Green Stock Research Articles

Investor sentiment and stock price jumps: A network analysis based on China’s carbon–neutral sectors

In this paper, we analyze the interconnectedness between investor sentiment and stock price jumps based on the two-layer network models. We first use the Diebold and Yilmaz (DY) and Baruník and Křehlík (BK) spillover indexes to analyze the interactive effects of investor sentiment and price jumps between different industries in China's carbon–neutral sectors from the time and frequency domains. The results verify strong two-way spillover effects of investor sentiment and jump volatility among green industries. The connectedness in the short-term risk network of stock volatility is significantly higher than that of the Internet sentiment network, and the short-term risk spillover effect of the network plays a leading role in the total risk spillover. Subsequently, we further study the dynamic spillover between investor sentiment and jump volatility using the rolling time window. The dynamic network reveals significant heterogeneity in the spillover of Internet sentiment, and the interaction effect of investor sentiment and jump volatility displays time-varying characteristics. The green industrials and energy industries are systemically important sectors in the two-layer network system. The empirical results show the complex risk contagion mode in the green stock market and provide a reference for investors and market regulators on the risk management of the green stock market.

Development and evaluation of Islamic green financing: A systematic review of green sukuk

The threat of the global climate crisis demands improvement and adjustment from various sides, including the financial sector. Islamic finance responds to environmental responsibility by presenting environmentally friendly financing products in green sukuk. This study aims to show the development trend of the number of publications in green sukuk and systematize the results of studies that explain the development and evaluation of the emergence of green sukuk investments. This study analyzed 15 publications on green sukuk during the 2016-2022 years indexed by the Scopus database. As for methodology, the descriptive analysis was used to explain the green sukuk data quantitatively; the synthesis analysis was used to describe data based on four directions (the development of models (10 sources), opportunities (12 sources), challenges (12 sources), and evaluations of green sukuk (10 sources). Preferred Reporting Items for Systematic Review and Meta-Analyses standard were used to choose samples for this investigation. The green sukuk challenge is dealing with the sukuk market after the pandemic. Several evaluation findings regarding managing commitment from the government and investors for the renewable energy sector and efforts to provide low-cost sukuk financing and risk minimization are found. Green sukuk demands efficient management to be more viable, competitive, and attractive to investors if the operational area supports it. Green sukuk projects face expanding green funding, global climate financing, managing renewable energy, and validating greenhouse gas emissions. The green stock market reaction requires coordination amongst economic subsectors.

Time-frequency connectedness among traditional/new energy, green finance, and ESG in pre- and post-Russia-Ukraine war periods

This paper examines how the continuing war between Russia and Ukraine affects the transmission of returns spillovers among traditional/new energy, green finance, and ESG. We evaluate the dynamic and directional risk connectedness across time and at various frequency bands using Diebold and Yilmaz and Baruník and Křehlík approaches. First, there is a noticeable rise in overall connectedness, from 19.36% to 29.99%, and it is more pronounced in the short time. Second, new energy, ESG, and green stocks are closely linked. Third, new energy, ESG, and green stock are main risk transmitters functioning in the long- and short-term respectively after the war. Fourth, the oil market becomes more vulnerable to other markets, changing from a net transmitter to a net receiver. These findings can offer important empirical implications for governments and market participants to copy with the contagion risk during the Russia-Ukraine war.

Factor exposure heterogeneity in green and brown stocks

Using the peer-exposure ratio, we explore the factor exposure heterogeneity in green and brown stocks. By looking at peer groups of S&P 500 index firms over 2009–2020 based on their greenhouse gas emission levels, we find that, on average, green stocks exhibit less factor exposure heterogeneity than brown stocks for most of the traditional equity factors but the value factor. Hence, investment managers shifting their investments from brown stocks to green stocks have less room to differentiate themselves regarding their factor exposures. Finally, we find that factor exposure heterogeneity has increased for green stocks compared to earlier periods.

