What happens when the stock markets are closed

IF 0.6 Q4 STATISTICS & PROBABILITY
A. Mulenga, M. Faias, P. Mota, J. Pina
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引用次数: 0

Abstract

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. 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.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. 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.
当股票市场关闭时会发生什么
股票价格对数回报的正态性通常由市场参与者假设,以便使用一些有用的结果,例如,欧洲期权定价的Black-Scholes公式。然而,关于不同指数的几项研究表明,收益率的正态性假设通常是失败的。在本文中,我们分析了日内和日间日志回报的正态性假设,比较了纳斯达克综合指数中大量公司的开盘价和/或收盘价。我们使用Pearson’s Chi Square、Kolmogorov Smirnov、Anderson Darling、Shapiro Wilks和Jarque Bera拟合优度检验来研究正态性假设。我们发现,对于日内和日间价格,股票价格对数回报的正态性假设中的失败率并不相同,在一定程度上取决于测试,并且强烈依赖于一些极端价格观察。据我们所知,这是首次对股票价格对数回归的正态性假设进行研究,同时处理大量公司和正态性测试,同时考虑日内、日间价格和数据修剪的各种场景。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
1.40
自引率
14.30%
发文量
0
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