Energy Stock Research Articles

The Time-Varying Relationship Between Economic Policy Uncertainty and Returns of New Energy Stocks

With the increasing global emphasis on environmental protection, green development has become an important part of high-quality development in various countries and has stirred up enthusiasm for new energy consumption and investment. This paper uses a TVP-VAR model to analyze the dynamic effects between Chinese economic policy uncertainty, international crude oil prices, Guangdong carbon prices, and the CSI New Energy Index from July 2015 to November 2023. It turns out that they are closely linked in the short term, with obvious time-varying features in direction and magnitude. The effects of economic policy uncertainty are more persistent when extreme events occur. Finally, based on the research results, some constructive suggestions are proposed, such as establishing a risk early warning mechanism among them, improving the market system, enhancing regulatory capabilities, and promoting the development of green finance.

Akane: Perplexity-Guided Time Series Data Cleaning

Dirty data are prevalent in time series, such as energy consumption or stock data. Existing data cleaning algorithms present shortcomings in dirty data identification and unsatisfactory cleaning decisions. To handle these drawbacks, we leverage inherent recurrent patterns in time series, analogize them as fixed combinations in textual data, and incorporate the concept of perplexity. The cleaning problem is thus transformed to minimize the perplexity of the time series under a given cleaning cost, and we design a four-phase algorithmic framework to tackle this problem. To ensure the framework's feasibility, we also conduct a brief analysis of the impact of dirty data and devise an automatic budget selection strategy. Moreover, to make it more generic, we additionally introduce advanced solutions, including an ameliorative probability calculation method grounded in the homomorphic pattern aggregation and a greedy-based heuristic algorithm for resource savings. Experiments on 12 real-world datasets demonstrate the superiority of our methods.

Examining the Spillover Effects of Renewable Energy Policies on China’s Traditional Energy Industries and Stock Markets

With the development and refinement of the carbon emissions trading market, the relationship between the carbon market and the stock market has grown increasingly intertwined. This has led to a surge in research investigating the interactions between the carbon market and related sectors. This study examines the intensity and direction of spillover effects among ten industries associated with carbon emissions, spanning traditional and emerging energy sectors. Through static analysis, we find that spillover effects between industries in the carbon and stock markets are bidirectional and asymmetric. Dynamic analysis reveals that the carbon market, acting as the primary recipient of spillover effects, is notably influenced by traditional energy industries such as coal and oil, followed by photovoltaics, new energy vehicles, and others. The magnitude of these spillover effects is subject to fluctuations influenced by energy crises and events like the COVID-19 pandemic, while policy interventions can alter the overall trends in net spillover effects across various industries.

Characteristics and influencing factors of risk spillover effects across clean energy stock prices: A comparative analysis during four periods of the COVID-19 pandemic

This paper explores the characteristics and influencing factors of risk spillover effects across clean energy stock prices during four periods of the COVID-19 pandemic, using the TVP-VAR-DY model and the TVP-SVAR-SV model. The empirical results suggest that the risk spillover level across clean energy stock prices declined with the outbreak of the COVID-19 pandemic, and the volatility was initially violent. However, as the pandemic began to mitigate and recovery ensued, the risk spillover level rebounded and became stable. After the COVID-19 pandemic, smart grids and three renewable energy sources (photovoltaics, wind energy, and hydropower) were the main transmitters of net risk spillover effects across clean energy stock prices, while the clean and efficient use of traditional energy was always a net risk spillover effects absorber. Regarding influencing factors, the impact of structural factors (net power generation of various types of clean energy) on the risk spillover effect across clean energy stock prices is generally greater than that of external factors (economic factors and political factors), and these effects last longer. Finally, among structural factors, the net power generation of two renewable energy sources—wind energy and photovoltaics—has a greater impact, especially during the outbreak and mitigation period of the COVID-19 pandemic. Beyond renewable energy, the net power generation from smart grids and nuclear power had a significant impact during the post-COVID-19 recovery period. These new findings suggest useful implications for investors and policymakers in the clean energy markets.

