Combining the Data of Google Trend to Forecast the Monthly Revenue of Firms in Taiwan\'s Telecom Industry
| Autor: | Tzu-Yu Yeh, 葉芷妤 |
|---|---|
| Rok vydání: | 2019 |
| Druh dokumentu: | 學位論文 ; thesis |
| Popis: | 107 In this study, we applied the econometric models to evaluate the extension of revenues of three major telecom companies in Taiwan. By this way, we hope the study results can help them to improve their operational efficiency. Besides, the significant variables in the model can also provide the directions of improving competency for the telecom operators. Based on the existing theories and the reference of relevant literatures, the regression model was established, and the statistical verification, such as moving average autoregressive model (ARIMA), autoregressive model (AR), mean moving average autoregressive model (MA), vector autoregressive model (VAR), and single root test, were used to figure out the best fitted regression model. This study collect the revenue data of Taiwan Mobile Co., Ltd., Chunghwa Telecom Co., Ltd., Far EasTone Telecommunications Co., Ltd.’s data, and Google trend data (key words in Chinese and English, the stock code, Chinese and stock code) in the period of April 2004 to April 2018 to predict their revenues from May 2018 to April 2019. Our results found that, the usage of data through related keyword searching frequency in google trend, with the combination of the monthly data in revenues of the Taiwan’s top 3 telecom companies, the VAR model is best model with the highest accuracy of prediction on their monthly revenues. Furthermore, according to our results, the revenue of Taiwan Mobile Co.Ltd. and Far EasTone Telecommunications Co., Ltd. are more fluctuations, the revenue of Chunghwa Telecom Co. Ltd. is relatively stable in the future. |
| Databáze: | Networked Digital Library of Theses & Dissertations |
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