Energy Exchange Traded Funds Research Articles

Delving into the Exchange-Traded Funds (ETFs) Market: Understanding Market Efficiency

Exchange-traded funds (ETFs) are the most popular products in the financial sector today. There is extensive literature on the multifractal analysis of some stock markets, but not about the multifractal behaviour of the ETF market. This study examines the efficiency of stock index ETFs worldwide from an Efficient Market Hypothesis (EMH) perspective, using the ETFs: Ishares Msci World ETF (URTH), Ishares Russell 1000 ETF (IWB), SPDR S&P 500 ETF TRUST (SPY), Ishares Global Clean En. ETF (ICLN), Ishares USD Green Bond ETF (BGRN), from 1 January 2021 to 24 May 2024. It analyses a pre-conflict and a geopolitical conflict to uncover distinct patterns of behaviour reflecting significant changes in market conditions. Before the conflict, the Ishares MSCI World, Ishares Russell 1000, SPDR S&P 500 and Ishares USD Green Bond ETFs showed signs of anti-persistence in returns, indicating a lack of strong relationship or predictability between short-term price movements. The Ishares Global Clean Energy ETF did not reject the random walk hypothesis, suggesting that returns follow a pattern closer to random, where market prices already efficiently reflect all available information. During the conflict, there was a transition in the ETFs' behaviour patterns, as evidenced by the increases in slope values for Ishares MSCI World, Ishares Russell 1000, SPDR S&P 500, Ishares Global Clean Energy and Ishares USD Green Bond. Thus, the possible transition from anti-persistence to long-term memories in ETF returns during the conflict. For portfolio managers, these findings highlight the need to continually adapt investment strategies to manage risks better and take advantage of opportunities in a dynamic and complex investment environment.

Portfolio diversification opportunities in traditional energy and alternative/renewable energy ETF segments

"This study evaluates the diversification benefits of investing in traditional and alternative/renewable energy Exchange Traded Funds (ETFs) using the VAR-ADCC-GARCH model to analyze yields, correlations, and volatilities. The results demonstrate that alternative/renewable energy ETFs not only offer higher average returns but also significantly reduce portfolio risk compared to traditional energy ETFs. The research underscores the distinct investment dynamics between the two ETF segments, highlighting the advantages of incorporating renewable energy assets into diversified portfolios. These findings support the inclusion of environmentally-conscious investment strategies that effectively balance risk and return, emphasizing their importance for investors aiming to optimize their portfolios in line with sustainable practices. Keywords: portfolio diversification, ETFs, traditional energy, renewable energy, VAR-ADCC-GARCH Model JEL classification: G11, C58, A100, A110"

ESG, clean energy, and petroleum futures markets: Asymmetric return connectedness and hedging effectiveness

This study investigates the asymmetric return connectedness and portfolio implications among environmental, social and governance (ESG) exchange-traded funds (ETFs), clean energy ETFs, and five petroleum futures markets from December 2016 to December 2022. To this end, it uses an asymmetric time-varying approach of connectedness and constructs portfolios using minimum variance portfolio (MVP), minimum correlation portfolio (MCP), and minimum connectedness portfolio (MCoP). The results show that negative return connectedness is stronger than positive ones across most of the sample period, especially around the peak of the COVID-19 pandemic. The dynamic of net connectedness between markets is altered by the pandemic. ESG ETFs are more connected to petroleum futures markets than clean energy ETFs. The connectedness is strong during the COVID-19 outbreak, which suggests the instability of the system of return connectedness during the global health crisis. The minimum connectedness portfolio approach reflects the asymmetric and non-asymmetric return connectedness more than other portfolio approaches. Notably, clean energy and ESG ETF exhibit a safe-haven property under both symmetry and asymmetry in return connectedness. The findings are insightful from investment and policy perspectives.