Measuring the impact of climate risk on renewable energy stock volatility: A case study of G20 economies

The contemporary world faces significant challenges in energy crises and climate change. To analyze the relationship between energy and climate, we explore the influence of the climate-related attention of G20 countries on renewable energy stock volatility forecasting under the framework of the extended GARCH-MIDAS model. In the context of COP26, we further adopt natural language processing technology and shrinkage approach to obtain Google search volume for 107 climate-related keywords and then construct new climate risk attention indicators. The in-sample parameter estimation results show that the climate attention of G20 countries has a remarkable positive effect on the renewable energy stock market volatility. The out-of-sample results demonstrate that the climate attention of different countries exerts varying influences on the volatility of the renewable energy stock market. Climate risk and energy issues are among the serious challenges facing the 21st century, and reducing greenhouse gas emissions and finding cleaner energy is an urgent task. As the response to climate change necessitates diverse strategies in various countries, our research can offer valuable guidance and serve as a reference for national energy transitions and the selection of alternative energy solutions.

Research on the assessment of technical methods to suppress auger recombination

Human demand for fossil fuels has reached a very high level. However, fossil energy stocks are limited and, more importantly, their impact on the environment is increasing. The exploration of clean energy is particularly important. Among all the clean energy sources, solar energy is a very promising and important alternative to fossil fuels. And one of the primary reasons for the failure of solar photovoltaic cells to achieve rapid development is the generation of Auger composite. In order to provide support to solve this problem or facilitate the follow-up of researchers, this paper summarizes several effective methods such as Interfacial Engineering and Gradient Alloying to solve the Auger recombination problem in multi-exciton photovoltaic cells through reading and comparing a large number of relevant authoritative literature. The two methods mentioned above suppress Auger recombination by applying a new type of MXene (Nb2CTX-MXene) to the interface of SnO2 layers to pssivate the interfacial defects and promote charge transport and to generate InAs/CdSe core/shell QDs, overcoating InAs QDs with a lattice-matched CdSe shell. Comparing a large number of pieces of literature, it is found that the above two methods have guiding effects in improving the efficiency of photovoltaic cells.

Side Effects and Interactions: Exploring the Relationship between Dirty and Green Cryptocurrencies and Clean Energy Stock Indices

This study aimed to assess whether renewable energy cryptocurrencies such as Cardano (ADA), Ripple (XRP), IOTA (MIOTA), and Stellar (XLM) can be considered hedging assets and safe havens for cryptocurrencies classified as "dirty", such as Bitcoin Cash (BCH), Bitcoin (BTC) Litcoin (LTC), Ethereum (ETH), Ethereum Classic (ETC) and the clean energy stock indices WILDERHILL Clean Energy (ECO) and Clean Energy Fuels (CLNE), from July 6, 2018, to July 6, 2023. The results show that the movements decreased significantly during the Stress period, which includes the events of 2020 and 2022. The Cardano cryptocurrency shows moderate movements, indicating stability and diversification, while Stellar shows moderate movements that suggest resilience. Conversely, XRP shows varied movements, requiring some caution, while IOTA stands out for significant movements associated with sustainable assets. These results interest players operating in these markets when they want to diversify and rebalance their portfolios.

