Authors: Divya Verma Gakhar; Shweta Kundlia
Addresses: Guru Gobind Singh Indraprastha University, Sector 16 C, Dwarka, Delhi, 110078, India ' Guru Gobind Singh Indraprastha University, Sector 16 C, Dwarka, Delhi, 110078, India
Abstract: This study aims to predict stock characteristics such as returns, volatility, and liquidity of companies involved in sustainable investments, using sentiment analysis. The paper uses lexicon-based sentiment analysis and develops regression-based predictive models for testing the impact of Twitter sentiments on stock market movements using four sentiment scores (positive, negative, total, and directional). It is found that positive Twitter sentiments are better able to predict stock returns and volatility than liquidity. While negative sentiment scores can better predict volatility and liquidity than stock returns. All stock market variables are found to be significantly affected by the total number of tweets, i.e., posting volumes. Our study suggests that investors investing in companies with sustainability interests tend to keep track on their corporate social platforms, and thus, companies involved in sustainable investments should remain active on social networking platforms such as Twitter to maintain their corporate image and enhance social value.
Keywords: sentiment analysis; Twitter; illiquidity; sustainability.
International Journal of Economic Policy in Emerging Economies, 2021 Vol.14 No.5/6, pp.536 - 565
Received: 30 Nov 2019
Accepted: 14 Oct 2020
Published online: 09 Nov 2021 *