ABSTRACT
Purpose: This study aims to investigate the dynamic interconnectedness of economic policy uncertainty (EPU), fiscal policy uncertainty (FPU) and monetary policy uncertainty (MPU) in four nations, the USA, Japan, Greece and South Korea, between 1998 and 2021. Design/methodology/approach: To comprehend the cross-category/cross-country evolution of uncertainty connectedness, the authors use the conditional connectedness approach. By using an inclusive network, this strategy lessens the bias caused by omitted variables. The TVP-VAR method is advantageous as it eliminates outliers that may potentially skew the results and reduces the bias caused by picking arbitrary rolling windows. Findings: Based on the findings, aggregate EPU is a net transmitter of policy uncertainties across all countries when conditional-country connectedness is used. MPU receives significantly more spillovers than FPU does across all countries, even though both are primarily recipients of uncertainties. The USA appears to be a transmitter of categorical spillovers before COVID-19, while Greece appears to be a net receiver of all category spillovers in terms of category-specific connectedness. The existence of extreme global events is also seen to cause an increase in category-specific and country-specific connectedness. Additionally, the authors report that conditional country-specific connectedness is greater than conditional category-specific connectedness. Originality/value: This study expands existing literature in several ways. Firstly, the authors use a novel conditional connectedness approach, which has not been used to untangle cross-category/cross-country policy uncertainty connectedness. Secondly, they use the TVP-VAR approach which does not depend on rolling windows to understand dynamic connectedness. Thirdly, they use an expanded number of countries in their analysis, a departure from existing studies that have in most cases used two countries to understand categorical EPU connectedness. © 2023, Kingstone Nyakurukwa and Yudhvir Seetharam.
ABSTRACT
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.