Evidence on Price Formation In Financial Markets: A Multitemporal Analysis

Background: Although clean energy stocks have become a popular new asset class for market players, relatively little research has been done on risk management strategies for investors in clean energy stock markets. Gold and Silver are examples of precious metals typically considered suitable investments to hedge against uncertainty. Therefore, their demand tends to rise when stock markets decline. Purpose: The study aims to analyse the influence of precious metals (Gold, Silver and Platinum) and green stock indices (Clean Energy Fuels, Nasdaq Clean Edge Green Energy, S&P Global Clean Energy, WilderHill Clean Energy) on price formation during different economic periods between 1 January 2018 and 23 November 2023. Methods: The periods analysed were Tranquil, 2020 pandemic, pre-conflict and Conflict (Russian invasion of Ukraine). To this end, a VAR Granger Causality/Block Exogeneity Wald model was estimated to identify different influence patterns during each period. Results: During the Tranquil period, 15 movements affecting prices were observed, with Silver significantly influencing all its peers, while Gold impacted Platinum, S&P Global, Nasdaq and WilderHill. Platinum was the asset that received the most shocks from its peers. During the 2020 pandemic, there was an increase to 26 movements, with the S&P Global and Nasdaq Clean indices influencing most of their peers. Gold and Platinum continued to be the assets most influenced by their peers. In the pre-conflict period, 11 movements were identified, with the highlight being the mutual influence between Gold, the Nasdaq and WilderHill indices, and Platinum. During this period, Silver and S&P Global only affected the price formation of Platinum and Clean Energy Fuels, respectively. During the Conflict period, 18 movements were observed, highlighting the influence of Platinum and S&P Global on the price formation of various assets. Gold was the asset that received the most shocks from its peers during this period. Conclusion: the results indicate changes in the interactions between assets throughout the different economic contexts, highlighting the importance of understanding these dynamics to make more informed decisions.

Measurement of daily climate physical risks and climate transition risks faced by China's energy sector stocks

This paper introduces a novel approach for assessing the daily climate transition risk level in China and quantifying the climate physical risk associated with various fossil energy stocks. These measurements offer valuable data sources for empirical research in this field. In assessing climate transition risk, this paper employs the Term Frequency-Inverse Document Frequency (TF-IDF) method to construct a glossary of China's climate transition terminology. It also utilizes the multi-scale moment difference method to evaluate China's daily climate transition risk from 2000 to 2022. Climate physical risk measurement primarily focuses on boundary projection and base period shifting. The analysis reveals that: (1) China's climate policy documents emphasize areas such as energy conservation, meteorology, renewables, low-carbon solutions, and carbon emissions. Notably, meteorology-related provisions, including those for typhoons, rainfall, and drought, indicate heightened government attention to climate disaster response. (2) The research identifies periods of increased climate transition risk levels in 2004–2008 and 2017–2019, with decreases in 2011–2015 and 2020–2022. (3) The distribution of climate physical risk levels in China's fossil energy stocks is right-skewed, with the range [0.86, 0.88] representing the predominant distribution interval and concentration of these risks. The findings of this study can assist policymakers and investors in making informed decisions for market management and investments based on climate risk scenarios.

Global evidence on the Russia–Ukraine conflict and energy stock returns

Using the event-study and difference-in-differences approaches, this paper examines the impact of the Russia–Ukraine conflict on the stock returns of alternative energy and oil & gas producers from 48 countries. We focus on multiple critical events from the beginning of the invasion through eight months into the conflict. Our empirical results indicate that renewable energy and oil & gas producers performed better than the general stock market. Oil & gas producers generated greater returns when compared with alternative energy firms, especially at the beginning of the conflict. The gap in stock returns between the two groups of energy producers shrank significantly as the conflict progressed. Particularly in Europe, later stages of the conflict witnessed greater alternative energy stock returns than oil & gas ones. A further examination of the index returns for the segment of well-established energy firms reveals that renewable indices performed better then oil & gas indices in every critical phase of the conflict. Finally, we show that the stock returns of renewable energy equipment manufacturers also exceeded those of oil & gas equipment producers during the crisis. Overall, our results indicate investors’ optimism about the prospect of green energy following the Russian invasion of Ukraine.

Portfolio risk and return between energy and non-energy stocks

This paper aims to examine the potential for portfolio returns by adding together conventional and energy stocks with varying proportions. We examine the risk and return characteristics of a portfolio comprising energy and non-energy stocks from twenty countries. The period for daily data ranges from 2nd July 1999 to 2nd July 2021. We use multiscale Sharpe and VaR ratios to examine the risk and returns behaviour of a portfolio with varying composition between energy and non-energy stocks across different investment periods. Our results highlight optimal returns for the equally weighted portfolio during normal and crisis periods except COVID-19 during which more proportion of conventional stocks is preferred. Risk estimates advocate an equally weighted portfolio for all periods however risk varies with the holding period. These results carry useful investment implications during short- and long-run holdings of conventional and energy stocks in a portfolio.

