The classical finance theory postulates that markets are informationally efficient and that the actions of arbitrageurs always bring stock prices to their correct values. Behavioural finance, on the other hand, emphasises the role of investor sentiment in the formulation of asset prices. In this study, we provide insights into the relationship between textual sentiment extracted from Twitter and stock returns in the fragile market of Zimbabwe between 24 February 2019 and 22 June 2020. Wavelet analysis is used to find the linkages between sentiment and returns in a frequency-time domain. The results from this study show that coherence is persistent and significant in highly volatile periods characterised by increasing inflation as well as during the time COVID-19 was declared a global pandemic. The findings also show that macroeconomic instability, especially hyperinflation, induces fear in investors while the onslaught of black swan events like the COVID-19 pandemic leads to greed in the financial markets as investors become uncertain about the future. The government could, therefore, prioritise macroeconomic stability as the high coherence between sentiment and returns during a crisis like the COVID-19 pandemic may lead to a crashing of the stock market. Classical finance theory, therefore, falls short in explaining the stock market returns as the evidence in the study shows that investors are susceptible to investor sentiment.

References are not ready for this file yet, please refer to reference from the PDF file

Keywords

Twitter sentiment, Zimbabwe Stock Exchange, Old Mutual Implied Rate, wavelet analysis, behavioural finance