Green bond vs. Islamic bond: Which one is more environmentally friendly?

This research investigates the dynamic dependence and causality relationship of the S&P Kensho Clean Energy (CE) and Cleantech (CT) indices with two green bond indices, including the S&P Green Bond Index (GB) and Green Bond Select (GBS) indices, and four Islamic bond indices, including A-, AA-, AAA-, and BBB-graded Sukuk Indices. In the long- and medium-term, the dependence of CE and CT on Sukuk and green bond indices strengthens under normal or bearish market conditions based on quantile cross-spectral (coherency). Overall, among all alternative financing instruments, AA- and A-rated Sukuk indices and GBS indices have higher coherency with CE and CT. Furthermore, the direction of causality in the frequency domain is most commonly observed from Sukuk and bond indices to CT and CE. Once again, AA-rated, A-rated, and GBS have more significant causality effects on CT and CE for nearly all frequencies compared to other indices. These results present vital implications for both policymakers who want to advocate the development of environmentally friendly projects and investors who want to invest their capital in green economic activities in terms of diversifying and hedging their investments.

Quantiles dependence and dynamic connectedness between distributed ledger technology and sectoral stocks: enhancing the supply chain and investment decisions with digital platforms.

Distributed Ledger Technology (DLT) is highly applicable in various fields, especially the supply chain in many sectors. Against limited empirical evidence, this paper analyzes the relations between the Kensho Distributed Ledger Technology Index and stock indices of 12 sectors, including communication services, consumer discretionary, consumer staples, energy, health care, financials, industrials, information technology, materials, utilities, and real estate, and ESG by employing the quantile coherency and dynamic connectedness techniques. Our results reveal that the quantile coherency between the DLT stock index and the sectoral stock indices in almost all cases is significant and positive. The positive co-movement tends to be stronger in the longer terms and as we move from the lower to the higher quantiles, implying that they are more strongly connected in the long term and during the bearish market condition. Moreover, the dynamic connectedness indicates that the DLT stocks and the sectoral stocks are highly connected, with the former being a net transmitter of spillover shocks. The spillovers are also time-varying, and the results significantly corroborate those of the quantiles coherency methods. Among other relevant implications, DLT can be an important factor in the development and enhancement of these sectors.

Sector-by-sector analysis of dependence dynamics between global large-cap companies and infectious diseases: A time-varying copula approach in EBOV and COVID-19 episodes.

Infectious diseases and widespread outbreaks influence different sectors of the economy, including the stock market. In this article, we investigate the effect of EBOV and COVID-19 outbreaks on stock market indices. We employ time-varying and constant bivariate copula methods to measure the dependence structure between the infectious disease equity market volatility index (IEMV) and the stock market indices of several sectors. The results show that the financial and communication services sectors have the highest and the lowest negative dependency on IEMV during the Ebola virus (EBOV) pandemic, respectively. However, the health care and energy sectors have the highest and lowest negative dependency on IEMV during the COVID-19 outbreak, respectively. Therefore, the results confirm the heterogeneous time-varying dependency between infectious diseases and the stock market indices. The finding of our study contributes to the ongoing literature on the impact of disease outbreaks, especially the novel coronavirus outbreak on global large-cap companies in the stock market.