Bacterial-Polyhydroxybutyrate for Biocompatible Microbial Electrodes

The development of bioelectrochemical systems requires careful selection of both their biotic and abiotic components to obtain sustainable devices. Herein, we report a biophotoelectrode obtained with polyhydroxybutyrate (PHB), a biopolymer, which purple non-sulphur bacteria produce as an energy stock under specific environmental conditions. The electrode was obtained by casting a mixture composed of PHB and carbon fibers in a 3:2 mass ratio. Following, the composite material was modified with polydopamine and thermally treated to obtain a hydrophilic electrode with improved electrochemical behavior. The bio-based electrode was tested with metabolically active cells of Rhodobacter capsulatus embedded in a biohybrid matrix of polydopamine. The system achieved enhanced catalytic activity under illumination, with an 18-fold increase in photocurrent production compared to biophotoelectrodes based on glassy carbon, reaching a current density of 12 ± 3 μA cm−2, after 30 min of light exposure at +0.32 V. The presented biocompatible electrode provides a sustainable alternative to metal-based and critical raw material-based electrodes for bioelectrochemical systems.

Pricing behavior of clean energy stocks? Some trading implications

Mispricing and price adjustment to shocks are common features of stocks, which arise due to various types of shocks. Understanding mispricing and price adjustment mechanism can guide trading strategy design. Our hypothesis is that clean energy stocks are characterised by mispricing and that there are unique stocks in the sense that they move first when exposed to shocks. We employ a price discovery model to rank clean energy stock indices in terms of those that adjust to prices faster than those that do not. We then identify mispricing in those stocks using a market risk factor model. Utilizing time-series data on 11 clean energy stock indices, we propose eight trading strategies, and show that they offer annualized returns in the −5.37% to 61.10% range. Six of the eight strategies offer profits close to 15% or more, beating the buy and hold strategy. Trading strategies devised on mispricing suggest that two of the clean energy stocks can potentially beat the buy-and-hold strategy, offering annualized returns in excess of 13%. Because our results guide investors towards making profits from trading clean energy stocks, the implication is that the trading strategies can enhance the green finance market.

Dynamic interplay between Chinese energy, renewable energy stocks, and commodity markets: Time-frequency causality study

In this study, we explore the interconnections among Chinese energy stocks, renewable energy stocks, and commodity markets by employing time-frequency connectedness and causality-in-quantiles methodologies. This research contributes to the existing body of literature by scrutinizing the time-varying causal relationships between Chinese energy/renewable energy stocks and commodity markets. Utilizing data spanning from January 2011 to April 2023, we discover that while the energy stock market typically exhibits susceptibility to external influences over the long term, it plays a contributing role in the short term. Notably, during the COVID-19 period, there were more pronounced long-term repercussions across the markets. Furthermore, the influence of specific markets has undergone changes; for instance, petrochemical stocks exert a significant impact on commodity markets, whereas renewable energy stocks exhibit minimal influence. Insights derived from quantile causality analysis underscore the predictive utility of stock markets in forecasting the movements of commodity markets across a broad quantile of commodities.

Investment Portfolio Optimization in Renewable Energy Stocks in Indonesia Using Mean-Variance Risk Aversion Model

Climate change is a phenomenon that has been occurring for quite some time. However, the increasingly felt impacts of climate change necessitate human action to mitigate these effects. One way to address this issue is by transitioning from conventional or non-renewable energy sources to renewable energy. This step undoubtedly has implications for various aspects, such as investments. Naturally, investors are beginning to turn their attention to the field of renewable energy as a new target. Investments are inherently associated with risks and returns One approach to maximizing returns is through portfolio optimization. One well-known method in portfolio optimization is the Mean-Variance method, also known as the Markowitz method, as it was first introduced by Harry Markowitz. In this research, an optimal portfolio is generated with weights of 0.1470 for ADRO; 0.1939 for MEDC; 0.2143 for ITMG and 0.4449 for RAJA. With this composition of optimal portfolio weights, the expected return is obtained at 0.002252, and the return variance is 0.000496.

