Many behavioral economics and finance studies recognize the bounded rationality and psychological biases of investors who often rely on and/or are influenced by computational shortcuts, heuristics, frame dependence and intuition when making decisions in a complicated and uncertain world with market frictions. Such phenomenon might be more significant in the real estate market due to the unavoidable information asymmetry and many limits to arbitrage. In addition, with the development of the Internet and technology, the amount of data is growing rapidly with complex types, and therefore how to extract or combine these unstructured data has become an important issue in contemporary researches of social science. Hence, this paper intends to employ these unstructured data in the real estate market—such as news reports, online forum posts, and online search behaviors—to extract the so-called public sentiment and crisis sentiment, and uses these sentiment indices to fit the variation of Taiwan housing market. The empirical results showed that sentiment indicators have a significant impact on the transaction price and volume of the real estate market.
|Effective start/end date||2020/08/01 → 2021/07/31|
- public sentiment
- crisis sentiment
- textual mining
- housing market
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