Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | 楊茜文 | zh_TW |
dc.contributor.author | 朱芳妮 | zh_TW |
dc.contributor.author | 呂少毫 | zh_TW |
dc.contributor.author | 陳明吉 | zh_TW |
dc.contributor.author | Chien-Wen Yang | en_US |
dc.contributor.author | Fang-Ni Chu | en_US |
dc.contributor.author | Shao-Hao Lu | en_US |
dc.contributor.author | Ming-Chi Chen | en_US |
dc.date.accessioned | 2022-12-19T08:08:09Z | - |
dc.date.available | 2022-12-19T08:08:09Z | - |
dc.date.issued | 2022-10-01 | en_US |
dc.identifier.issn | 1023-9863 | en_US |
dc.identifier.uri | http://dx.doi.org/10.29416/jms.202210_29(4).0004 | en_US |
dc.identifier.uri | http://hdl.handle.net/11536/159684 | - |
dc.description.abstract | 人對於大量訊息資料的關注是有限並且是選擇性的,使得關注力在何處成為決策的重要因素。本文探討房市參與者的關注是否會影響房價,採用Google Trends搜尋引擎的關鍵字搜尋量為代理變數,建構五個關注指標以測試2006年至2019年的台北市房市參與者之關注與房價關係。實證結果確認台灣的房市參與者關注會影響房價,關注增加會導致房價上升。進一步將樣本以時間區分成房價上升與平穩兩時期,發現市場參與者的關注有不對稱情形,在房價上升期較有影響力。本文最後比較關注與情緒兩指標對房價的預測能力,發現兩者預測能力接近,但關注模型的預測能力會略優於情緒模型。 | zh_TW |
dc.description.abstract | Investor attention to a large amount of information is limited and selective, making where attention is an important factor in decision-making. We explore whether the attention of housing market participants will affect housing prices. The search volume of keywords using the Google Trends search engine are the proxy variables to construct five attention indicators to test the relationship between the attention of participants and housing price in the Taipei housing market from 2006 to 2019. The empirical results confirm that the attention of market participants will affect house prices, and the increase in attention will cause house prices to rise. Divided price sample to rise and stable stage, we found that the attention of participants is asymmetry, which is more influential in the period of house price rise. We also compare the indicators of attention and sentiment on the predictive ability of house prices. The results show that the predictive ability is close. The predictability in attention model is slightly better than sentiment model. | en_US |
dc.language.iso | zh_TW | en_US |
dc.publisher | 國立陽明交通大學經營管理研究所 | zh_TW |
dc.publisher | Institute of Business and Magement, National Yang Ming Chiao Tung University | en_US |
dc.subject | 認知假說 | zh_TW |
dc.subject | 有限關注 | zh_TW |
dc.subject | Google搜尋量指數 | zh_TW |
dc.subject | 房價 | zh_TW |
dc.subject | Investor Recognition | en_US |
dc.subject | Limited Attention | en_US |
dc.subject | Google Trends | en_US |
dc.subject | Google SVI | en_US |
dc.subject | Real Estate Price | en_US |
dc.title | 房市參與者之關注會影響房價嗎? | zh_TW |
dc.title | Will Attention of Market Participants Influence Housing Prices? | en_US |
dc.type | Campus Publications | en_US |
dc.identifier.doi | 10.29416/jms.202210_29(4).0004 | en_US |
dc.identifier.journal | 管理與系統 | zh_TW |
dc.identifier.journal | Journal of Management and Systems | en_US |
dc.citation.volume | 29 | en_US |
dc.citation.issue | 4 | en_US |
dc.citation.spage | 495 | en_US |
dc.citation.epage | 523 | en_US |
Appears in Collections: | Journal of Management and System |