Portfolio management of ESG-labeled energy companies based on PTV and ESG factors

This paper evaluates monthly quartile portfolios of ESG-labeled companies constructed based on their Prospect Theory Value (PTV) and ESG scores in the closely monitored energy sector. Investing in ESG-labeled energy stocks can outperform a value-weighted global energy sector index, according to several out-of-sample performance analyses. The PTV strategy stands out over a sample period of more than twelve years. This strategy performs similarly to a fully diversified world market index and consistently outperforms a world energy index. Over the last five years, the simple strategy based on ESG scores performs similarly to the PTV strategy.

Liquidity of Non-US and Energy Stocks Listed on the NYSE in the Aftermath of the Fukushima Daiichi Nuclear Incident

In this paper, we investigate the impact of the Fukushima Daiichi nuclear incident on the liquidity of non-US stocks in the Asia-Pacific region, specifically those listed on the New York Stock Exchange (NYSE). The Fukushima Daiichi nuclear incident occurred in March 2011, following a severe earthquake and tsunami in Japan, and its consequences have extended beyond the borders of Japan. Our study shows that non-US stocks from Japan are associated with significantly wider spreads and higher price impacts. Additionally, we find a similar negative liquidity effect for energy stocks listed on the NYSE and stocks from neighboring countries such as China and South Korea, primarily due to geographic proximity. However, we do not observe any significant changes in the liquidity of stocks from the remaining Asia-Pacific countries. Furthermore, we examine the duration of this negative shock and observe that the illiquidity of stocks from Japan persists for over three weeks. In contrast, the liquidity of energy stocks and stocks from China and South Korea recovers within one week following the incident.

The Impact of ESG Performance of Energy Enterprises on Stock Value

ESG, as an increasingly important evaluation indicator for today's enterprises, is being widely used. This article aims to study the relationship between ESG performance in the energy industry and stock value. This article takes the data of energy companies listed in the Shanghai and Shenzhen A-share markets from 2015 to 2022 as samples, controls for two variables: energy type and industry profitability, and uses the P/E ratio estimation method for analysis. Research has found that energy companies with environmental friendliness, high social reputation, and good management practices have higher stock prices, making them more likely to be favored by investors. The relevant research in this article can effectively help investors optimize their decision-making by analyzing the ESG situation when choosing the energy industry. At the same time, this study can provide some development insights for new and traditional energy enterprises.

Political ratings, government quality, and liquidity: evidence from Non-U.S. energy stocks listed on the NYSE

Political ratings, government quality, and liquidity: evidence from Non-U.S. energy stocks listed on the NYSE

Asymmetric impacts of coal prices, fintech, and financial stress on clean energy stocks

The emergence of fintech has revolutionized financial systems, alleviating financial stress through innovative solutions and diversification. This shift towards clean energy stocks has reduced demand for coal, impacting coal prices significantly and highlighting the pressing need to preserve mineral resources for sustainable, cleaner energy alternatives. Therefore, the study examines the interconnectedness between coal price, fintech, financial stress, and green energy stock using quantile-based regression. The findings reveal that the impact of coal price, fintech, and financial stress on the clean energy stock is heterogeneous across all levels of quantiles. Specifically, the findings indicate that variations in the coal price positively influence the clean energy stock index, yet this association displays asymmetry across quantiles. Fluctuations in the fintech index contribute to the susceptibility of renewable energy stock prices. The financial stress index exhibits a consistently adverse influence on clean energy stock across quantiles ranging from lower to higher orders. The study findings would guide stock market investors, ecological activists, and policymakers at administrative levels aiming to promote clean energy investment while controlling for the adverse outcomes from financial stress.