Climate Change and Volatility Forecasting: Novel Insights from Sectoral Indices

This study investigates the impact of climate policy uncertainty (CPU) on sectoral indices and clean energy exchange-traded funds (ETFs) by using a GARCH-MIDAS model. The stock indices include renewable energy (NEX), transportation, mining, industrial, real estate, green economy US, green economy Europe, green economy Asia index, and ETFs clean energy (PBW), global clean energy (PBD). The research also evaluates the forecasting power of uncertainty factors, including equity market volatility (EMV), economy policy uncertainty (EPU), trade policy uncertainty (TPU), fiscal policy uncertainty (FPU), global economy policy uncertainty (GEPU), and geopolitical risk (GPR), to predict the volatility. We obtained some notable results. First, the out-of-sample findings show that CPU index information is useful to predict the volatility of the NEX renewable energy, green economy US, transportation, energy index for the US, and clean energy (PBW), global clean energy (PBD) ETFs. Second, EMV, EPU, and GPR also contain valuable information for the real estate, industrial, energy, and NEX renewable energy index. Additionally, we find evidence during low and high volatility and upheaval of the COVID-19 pandemic. The Roos2 square and model confidence set (MCS) tests verify each model's out-of-sample forecasting performance.

Are clean and black energy exchange-traded funds driven by climate risk?

ABSTRACT This research paper analyzes the connectivity and spillover effects of climate uncertainty policy in exchange-traded funds (ETFs) on clean and black energy. Using monthly data for the period from July 2008 to August 2022, the cDCC-GARCH model and the Diebold and Yilmaz index model approach were applied, revealing connectivity between clean and black energy assets, as well as between these and climate risk, with the latter producing a positive effect on the returns of clean energy assets, contrary to what happens in black energy counterparts. Our results also show that in phases of high climate uncertainty, clean energy assets can help hedge the risk of the black energy segment. In phases of financial turbulence, namely those corresponding to the pandemic crisis and the war in Ukraine, there was a marked intensification in the information transmission processes, giving rise to closer patterns of behavior by the assets studied.

The Efficiency of Alternative and Conventional Energy Exchange-Traded Funds: Are Clean Energy Exchange-Traded Funds a Safer Asset?

This paper examines the efficiency of alternative energy equity Exchange-Traded Funds (ETFs) and conventional energy equity ETFs from 2018 to 2020, utilizing a combination of an output-oriented Slack-Based Data Envelopment Analysis (DEA) model and cluster analysis. In the context of an output-oriented DEA model, efficiency is defined as the ability of an ETF to maximize its outputs (annualized average return; environmental, social responsibility, and corporate governance; and net asset value) given a fixed level of inputs (expense ratio and beta). The findings indicate that alternative energy ETFs have the potential for long-term outperformance compared to conventional energy ETFs in terms of efficiency. However, during financial crises, the performance differences between the two types of ETFs diminish, with no significant outperformance observed in either category. The expense ratio and net asset value are identified as key factors influencing the efficiency of both ETF types. Additionally, social and governance metrics have a notably stronger positive impact on conventional energy ETFs relative to alternative energy ETFs, highlighting the increasing significance of these factors in financial asset performance.

Dynamic conditional correlation between green and grey energy ETF markets using cDCC-MGARCH model

ABSTRACTUsing the cDCC form of the multivariate GARCH models (MGARCH), this paper examines the time-varying conditional correlations among green renewable, grey non-renewable, and the conventional investment strategy in the exchange-traded funds (ETFs) markets. Daily excess returns for the largest energy ETFs are used as proxies for the US energy sector over the period of 25 June 2008 to 9 May 2023. The empirical results find that the AR(1)-GARCH(1, 1)-cDCC model with t-distribution to be the best fit. The results indicate that the time-varying correlations between green and grey energy ETFs are between 0.42 and 0.55 and statistically significant at 10%, with lesser degree of persistence in green energy, while there is a high significant co-movement between the grey energy and the traditional investment strategy. This, in turn, implies that investing in green energy ETFs provides better diversification. These results provide important implications for policymakers, portfolio managers and investors on the benefits of portfolio diversification in energy markets amid the current global energy crisis.