Can green assets hedge against economic policy uncertainty? Evidence from China with portfolio implications

This paper examines whether green assets can hedge against economic policy uncertainty (EPU) via asymmetric time-varying connectedness and EGARCH models. Using daily data in China spanning from March 2014 to June 2022, we find that (1) an evident asymmetric connectedness exists between green assets and EPU. (2) Green bond, carbon emission allowances and some green stocks can act as hedging or safety-haven assets against EPU, and the conclusion remains robust to an alternative proxy of EPU. (3) The minimum variance and connectedness portfolios provide superior performance during pre- and post-COVID-19 periods, respectively, thereby carrying substantial portfolio implications.

Research on the time-varying effects among green finance markets in China: A fresh evidence from multi-frequency scale perspective

Green finance is an essential instrument for achieving sustainable development. Objectively addressing correlations among different green finance markets is conducive to the risk management of investors and regulators. This paper presents evidence on the time-varying correlation effects and causality among the green bond market, green stock market, carbon market, and clean energy market in China at multi-frequency scales by combining the methods of Ensemble Empirical Mode Decomposition Method (EEMD), Dynamic Conditional Correlation (DCC) GARCH model, Time-Varying Parameter Vector Autoregression with Stochastic Volatility Model (TVP-VAR-SV), and Time-varying Causality Test. In general, the significant negative time-varying correlations among most green finance markets indicate a prominent benefit of risk hedging and portfolio diversification among green financial assets. In specific, for different time points and lag periods, the green finance market shock has obvious time-varying, positive and negative alternating effects in the short-term scales, while its time delay and persistence are more pronounced in the medium-term and long-term scales. Interestingly, a positive event shock will generate positive connectivity among most green finance markets, whereas a negative event including the China/U.S. trade friction and the COVID-19 pandemic may exacerbate the reverse linkage among green finance markets. Furthermore, the unidirectional causality of “green bond market - carbon market - green stock and clean energy markets” was established during 2018–2019.

Asymmetric efficiency and connectedness among green stocks, halal tourism stocks, cryptocurrencies, and commodities: Portfolio hedging implications

This study examines asymmetric efficiency and connectedness among halal tourism stocks, green stocks, cryptocurrency, gold, and oil using data covering the period from 2018M12–2022M09. Employing asymmetric multifractal detrended cross-correlation analysis, this study finds gold to be the most efficient asset and halal tourism stocks to be more efficient than green stocks. The asymmetric connectedness approach identifies green stocks as net transmitters of return shocks in all market conditions and halal tourism stocks (oil) as net receivers of return shocks in normal and upward (downward) market conditions. The connectedness among the assets increases during major economic events such as COVID-19 and the Russia–Ukraine war. Portfolio analysis suggests that the minimum connectedness portfolio outperforms all the other methods and shows halal tourism and green stocks offer significant hedging effectiveness. Our findings have significant implications for investors and policymakers seeking to diversify portfolios, manage risks, and regulate information in periods of financial turmoil and asymmetric market conditions.

The impact of climate policy on U.S. environmentally friendly firms: A firm-level examination of stock return, volatility, volume, and connectedness

This paper investigates the green stock market reaction to climate policy events associated with the Paris Agreement and the U.S. presidential elections. We document abnormal returns, volatility and volume reactions to climate policy events among green stocks. However, the magnitude of the reactions varies between the tightening and loosening of climate policy and across subgroups of the green stock markets. Our connectedness analysis further investigates the spillover patterns among individual green stocks and confirms their heterogeneous natures when responding to the occurrence of these climate policy events. By constructing a minimum connectedness portfolio based on the estimated connectedness among these green stocks, we find that investors can substantially reduce their risks. Our findings have strong implications for policy makers in designing policies to effectively promote green investments and mitigate climate change.

Hedging strategies among financial markets: the case of green and brown assets.

Recognizing the growing importance of the green energy market-renewable energy stocks and bonds-and its classification as a viable financial asset, this paper examines hedging strategies with brown market instruments-gold, oil, bond and the composite S&P500-on the green energy markets. That is, we examine whether, and to what extent brown assets can provide a hedge for green assets, using variants of the multivariate GARCH framework (DCC, ADCC and GO-GARCH). Our dataset spans the period 01/12/2008 to 30/09/2021. To account for the influence of the COVID-19 pandemic, we split the dataset into two-pre-covid (1/12/2008-10/03/2020) and covid-era (11/03/202-30/09/2021). Two key findings emanate from our results: first, conventional bonds and stocks provide the most consistent hedge for investment in the green markets. Second, the results are sensitive to the state of the market-hedging effectiveness declined during the covid period in the green stock market. Among other things, it is recommended that investors include instruments of the green market in portfolio allocation.

