Assessing Dynamic Co-Movement of News Based Uncertainty Indices and Distance-to -Default of Global FinTech Firms

Abstract

Contemporary literature does not offer evidence on the causal relationship of default risk and investor sentiments for FinTech sector. We bridge this gap by assessing the dynamic co-movement between Distance-to-Default of leading global FinTech firms and three uncertainty indices namely Twitter Market Uncertainty Index-ENG, Twitter Economic Uncertainty Index-ENG, and US daily news-based Economic Policy. The sample period is from 07 April 2016 to 30 June 2021. The estimations are performed using Wavelet based analytical framework. The results reveal high dynamic co-movement of Twitter based uncertainty indices with Distance-to-Default of FinTech firms. However, there is very little co-movement between economic policy uncertainty and FinTech firms’ stability. The novelty of this work lies in the utilization of National University of Singapore’s Distance-to-Default measure, which is available in daily frequency and capable of performing dynamic data analysis. Our results offer maiden evidence of linkage of default risk and news based uncertainty indices.