Purpose
This paper aims to explore the impact of investor sentiments on economic policy uncertainty (EPU). The analysis also considers the momentum effect, stock market returns volatility and equity pricing inefficiencies across markets, which, to the best of the authors’ knowledge, has not been addressed in the literature. The role of these control variables has collectively been considered to have important behavioral implications for international investors
Design/methodology/approach
Quantile regressions are used for estimation purpose, as it provides robust and more efficient estimates rather than those coming from the traditional regression model.
Findings
The momentum effect is negative and significant only at higher quantiles, while oil prices are positive and significant across all quantiles. The exchange rate exerts a negative and significant effect on EPU, whereas equity price volatility (i.e. investor sentiment) exerts a negative and significant impact on EPU in most of the quantiles.
Research limitations/implications
The results have important implications for international investors and policymakers, especially in terms of the breakdown of economic policy uncertainty across different sample markets. The breakdown of complete sample period into sub-samples acts as a robust analysis and documents the similarity of the results for the Asian and developed markets cases, but not in the case of the European markets.
Practical implications
The findings imply the importance of financial stability that impacts the accumulation of systemic risks and adds smoothness to the financial cycle in particular geographical areas.
Originality/value
The contribution of this paper is threefold. First, existing literature highlights and empirically tests the impact of economic policy uncertainty on different market, macro-economic and global control variables. The analysis, however, performs it in the reverse order, i.e. analyzing the impact of the momentum effect (investor sentiment variables), equity market inefficiencies and volatility (market variables) and exchange rates and Brent oil (control variables). Second, to check the sensitivity of economic policy uncertainty, the analysis analyzes a wide range of markets, segregated as emerging, developed and European regions over the sample period to generate region-wise implications. Finally, the analysis explores the relationship of aforementioned variables with economic policy uncertainty keeping in view the non-linear structure and prior evidence and investor sentiments and economic policy uncertainty in the regression model.
Using Multi-View Learning to Improve Detection of Investor Sentiments on Twitter
