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

Guo, Yangli, Ma, Feng, Wang, Yizhi and Zhong, Juandan 2024. From text to treasure: the predictive superiority of a FinTech index in stock market returns. European Journal of Finance 10.1080/1351847X.2024.2399773

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Abstract

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.

Item Type:	Article
Date Type:	Published Online
Status:	In Press
Schools:	Business (Including Economics)
Publisher:	Taylor and Francis Group
ISSN:	1351-847X
Date of First Compliant Deposit:	2 October 2024
Date of Acceptance:	26 August 2024
Last Modified:	07 Nov 2024 20:30
URI:	https://orca.cardiff.ac.uk/id/eprint/172549

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