Cannabis Stocks Returns: The Role of Liquidity and Investors’ Attention via Google Metrics

This paper studies one of the most popular investment themes over recent years, investing in the cannabis industry. In particular, it investigates relationships between investor attention, as proxied by Google Trends, and stock market activities, i.e., return, volatility, and liquidity. To this end, in the empirical analysis we study how liquidity and investors’ attention affect the return dynamics of an investment in cannabis stocks by augmenting the three-factor Fama–French model. In addition, we use a vector autoregressive approach and the impulse response function to measure shock transmission between the variables under consideration. Our empirical findings show that there is a statistically positive relationship between cannabis stock returns and liquidity. We also find that increased investors’ attention results in higher returns.

Global and regional shock transmission: an Asian perspective

This paper constructs and uses the global input–output (GIO) table with 35 industries, 29 endogenous countries and 59 exogenous countries, and develops new indices to measure the degree of shock transmission in terms of intermediate goods and value-added embodied in production induced by negative global demand shock to finished goods. After the Global Financial Crisis (GFC) in 2008, China did not experience a large decline in economic growth, even though China’s gross exports fell most severely among Asian countries. In contrast, a sharp decrease in Japanese GDP in 2009 is a consequence of a substantial decline in finished goods exports, especially in the transport equipment industry. In Japan, the shock effect tends to be absorbed in its domestic sector and is not transmitted to other foreign countries. An asymmetric pattern of shock transmission between Japan and other Asian countries can explain why Japan was more affected by GFC than other Asian countries.

Shock propagation channels behind the global economic contagion network. The role of economic sectors and the direction of trade

Examining the spread of macroeconomic phenomena between countries has become increasingly popular after the 2008 economic crisis, but the recent COVID-19 pandemic rendered this issue much more relevant as it shed more light on the risks arising from strongly interconnected economies. This paper intends to extend previous studies in this line by examining the relationship between trade openness and business cycle synchronization. It extends the scope of previous analyses in three areas. First, we use a Granger-causality approach to identify synchronization. Second, trade is broken down to the sector level and third, we distinguish between upstream and downstream connections. These developments allow for a directed approach in the analysis. We use conditional logit regressions to estimate the effect of trade openness on the probability of shock-transmission. The results presented in this study contribute to the literature in two ways. First, in addition to revealing a positive effect of aggregate two-way trade on shock-contagion, it also points out that this overall effect hides diverse behavior in specific trading sectors as well as upstream and downstream channels. Second, while some sectors are not significant channels of shock-transmission in either directions, upstream channels seem to be important in agriculture while downstream channels dominate machinery and other manufactures. Also, there are sectors (chemicals and related products) trade in which affects shock-transmission negatively.

The Differences in Mean and Volatility Shock Transmission among Bitcoin, Currencies from Developed Countries, and Currencies from Emerging Countries

This paper studied the mean and volatility transmission among Bitcoin as the most prominent cryptocurrency, exchange rates from developed countries/regions, and exchange rates from emerging countries/regions. Using daily returns between January 1, 2015, and December 31, 2018, and Bivariate VAR - Diagonal VECH models. The empirical results suggest there was no mean transmission between USD/EUR and USD/BTC. However, there was a unidirectional mean shock transmission link from USD/CNH, USD/MAD, and USD/IDR to USD/BTC. The results also suggested the existence of a bidirectional cross-volatility persistence link between bitcoin and all the exchange rates, except for USD/IDR and a bidirectional cross-volatility spillover link between USD/BTC and USD/CNH. A critical implication of these results is that they will be of use to investors, speculators, risk managers, and policymakers in understanding the degree of integration in terms of volatility and return among Bitcoin, currencies from developed, and currencies from emerging countries.

Fiscal dominance and exchange rate stability in Nigeria

This study investigates fiscal dominance and exchange rate stability in Nigeria. The period of investigation spanned 1981q1–2018q4, and the Structural Vector Autoregression (SVAR) technique was employed to test the fiscal dominance hypothesis and further examine the shock transmission effects of fiscal deficit components such as budget deficit and public debt on exchange rate movement in Nigeria. As a robustness, Autoregressive Distributed Lag (ARDL) technique was employed to analyse the shock transmission effects of these components on the movement of exchange rate in Nigeria. More so, granger causality test was conducted to trace the direction of causality among the fiscal deficit components and the exchange rates. The results show that budget deficit and changes in exchange rates in Nigeria have bi-causal relationship, while public debt could not granger cause exchange rate movement in the country. The SVAR estimates suggests that exchange rate movement in Nigeria reacted only to the shock effects of financial openness and the ARDL results indicate that both public debt and budget deficit have destabilizing effects on exchange rates in Nigeria.

Global and Regional Shock Transmission ―Application of Global Input-Output Table―

This paper constructs and uses the global input-output (GIO) table with 35 industries, 29 endogenous countries and 59 exogenous countries, and develops new indices to measure the degree of shock transmission in terms of intermediate goods and value-added embodied in production induced by negative global demand shock to finished goods. After the Global Financial Crisis (GFC) in 2008, China did not experience a large decline in economic growth, even though China’s gross exports fell most severely among Asian countries. In contrast, a sharp decrease in Japanese GDP in 2009 is a consequence of a substantial decline in finished goods exports, especially in the transport equipment industry. In Japan, the shock effect tends to be absorbed in its domestic sector and is not transmitted to other foreign countries. An asymmetric pattern of shock transmission between Japan and other Asian countries can explain why Japan was more affected by GFC than other Asian countries.