Publicação
Using the baidu index to predict chinese housing price and volume - a survey-based keyword selection approach
| datacite.subject.fos | Ciências Sociais::Economia e Gestão | pt_PT |
| dc.contributor.advisor | Franco, Sofia | |
| dc.contributor.author | Quanxing, Zhang | |
| dc.date.accessioned | 2019-05-22T13:35:43Z | |
| dc.date.available | 2019-05-22T13:35:43Z | |
| dc.date.issued | 2019-01-15 | |
| dc.description.abstract | The paper uses a survey-based keyword selection approach to examine the effect of the Baidu Index on Chinese real estate trends. After obtaining weights from 546 questionnaires to composite the indexes, I find that in the transaction volume model with the survey-based indexes, the adjusted R2 increases by 8.240 percentage points compared to the baseline model. Such improvement also exists in a forecasting test, reducing the Mean Absolute Error by 2.931 percent and the Mean Squared Error by 5.079 percent. The paper further contributes to the keyword selection method and the model by exploiting an up-to-date dataset. | pt_PT |
| dc.identifier.tid | 202226964 | pt_PT |
| dc.identifier.uri | http://hdl.handle.net/10362/70406 | |
| dc.language.iso | eng | pt_PT |
| dc.subject | Baidu index | pt_PT |
| dc.subject | Housing price and volume | pt_PT |
| dc.subject | Keyword selection | pt_PT |
| dc.subject | Survey approach | pt_PT |
| dc.title | Using the baidu index to predict chinese housing price and volume - a survey-based keyword selection approach | pt_PT |
| dc.type | master thesis | |
| dspace.entity.type | Publication | |
| rcaap.rights | openAccess | pt_PT |
| rcaap.type | masterThesis | pt_PT |
| thesis.degree.name | A Work Project, presented as part of the requirements for the Award of a Masters Degree in Finance from the NOVA – School of Business and Economics | pt_PT |