The serial correlations of illiquid stock's price changes are studied, allowing for unconditional heteroscedasticity and time-varying zero returns probability. Depending on the set up, we investigate how the usual autocorrelations can be accommodated, to deliver an accurate representation of the price changes serial correlations. We shed some light on the properties of the different serial correlations measures, by mean of Monte Carlo experiments. The theoretical arguments are illustrated considering shares from the Chilean stock market.
翻译:研究股票价格变化的序列相关性,允许条件异方差和时变的零回报概率。根据设定,我们研究如何容纳通常的自相关性,以提供对价格变化序列相关性的准确表示。通过蒙特卡罗实验,我们阐明了不同序列相关性测量的特性。理论论证以智利股市股票为例进行了说明。