Green Stocks and the 2023 Banking Crisis

Green Stocks and the 2023 Banking Crisis

Volatility spillover effects and risk assessment of Indian green stocks: a DCC-GARCH analysis

Volatility spillover effects and risk assessment of Indian green stocks: a DCC-GARCH analysis

The Impact of Green Stock Indices and ESG Considerations on Sustainable Finance—A Study of Chinese Green Indices

The Impact of Green Stock Indices and ESG Considerations on Sustainable Finance—A Study of Chinese Green Indices

ESG tail risk: The Covid-19 market crash analysis

This paper shows that strong ESG taste leads to higher tail risk in high-ESG (green) stocks compared to low-ESG (brown) stocks during market crashes. In crash episodes, strong ESG tastes induce investors to hold green stocks despite negative expected returns. Logically, the non-pecuniary benefit from ESG investing compensates for the dis-utility of financial loss. This expectation of price declines makes put options on green stocks more expensive and increases tail risk. I conduct a pseudo-causal analysis on the COVID-19 market crash that supports these theoretical findings. My findings provide novel implications for portfolio selection and risk management with ESG consideration.

Where is the carbon premium? Global performance of green and brown stocks

The relative equity pricing of more climate-friendly (“green”) versus less climate- friendly (“brown”) companies is an open question in climate finance. Previous research comes to conflicting conclusions, documenting either a “carbon premium” with brown stocks yielding higher returns, or the opposite, with green stocks outperforming brown. This paper provides new international evidence on this issue for a range of methodologies. Using carbon dioxide (CO2) emissions as reported by companies to measure their greenness, we document that green stocks across the G7 have generally provided higher returns than brown stocks for much of the past decade. We also try to reconcile our findings with previous work, and we provide some results for early 2022 that show that brown stocks outperformed green ones during the energy crisis.

Risk-adjusted investment performance of green and black portfolios and impact of toxic divestments in emerging markets

Environmental degradation is a global concern that warrants cooperative efforts from multiple stakeholders. In this context, responsible finance is critical to help achieve the sustainability targets and foster transition to net-zero emissions. However, to encourage green finance, investors must receive some incentives, and this paper explores if there are any benefits for the market participants. We have employed a comprehensive sample of firms from the BRICS for ten years and sorted them into black and green portfolios using multiple constructs. The comparative assessment of these portfolios shows that green stocks dominate their black counterparts, and the dominance was robust across adjusted Sharpe and Sortino ratios and Jensen's alpha. Our evidence also demonstrates that rebalancing of the portfolios due to changing ecological characteristics results in successful market timing for the green portfolios. Finally, the results suggest that the divestment of fossil fuel stocks, firms with lower environmental scores, high carbon intensity, and low sustainable revenues provide investment benefits. These findings are very encouraging for the evolution of green finance in emerging markets and have important implications for market participants.

Causality between Green Stock Market with Monetary Policy, Global Uncertainty, and Environmental Damage in Indonesia

The study examines the effect of monetary policy, global uncertainty and environmental damage on the green stock market in Indonesia in the long and short term, using the Autoregressive Distributed Lag (ARDL) bound test method. The ARDL bound test results show that there is cointegration in the long term between the green stock market and monetary policy, global uncertainty and environmental damage. Empirical evidence finds that in the long term, the variables that affect the green stock market in Indonesia are monetary policy from interest rates, global uncertainty and environmental damage from carbon emissions. While in the short term the variables that affect the green stock market are interest rates without lag, lag 1, lag 2 and lag 3; global uncertainty in lag 1 and lag 2; and carbon emissions without lag and lag 1; while forest damage without lag shows a very weak effect at the 10% significance level. Coefficient also shows significant and negative sign. A deeper analysis found that there is a bidirectional causality from monetary policy to green stock markets and vice versa, and from carbon emissions to green stock markets and vice versa.

A Bayesian analysis based on multivariate stochastic volatility model: evidence from green stocks.

