No abstract

Governments around the world have responded to the COVID-19 outbreak with a mix of policies. The strictest responses of the New Zealand government are notable, given their abilities to contain and limit the spread of the virus. However, their impacts on stock returns remain unclear. This paper investigates the impact of three policies, namely lockdown, the stimulus package, and the travel ban, on the returns of 14 New Zealand industry stock indices. Using daily data from 1 January 2019 to 25 August 2020, evidence points to a heightened level of integration among the various industry stock indices during the early stages of the pandemic. Only lockdown has had a positive impact on aggregate stock returns, suggesting its ability to raise investors' confidence in the overall stock market. At the industry level, the impact of the three response policies is generally positive but heterogeneous across industry stock indices. Notably, none of the three adopted policies significantly impact technology, healthcare, and real estate returns.

No abstract

We examine the causal links between U.S. industry-wise credits and stock markets. The full sample bootstrap Granger causality results show that all stock markets Granger cause their CDS counterparts and there is also bidirectional causality for the banking, healthcare and material industries. The short-run parametric stability tests highlight that the full sample parameters are not stable and hence less reliable. The bootstrap rolling window estimations confirm the inconsistency in the CDS-stock causality relationships where bidirectional causalities are also found between the credit and stock markets that vary over different sub-samples. Finally, we analyze the impact of different financial and macroeconomic determinants on the CDS-stock causality through a probit model. Overall, the business conditions, stock market volatility, default premiums, Treasury bond rate and the slope of the yield curve are major drivers of the CDS-stock nexus. Our findings provide possible explanation for varying and mixed previous empirical findings in the existing literature, and hence have useful investment implications.JEL Classification: C32, G20, G32

No abstract

This study contributes to the literature on the relationship between fundamental economic factors and stock price movements. We evaluate the relationship between domestic and international macroeconomic indicators and financial sector index in a frontier market that is Amman Stock Exchange (ASE) in Jordan. We employed the ARDL bound testing approach and the VECM Granger causality test to examine long and short run relationships and the direction of causality among the variables. Monthly time series data from January 2007 to December 2016 were used to identify the relationships for interest rate (positive), inflation rate (insignificant), money supply (insignificant), industrial production index (insignificant), producer price index (negative), trade balance (insignificant), and crude oil price (negative). Our findings indicate that the deposit interest rate positively influenced the financial sector in the short run and the long run, while the producer price index and global oil price had significant negative impacts on the financial sector. This study contributes actionable insight for policy makers and investors regarding how global and domestic factors have significant impact on the financial index in Jordan. The current study provides several important implications and recommendations for investors, policy makers and the government. For example, the results imply that global oil prices have a

No abstract

A bulk of literature suggests that geopolitical events such as terrorist attacks dampen tourism demand. However, there is little research on whether this effect helps predict the return of the tourism equity sector. We provide country-level evidence on whether local and global geopolitical risk (GPR) predicts the first and second moments of tourism stocks in emerging economies. This objective was achieved by employing the non-parametric causality-in-quantiles (CiQ) model and a cross-quantilogram (CQ) test, which allowed us to uncover the predictive potential of GPR for the tourism sector equities. Our findings, obtained through the CiQ model, suggest that while both local and global GPRs carry significant potential for predicting the returns and volatility of tourism stocks of most emerging economies under normal market conditions, they seem to play no such role in certain countries. These countries include South Korea, for which only a limited number of tourism stocks trade on the domestic stock market compared to other sectors, and Colombia, for which both the domestic stock market and tourism sectors are at an emerging stage. Further, it turns out that, compared to its local counterpart, global GPR has a more pronounced predictive power for the tourism stocks of emerging economies. Finally, with some exceptions, the results are qualitatively similar, and hence reasonably robust, to those when a directional predictability model is applied. Given that geopolitical shocks are largely unanticipated, our findings underscore the importance of a robust tourism sector that can help the market recover to stability as well as an open economy that allows local investors to diversify country-specific risks in their portfolios. Implications and directions for future research are discussed.