From text to treasure: the predictive superiority of a FinTech index in stock market returns

被引:0
|
作者
Guo, Yangli [1 ]
Ma, Feng [1 ]
Wang, Yizhi [2 ]
Zhong, Juandan [1 ]
机构
[1] Southwest Jiaotong Univ, Sch Econ & Management, Chengdu, Peoples R China
[2] Cardiff Univ, Cardiff Business Sch, Cardiff, Wales
基金
中国国家自然科学基金;
关键词
FinTech index; text analysis; predictive power; stock market returns; economic downturns; G17; G12; C53; G14; O33; TECHNOLOGY SHOCKS; SENTIMENT; PREDICTABILITY; COMBINATION; PREMIUM; RISK; ACCURACY; GROWTH; SAMPLE; TESTS;
D O I
10.1080/1351847X.2024.2399773
中图分类号
F8 [财政、金融];
学科分类号
0202 ;
摘要
This study employs a text analysis methodology to construct a Financial Technology (FinTech) Index, utilizing textual data from The New York Times. The primary aim is to investigate the correlation between financial technology and stock market performance. Our findings provide compelling evidence that the FinTech Index possesses substantial predictive capability for excess returns in the US stock market, a feature that becomes particularly pronounced during economic downturns. Notably, when compared with traditional macroeconomic indicators, the FinTech Index offers valuable incremental insights. Moreover, this study expands to include sector-level and international market analyses, demonstrating the broad applicability and robust performance of the FinTech Index. Importantly, through the use of out-of-sample testing, we substantiate that the FinTech Index demonstrates superior predictive accuracy, presenting opportunities for investors to achieve higher economic returns.
引用
收藏
页数:18
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