<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Mulenga, A.</style></author><author><style face="normal" font="default" size="100%">Faias, M.</style></author><author><style face="normal" font="default" size="100%">Mota, P.</style></author><author><style face="normal" font="default" size="100%">Pina, J.P.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">What happens when the stock markets are closed?</style></title><secondary-title><style face="normal" font="default" size="100%">Electronic Journal of Applied Statistical Analysis</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2019</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://siba-ese.unisalento.it/index.php/ejasa/article/view/19750</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">12</style></volume><pages><style face="normal" font="default" size="100%">405-415</style></pages><abstract><style face="normal" font="default" size="100%">&lt;p&gt;The normality of the log-return of stock prices is often assumed by the market players in order to use some useful results, as for instance, the Black-Scholes formula for pricing European options. However, several studies regarding different indexes have shown that the normality assumption of the returns usually fails.&lt;br /&gt;
In this paper we analyse the normality assumption for intra-day and inter-day log-returns, comparing opening prices and/or closing prices for a large number of companies quoted in the Nasdaq Composite index. We use the Pearson's Chi-Square, Kolmogorov-Smirnov, Anderson-Darling, Shapiro-Wilks and Jarque-Bera goodness-of-fit tests to study the normality assumption.&lt;br /&gt;
We find that the failure rate in the normality assumption for the log-return of stock prices is not the same for intra-day and inter-day prices, is somewhat test dependent and strongly dependent on some extreme price observations.&lt;br /&gt;
To the best of our knowledge, this is the first study on the normality assumption for the log-return of stock prices dealing simultaneously with a large number of companies and normality tests, and at the same time considering various scenarios of intra-day, inter-day prices and data trimming.&lt;/p&gt;
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