We present a new Hawkes-Contact model that combines a Hawkes process and a finite-range contact process to model the stock price movements, especially under the impact of news and other information flows that could lead to contagious effects. To fully capture the underlying price process, we take the Hawkes process to track the full pathway of historical prices on their future movements and the contact process to capture the impact from news/investment sentiment. We compare this full model to a univariate Hawkes process that works as a benchmark model through analyzing their statistical properties using both simulated returns and the real 5-min returns of the crude oil index (Wind CZCE-TA). The statistical properties include probability density function, complementary cumulative distribution function, and Lempel-Ziv Complex. Our results show that the real returns' distribution is often far from normal, but the simulated returns through the Hawkes or Hawke-Contact model can achieve close fit to the real returns and exhibit similar statistical properties. More importantly, the Hawkes-Contact model performs better than the simple Hawkes model in capturing characteristics in the return movements, which indicates that the price evolution is also driven by the news sentiment created after them.

我们提出了一种新的 Hawkes-Contact 模型，该模型结合了 Hawkes 过程和有限范围接触过程来模拟股价走势，尤其是在可能导致传染效应的新闻和其他信息流的影响下。为了充分捕捉潜在的价格过程，我们采用霍克斯过程来跟踪历史价格对其未来走势的完整路径，并采用接触过程来捕捉新闻/投资情绪的影响。我们通过使用原油指数 (Wind CZCE-TA) 的模拟收益和真实 5 分钟收益分析它们的统计特性，将这个完整模型与作为基准模型的单变量霍克斯过程进行比较。统计特性包括概率密度函数、互补累积分布函数和 Lempel-Ziv Complex。我们的结果表明，真实收益的分布往往与正态分布相去甚远，但通过 Hawkes 或 Hawke-Contact 模型模拟的收益可以实现与真实收益的紧密拟合，并表现出相似的统计特性。更重要的是，Hawkes-Contact 模型比简单的 Hawkes 模型更能捕捉回报走势中的特征，这表明价格演变也受其后产生的新闻情绪驱动。