Green stocks are companies environmental protective and friendly. We test Green stock index in Shanghai Stock Exchange and China Securities Index as safe-havens for global investors. Suitable multivariate-SV model and Bayesian method are used to estimate the spillover effect between different assets among local and global markets. We choose multivariate volatility model because it can efficiently simulate the spillover effect by using machine learning MCMC method. The results show that the Environmental Protection Index (EPI) of Shanghai Stock Exchange (SSE) and China Securities Index (CSI) have no significant volatility spillover from Shanghai Stock index, S &P index, gold price, oil future prices of USA and China. During COVID-19 pandemic, we find Green stock index is a suitable safe-haven with low volatility spillover. Green stock indexes has a strongly one-way spillover to the crude oil future price. Environmentally friendly investor can use diversity green assets to provide a low risk investment portfolio in EPI stock market. The DCGCt-MSV model using machine learning of MCMC method is accurate and outperform others in Bayes parameter estimation.

Dynamic spillovers and asymmetric connectedness between fossil energy and green financial markets: Evidence from China

With the purpose of risk management for fossil energy investors, this paper examines the dynamic spillover effect and asymmetric connectedness between fossil energy, green financial and major traditional financial markets in China. By employing the spillover index model of Diebold and Yilmaz, a weak correlation between green financial and fossil energy markets is verified, and the market connectedness remains relatively calm despite the COVID-19 pandemic outbreak. Specifically, green bonds receives fewer shocks from crude oil than coal, green stocks receive fewer shocks from coal than crude oil. In addition, rather than the safe-haven characteristics presented by gold, this paper further proves that green bonds also have the potential to act as safe-haven assets, due to the fact that the connectedness between green bonds and energy markets is at low levels. Finally, the magnitude of return spillovers between markets would vary significantly during different periods. The results obtained in this paper have practical implications for both investors and policymakers.

The Green Stock Market Bubble

One may contend that there are some clear similarities between the market for sustainable assets now and the situation of tech stocks right before the collapse of the dot-com bubble. In fact, before 2000, the risk of the new technology was primarily idiosyncratic because of the limited scale of production and the low likelihood of a widespread adoption. Subsequently, with an increasing probability of adoption, also, the old economy was affected by the new technology and, hence, the wealth of the representative agent. As a result, systematic risk increased, which depressed stock prices, because it pushed up the discount rates in the new and old economies. Similarly, given the high probability of a large-scale adoption of the new “green technology,” it is likely that there is not only a bubble forming in green energy stocks, but the boom is affecting the stock market as a whole. I apply a recently developed recursive testing procedure and dating algorithm that is useful in detecting multiple bubble events. Using S&P 500 stock market data, price-dividend ratios, I identify the well-known historical speculative bubbles and find an explosive movement in today’s market starting in June 2021, which can be associated with the new “green technology.” I find that an explosive movement in green stocks started roughly a year before it was migrating to the whole stock market. I argue that this is a good bubble because it will enable businesses to invest cheaply in green energy, hastening the transition away from fossil fuels and assisting in the fight against climate change.

Evidence of the fractal market hypothesis in European industry sectors with the use of bootstrapped wavelet leaders singularity spectrum analysis

The main purpose of this paper is to examine the Fractal Market Hypothesis (FMH) on family business, sustainability, shariah, green, technology, and global (all stocks) markets in European zone. By using the method of bootstrapped wavelet leaders, we found that there is strong evidence in favour of the FMH. Specifically, the analyses of singularity spectrums show evidence that family business, sustainability, technology and global markets exhibit large multifractality during the COVID-19 pandemic compared to the period prior to the pandemic. Hence, these markets became more unpredictable during the pandemic. In contrary, we found strong evidence that the green market exhibits large multifractality before the COVID-19 pandemic compared to the period during the pandemic. Thus, green market became more predictable during the pandemic compared to the period pre-pandemic period. Our findings show that in one hand the COVID-19 pandemic has significantly increased complexity in family business, sustainability, technology and global markets. On the other hand, the pandemic reduced complexity in the green market. We conclude that the green stocks traded in European zone may offer a significant opportunity for hedging portfolios during times of crisis such as the COVID-19 pandemic.