부산대학교 도서관

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.