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：研究了非流动性股票价格变动的序列相关性，允许存在无条件异方差以及随时间变化的零收益概率。根据不同设定，我们探讨了如何调整常规自相关以准确反映价格变动的序列相关性。通过蒙特卡罗实验，我们揭示了不同序列相关性测度的特性。理论论证以智利股票市场的股票为例进行说明。