Price discovery in carbon exchange traded fund markets

In this study, we analyze the price discovery in four carbon exchange-traded funds (ETF) markets: (i) VanEck Low Carbon Energy ETF (Vaneck), (ii) iShares MSCI ACWI Low Carbon Target ETF (iShare), (iii) SPDR MCSI ACWI Climate Paris Aligned ETF (SPDR), and (iv) Xtrackers Emerging Markets Carbon Reduction and Climate Improvers ETF (Xtrackers) using daily closing prices of the four carbon ETFs from December 6, 2018, to November 30, 2022. All four ETF prices are found to have a single unit root implying the efficiency of these ETF markets (LeRoy 1989). However, Johansen's (1991) cointegration test reveals that these four ETFs are driven by not one but three common stochastic trends. Further Analysis reveals that iShares and SPDR markets are driven by the same market force (common stochastic trend). Based on the generalized information share (GIS), we find that approximately 57.89% and 42.11% of the price discovery occurs in the iShares and SPDR markets, respectively. We further analyze the impact of the COVID-19 pandemic by dividing the whole sample into pre-COVID and COVID subsamples. In the pre-COVID period, the GIS measures for the iShares and SPDR are 88.69% and 11.31%, respectively. However, GIS measures for the iShares and SPDR are 1.04% and 98.96%, respectively, in the COVID period indicating a significant impact of COVID-19 on price discovery.

Performance of renewable and non-renewable exchange-traded funds during heightened uncertainty

ABSTRACT This study adopts a composite threshold model that differentiates between the upside and downside betas of the major US-based renewable and non-renewable exchange-traded funds (ETFs) during heightened uncertainty. It is found that downside betas for both renewable and non-renewable energy ETFs are significantly greater than upside betas. However, in a highly uncertain market, renewable energy ETFs tend to enjoy higher upside gains than the fossil-fuel ETFs. The results suggest that renewable energy ETFs have great potential to generate high returns, but the downside risk associated with renewables should be mitigated by government incentivizing the use of renewables in both domestic and foreign markets. Investing in renewable energy is not only good for the environment but also compared to other investment alternatives (including fossil fuels) it provides better risk-adjusted returns. During the last 5 years, some renewable energy ETFs have even outperformed several well-established sectoral ETFs. This paper finds that there is a more favourable business case for investing in renewables than common perception would suggest.

Evaluating the performance of energy exchange-traded funds

Evaluating the performance of energy exchange-traded funds

Effects of Temperature Rise on Clean Energy-Based Capital Market Investments: Neural Network-Based Granger Causality Analysis

During the past 20 years, due to climate change, the government and the private sector have significantly focused on relying on non-fossil fuel-based methods for their energy needs. Climate change-related events, such as unusual weather conditions, abnormal temperature spikes, etc., have an adverse influence on clean energy-based investments. In the given study, we intend to focus on how an incremental temperature rise could affect investors’ perceptions of clean energy assets. To understand the investor-based sentiment on climate change, we utilize prominent clean energy ETFs (exchange traded funds) and consider the temperature’s effect on them. The daily average temperatures of the three most dynamic international financial centers: New York, London and Tokyo, are taken as predictors. Deep learning-based neural networks are applied to understand both the linear and non-linear relationships between the desired variables and identify the causal effects. The results indicate that in almost all the cases with desired lags, there is some sort of non-linear causality, irrespective of linear causality effects. We hope this occurrence can help portfolio managers and environmental professionals in identifying novel climate change-related factors when considering the temperature-related risks.

Geopolitical risk and renewable energy asset prices: Implications for sustainable development

This study intends to investigate the impact of geopolitical uncertainty, proxied by the geopolitical risk (GPR) index, on the volatility of renewable energy exchange traded funds (ETFs). Employing a two-state Markov regime switching model reveals that an upturn in the GPR index increases (reduces) the likelihood of being in the low (high) volatility regime. This finding could be attributed to the fact that when the geopolitical risk increases, users of crude oil, which is highly sensitive to such risk, tend to consider clean energy as a substitute for traditional energy sources. This causes a growth in the equity prices of new energy firms, further leading to a drop in the levels of volatility. Additionally, the results of generalized autoregressive conditional heteroscedasticity (GARCH) models also confirm that higher GPR implies lower risk for these green assets. The outcomes have implications to policymakers and investors participating in clean energy markets.

