We use the Autoregressive Integrated Moving Average(ARIMA)model and Facebook Prophet model to predict the closing stock price of Google during the COVID-19 pandemic as well as compare the accuracy of these two models...We use the Autoregressive Integrated Moving Average(ARIMA)model and Facebook Prophet model to predict the closing stock price of Google during the COVID-19 pandemic as well as compare the accuracy of these two models’predictions.We first examine the stationary of the dataset and use ARIMA(0,1,1)to make predictions about the stock price during the pandemic,then we train the Prophet model using the stock price before January 1,2021,and predict the stock price after January 1,2021,to present.We also make a comparison of the prediction graphs of the two models.The empirical results show that the ARIMA model has a better performance in predicting Google’s stock price during the pandemic.展开更多
Based on the research technology of scholars' prediction of farmers' income and the data of per capita annual net income in rural households in Henan Statistical Yearbook from 1979 to 2009,it is found that tim...Based on the research technology of scholars' prediction of farmers' income and the data of per capita annual net income in rural households in Henan Statistical Yearbook from 1979 to 2009,it is found that time series of farmers' income is in accordance with I(2)non-stationary process.The order-determination and identification of the model are achieved by adopting the correlogram-based analytical method of Box-Jenkins.On the basis of comparing a group of model properties with different parameters,model ARIMA(4,2,2)is built up.The testing result shows that the residual error of the selected model is white noise and accords with the normal distribution,which can be used to predict farmers' income.The model prediction indicates that income in rural households will continue to increase from 2009 to 2012 and will reach the value of 2 282.4,2 502.9,2 686.9 and 2 884.5 respectively.The growth speed will go down from fast to slow with weak sustainability.展开更多
文摘We use the Autoregressive Integrated Moving Average(ARIMA)model and Facebook Prophet model to predict the closing stock price of Google during the COVID-19 pandemic as well as compare the accuracy of these two models’predictions.We first examine the stationary of the dataset and use ARIMA(0,1,1)to make predictions about the stock price during the pandemic,then we train the Prophet model using the stock price before January 1,2021,and predict the stock price after January 1,2021,to present.We also make a comparison of the prediction graphs of the two models.The empirical results show that the ARIMA model has a better performance in predicting Google’s stock price during the pandemic.
基金Supported by the Planned Project of"Studies on Institutional Innovation of Farml and Property Rights in the Core Area of Grain Production"Launched by Philosophy and Social Sciences in Henan Province
文摘Based on the research technology of scholars' prediction of farmers' income and the data of per capita annual net income in rural households in Henan Statistical Yearbook from 1979 to 2009,it is found that time series of farmers' income is in accordance with I(2)non-stationary process.The order-determination and identification of the model are achieved by adopting the correlogram-based analytical method of Box-Jenkins.On the basis of comparing a group of model properties with different parameters,model ARIMA(4,2,2)is built up.The testing result shows that the residual error of the selected model is white noise and accords with the normal distribution,which can be used to predict farmers' income.The model prediction indicates that income in rural households will continue to increase from 2009 to 2012 and will reach the value of 2 282.4,2 502.9,2 686.9 and 2 884.5 respectively.The growth speed will go down from fast to slow with weak sustainability.
