In COVID-19 outbreak, correlating the cost-based market liquidity risk to microblogging sentiment indicators

Abstract

In the wake of the COVID-19 pandemic, this paper links the cost-based market liquidity risk to investors’ sentiment analysis through microblogging content. The study performed a sentiment analysis of tweets and considered distinct measures of cost-based market liquidity. In financial market, liquidity risk and execution cost are other major concerns for both academics and those who participate in trading. The literature in asset pricing usually distinct the informed trades and uninformed trades. Due to the growth of internet and Web 2.0 phenomenon, microblogging social service providers are considerably big data sources for various purposes, including the financial market behavior modeling and prediction. The empirical results, based on the analysis of Australian Securities Exchange (ASX), found that Twitter sentiment indicators were relevant in the forecasting of market liquidity and execution cost at market level. In the COVID-19 outbreak, the investors’ pessimistic perceptions about the ASX caused adverse impact on its liquidity and final cost paid by traders.

Keywords

• microblogging data
• textual sentiment analysis
• asset pricing