Going beyond sustainability: The diversification benefits of green energy financial products

After the inclusion of Green energy financing in the list of United Nations Sustainability Goals (SDGs) as SDG 7, the role, importance, and visibility of green financial products; all have escalated enormously. This paper assesses the utility of green exchange-traded funds (ETFs), in the investors' portfolios for their dual potential of sustainability and diversification. ETFs provide a unique opportunity to construct practically investible portfolios and have long been used as conduits to facilitate project financing. In this paper, we use distinct ETFs based on dirty (conventional) and clean (green) energy products and companies, bonds, equity, ex-energy commodity, and real estate markets to examine the diversification benefits of green energy for a US-based investor. We construct efficient frontiers under different asset allocations and diversification strategies using the Markowitz MVO framework. Our results show that green energy ETFs provide significant diversification benefits and move the efficient frontier upward. In contrast, the portfolio performance deteriorates with dirty energy funds under different asset allocation and diversification strategies. Overall, we find that owing to their risk-return profile, green energy ETFs can be a rewarding alternative to dirty energy for investors in the global energy market.

Is green investment different from grey? Return and volatility spillovers between green and grey energy ETFs.

Investment in Green energy is becoming a popular alternative asset class for investors, primarily due to its environment-friendly attributes. However, there is a dire need for subjective evaluation of this emerging asset class based on the risk-return dynamics to which investors are exposed. To respond to this call, in this study, we conduct this evaluation utilizing a unique and rich data set consisting of daily prices of exchange-traded funds (ETFs) established on different asset classes. We use Vector autoregression and Baba-Engle-Kraft-Kroner parameterization of multivariate GARCH models and assess the relative strength of return and volatility spillovers from the Green and Grey energy markets. Our results reveal the return shocks originated in the Green energy market and transmitted to other markets are more pronounced. It is also observed that the potential to earn high returns and the weak correlation of Green energy ETFs with the traditional asset classes are the crucial factors helpful in inviting attention and investment of investors after 2015. Although our results further suggest that the role of Grey energy is diminishing, as shown by the Impulse response functions and the coefficients of multivariate ARCH and GARCH. Nonetheless, for some asset classes, e.g., Bonds, the volatility spillovers that originated in the Grey energy market are still prominent and robust.

Impact of energy sector volatility on clean energy assets

We study the effect of uncertainty in energy sector firms, as reflected in the information in the energy sector implied volatility index (VXXLE), on clean energy exchange traded funds (ETFs). Unlike the existing literature that mainly employs linear models to study the association between clean energy and financial markets, we apply the Markov regime switching process to uncover the impact of the VXXLE on clean energy ETFs during high and low volatility regimes. Our findings reveal a negative impact, suggesting that, when implied volatility levels are high for energy sector firms, a drop is likely in clean energy asset returns. The results also show evidence of an asymmetric effect. During high volatility regimes, the association between the VXXLE and clean energy ETFs holds stronger than in low volatility regimes. These results remain unchanged controlling for the effects of oil prices, crude oil volatility, and technology stock prices. We further document that changes in levels of the VXXLE substantially impact the realized volatility of clean energy ETFs. Our findings have significant implications for investors and policymakers.

Are alternative energies a real alternative for investors?

Fossil fuels supply most of the energy we need for many functions but alternative energy global consumption is expected to increase in the future supported by great incentives, advances in technologies, and the depletion of fuel oil reserves. In that context, investors begin to consider the possibility of investing in the alternative energy sector using different assets such as the Exchange Traded Funds (ETFs). We evaluate the out-of-sample performance of four strategies using the returns and volatility forecasts from a VAR-ADCC approach. We provide evidence that Alternative Energy ETFs clearly outperform Energy ETFs and, therefore, they are a real alternative for investors. These findings are relevant not only for academics but also for active professional managers who can use this technique to add value to their investment strategies.

