Agosto Arianna, Giudici Paolo
University of Pavia, Pavia, Italy.
Digit Finance. 2020;2(1-2):159-167. doi: 10.1007/s42521-020-00021-3. Epub 2020 May 11.
Digital finance is going to be heavily affected by the COVID-19 outbreak. We present a statistical model which can be employed to understand the contagion dynamics of the COVID-19, so that its impact on finance can possibly be anticipated, and digitally monitored. The model is a Poisson autoregression of the daily new observed cases, and considers both short-term and long-term dependence in the infections counts. Model results are presented for the observed time series of China, the first affected country, but can be easily reproduced for all countries.
数字金融将受到新冠疫情的严重影响。我们提出了一个统计模型,可用于理解新冠疫情的传播动态,从而有可能预测其对金融的影响并进行数字监测。该模型是对每日新增确诊病例的泊松自回归模型,同时考虑了感染病例数的短期和长期依赖性。我们给出了首个受影响国家中国的观测时间序列的模型结果,不过该结果很容易应用于所有国家。