation is warranted. We apply our test to the target zone model introduced by Krugman where the intervention bands are credible. We study bilateral exchange rates of currencies party to the European Monetary System during a period of sustained stability consistent with the credible band assumption. Our results are consistent with those obtained employing significantly more complex maximum likelihood procedures.C51;F33,

This paper investigates the performance of size-and value-based strategies in the Italian Stock Market in the period 2000 -2018. Previous research (Beltratti and Di Tria (2002) argued the impossibility to define properly value sorted portfolios due to the inaccuracy of book-to-market ratios available for Italian listed stocks. The Datastream database, which was commonly used by previous authors, contains errors which may undermine the result of the analysis. Using accurate data provided by Borsa Italiana and Mediobanca, we implement portfolios sorting based on value and growth stocks, in order to asses the relevance of the value factor in the Italian Stock Market. We find that the CAPM fails to explain the cross section of returns on the different strategies while the Fama and French (1993) three-factor model provides a better fit. The results show that all three factors are significant in explaining Italian stock returns during the sample period. Unlike previous studies, which either found no value effect at all (Barontini (1997);Aleati et al., (2000)) or no clear cut results when testing the bookto-market variable (Bruni et al. (2006); Rossi ( 2012)), we find that the value factor is statistically significant and the associated risk premium is of a considerable size.