Clean energy investing in public capital markets: Portfolio benefits of yieldcos

Deployment of clean energy technologies in order to mitigate climate change requires large-scale mobilization of capital markets. Investors’ perceptions that renewable energy investments do not deliver attractive returns compared with conventional alternatives can impede the flow of sufficient capital to finance these requirements. This paper examines whether publicly-traded financial products offer investors competitive risk-adjusted returns, or whether renewable energy investors face a penalty for choosing sustainable assets. We use a traditional portfolio approach to test whether adding renewable energy exchange-traded funds (ETFs) to a standard portfolio provides diversification benefits over a period of study of two, six, and nine years. We also examine the benefits of investing in yieldcos, which hold operational renewable energy assets. We find that the renewable energy ETFs provide only minimal diversification benefits, and that a yieldco index fund provides none. However, given the superior performance demonstrated by yieldcos based outside the US, we repeat the optimization using a constructed index featuring non-US yieldcos, and find that it improves Sharpe ratio. The analysis suggests that public investment in renewable energy can be profitable, but existing vehicles may not be managed properly to deliver their true benefit. In particular, the non-US yieldco model demonstrates better performance and offers portfolio benefits that are not matched by US yieldcos.

Latent Volatility Granger Causality and Spillovers in Renewable Energy and Crude Oil ETFs

The purpose of the paper is to examine latent volatility Granger causality for four renewable energy Exchange Traded Funds (ETFs) and crude oil ETF (USO), namely solar (TAN), wind (FAN), water (PIO), and nuclear (NLR). Data on the renewable energy and crude oil ETFs are from 18 June 2008 to 20 March 2017. From the underlying stochastic process of a vector random coefficient autoregressive (VRCAR) process for the shocks of returns, we derive Latent Volatility Granger causality from the Diagonal BEKK multivariate conditional volatility model. We follow Chang et al. (2015)’s definition of the co-volatility spillovers of shocks, which calculate the delayed effect of a returns shock in one asset on the subsequent volatility or co-volatility in another asset, and extend the effects of the co-volatility spillovers of shocks to the effects of the co-volatility spillovers of squared shocks. The empirical results show there are significant positive latent volatility Granger causality relationships between solar (TAN), wind (FAN), nuclear (NLR), and crude oil (USO) ETFs, specifically significant volatility spillovers of shocks from solar ETF on the subsequent wind ETF co-volatility with solar ETF, and wind ETF on the subsequent solar ETF co-volatility with wind ETF. Interestingly, there are significant volatility spillovers of squared shocks for the renewable energy ETFs, but not with crude oil ETFs.

To trust or not to trust? A comparative study of conventional and clean energy exchange-traded funds

In this paper we examine the performance of portfolios of energy-related ETFs, under periods of market turmoil and market uptrend, using groups of clean or conventional energy ETFs. We examine seven popular quantitative investment strategies for constant assets rotation, evaluate their performance with appropriate return and risk measures, and control of the robustness of their performance with different sets of parametrizations. The impacts of the 2008 financial crisis and the 2014 collapse in oil prices, as well as the interaction with exogenous to the energy industry ETFs are explored. We find that one portfolio of ALL ETFs in aggregate outperform two disaggregated portfolios with clean and conventional ETFs separately. We discuss the potential implications both from the perspective of potential investors but also on the potential on the future growth of clean energy related class of assets

Measuring the Market Efficiency of Energy Exchange-Traded Funds (ETFS)

This paper examines the market efficiency of Energy Exchange-Traded Funds (ETFs) of both renewable and unrenewable energy ETFs. We adopt GARCH modelling approach to investigate the long-range dependence in ETFs volatility. Specifically, we estimate a FIGARCH model proposed by Baillie et al. (1996) using daily returns. We find evidence of long memory dependence in all ETFs, implying that, all the indexes under investigation are weak-form inefficient. The results also indicate that the volatility has a predictable structure in all the ETFs of both renewable and unrenewable energy ETFs, indicating the potential of diversification for the international investors.