This paper empirically examines the inter-linkages between energy consumption and economic growth in top ten energy-consuming countries i.e. China, the USA, Russia, India, Japan, Canada, Germany, Brazil, France and South Korea. We use the quantile-on-quantile (QQ) approach of Sim and Zhou (2015) to explore some nuanced features of the energy-growth nexus and to capture the relationship in its entirety. The results show a positive association between economic growth and energy consumption, with considerable variations across economic states in each country. A weak effect of economic growth on energy consumption is noted for the lower quantiles of economic growth in China, India, Germany and France, which suggests that energy as an input has less importance at low levels of economic growth. A weak effect of economic growth on energy consumption is also noted for the highest quantiles of income in the United States, Canada, Brazil and South Korea, which indicates that energy demand decreases with the increase in economic growth as these countries have become more energy efficient. The weakest effect of energy consumption on economic growth is observed at lower quantiles of energy consumption in China, Japan, Brazil and South Korea. The results of the present study can help in the design of energy development and conservation policies for sustainable and long-term economic development.

The Energy Consumption and Economic Growth Nexus in Top Ten Energy-Consuming Countries: Fresh Evidence from Using the Quantile-on-Quantile Approach

The young growing market for green bonds offers investors the opportunity to take an explicit focus on climate protecting investment projects. However, it is an open question whether this new asset class is also offering attractive risk–return profiles compared to conventional (non-green) bonds. To address this question, we match daily i-spreads of green-labeled and similar non-green-labeled bonds and look at their pricing differentials. We find that rating classes AA–BBB of green bonds as well as the full sample trade marginally tighter for the respective period compared to non-green bonds of the same issuers. Furthermore, financial and corporate green bonds trade tighter than their comparable non-green bonds, and government-related bonds on the other hand trade marginally wider. Issue size, maturity and currency do not have a significant influence on differences in pricing but industry and ESG rating.

Are green bonds priced differently from conventional bonds

The study of volatility spillovers provides useful insights into how information is transmitted from stock market to foreign exchange market and vice versa. This paper explores volatility spillovers between the Indian stock and foreign exchange markets. The results indicate that there exists a bidirectional volatility spillover between the Indian stock market and the foreign exchange market with the exception of S&P CNX NIFTY and S&P CNX 500. The findings of the study also suggest that both the markets move in tandem with each other and there is a long run relationship between these two markets. The results of significant bidirectional volatility spillover suggest that there is an information flow (transmission) between these two markets and both these markets are integrated with each other. Accordingly, financial managers can obtain more insights in the management of their international portfolio affected by these two variables. This should be particularly important to domestic as well as international investors for hedging and diversifying their portfolio.

Volatility Spillover between Stock and ForeignExchange Markets: Indian Evidence

Quantile time-frequency price connectedness between green bond, green equity, sustainable investments and clean energy markets

Oil prices and agricultural commodity markets: Evidence from pre and during COVID-19 outbreak

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Return and volatility spillover across equity markets between China and Southeast Asian countries

Purpose The purpose of this paper is to examine the conditional correlations and spillovers of volatilities across CEE markets, namely, Hungary, Poland, the Czech Republic, Romania and Croatia, in the post-2007 financial crisis period. Design/methodology/approach The authors use five-dimensional GARCH-BEKK alongside with the CCC and DCC models. Findings The estimation results of the three models generally demonstrate that the correlations between these markets are particularly significant. Also, own-volatility spillovers are generally lower than cross-volatility spillovers for all markets. Practical implications These results recommend that investors should take caution when investing in the CEE equity markets as well as diversifying their portfolios so as to minimize risk. Originality/value Unlike the previous studies in this field, this paper is the first study using multivariate GARCH-BEKK alongside with CCC and DCC models. The study makes an outstanding contribution to the existing literature on spillover effects and conditional correlations in the CEE financial stock markets.

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An analysis of CEE equity market integration and their volatility spillover effects

This study explores the connectedness between cryptocurrencies (Bitcoin, Ethereum, Ripple, Bitcoin cash and Ethereum Operating System) and major stock markets (NYSE composite index, NASDAQ composit...

Are stock markets and cryptocurrencies connected

This article attempts to examine the changing nature of volatility spillovers among foreign exchange markets of select Central and Eastern European countries (CEEs-5), namely, Hungary, the Czech Re...

Volatility Behaviour of the Foreign Exchange Rate and Transmission Among Central and Eastern European Countries: Evidence from the EGARCH Model:

This study investigates the connectedness between Bitcoin prices and major stock indices in the Asia-Pacific region from February 2012 to August 2019. Based on the wavelet transform framework, we f...

Ngo Thai Hung

Papers

Return and volatility spillover across equity markets between China and Southeast Asian countries

An analysis of CEE equity market integration and their volatility spillover effects

Are stock markets and cryptocurrencies connected

Volatility Behaviour of the Foreign Exchange Rate and Transmission Among Central and Eastern European Countries: Evidence from the EGARCH Model:

Time-frequency nexus between bitcoin and developed stock markets in the asia-pacific