Applications in Energy Finance

This paper surveys the recent development in energy finance, a booming inter-disciplinary subject of research. By looking back to the history of its development, we aim to clarify the conceptual issues and try to summarize the current research streams of this subject. The survey starts from financialization in energy markets, making use of the most recent empirical evidence and theoretical arguments to revisit the relationship between energy and financial markets. Corporate finance issues in energy sector are another main stream of research, which is based on the assumption that energy firms are different. A new direction of research is on green finance and investment, mainly related to financing, investment and governance in energy transition process. Through the survey, we show that energy finance is a promising research subject, and there are many exciting topics worth further investigation.

This study takes into account two previously neglected issues when analyzing the relationship between oil prices and effective dollar exchange rates. We distinguish between demand and supply side dynamics and the role of time-variation in terms of in-sample and out-of-sample results. While we find robust evidence for a long-term link between the price of oil and exchange rates, we are unable to identify systematic forecasting ability in either direction. We also find that a potential link between long-run relationships and out-of-sample predictability is changing over time and discuss avenues for further research.

The aim of this paper is to examine the relationship between exchange rates, real stock returns, crude oil prices, and industrial production levels for emerging countries. Toda Yamamoto Augmented VAR for Granger non-causality methodology is implemented to determine the linkages and make inferences about the results. Monthly data is used covering the period between January 1990 and December 2016 to determine the direction of the causality between variables. Our results show that there exists a significant causal relationship between production and crude oil prices. It is also observed that causality from exchange rates to manufacturing indices can be used to explain the economic dynamics of emerging countries. Weak causal linkage from stock market returns to industrial production is found for emerging countries, and it is unidirectional.

Credit markets play a crucial role in the propagation of shocks through an economy. Both economic uncertainty and oil market shocks transmit through credit markets to various sectors of an economy. However, the transmission of the shocks depends on the state of an economy as crises periods behave quite differently  from normal times. We use a nonlinear vector autoregressive (VAR) model to study the transmission of uncertainty and oil market shocks using monthly data over the 1986:M1–2021:M1 period. The nonlinear VAR model allows the transmission of uncertainty and oil market shocks to a change during financial distress periods. We find that economic uncertainty is closely related to financial conditions and transmission dynamic change during financial crises. Uncertainty shocks are recessionary with a stronger effect during financial distress. Oil supply shocks associated with increasing oil prices are also recessionary and stronger during financial distress while positive demand shocks are expansionary. We find strong asymmetry in responses of macroeconomic aggregates across financial regimes and signs of the shocks.

We introduce an approach to trace the genesis of contagion occurring in the oil-finance nexus, which consolidates veteran non-linear oil price measures derived from the empirical oil literature, to construct a rule-based specification for filtering structural oil market shocks into calm and extreme episodes. Such identified conditions are useful to understand how changing scenarios in the international crude oil market influence the dynamic relationships between the crude oil, exchange rate, and stock markets. As we are the first to explicitly consider how the relationship between the exchange rate and stock market change under extreme oil market shocks, our applications to a small emerging oil-exporter provide novel results about this particular linkage. We find that the positive supply shocks and negative demand shocks associated with the 2014/2015 oil price crash coincide with a marked increase in the inverse exchange rate-stock market relationship. This highlights the importance of including exchange rates when analysing the dependence between oil and stock markets. Our results also show that international financial crises, such as the Asian flu and dot-com crash, are episodes of contagion in an otherwise weak oil-stock market relationship. In addition, we provide findings which are consistent with previous empirical literature that extreme demand-side oil market shocks tend to dominate the absolute increase in cross-market linkages and that the 2008/2009 global financial crisis is the most prominent contemporary event in the oil-finance nexus in a pre-COVID-19 world.

We investigate volatility contagion across G7 stock markets and the market for crude oil for the period between 2007 and 2021. Following the work of Balcilar et al. (2021), we utilise the TVP-VAR extended joint connectedness method and compare results to the standard TVP-VAR method that predicates upon the normalisation approach by Diebold and Yılmaz (2009, 2012, 2014). Both methods provide qualitatively similar results. Overall, findings suggest that connectedness in this network is highly responsive to events that greatly affect international financial markets and assume large values across the sample period. Prominent among our results is that the crude oil market is an important net transmitter of volatility shocks across the network during the 2014 oil collapse period. In addition, the period from the beginning of 2018 and until mid-2019 is a rather turbulent period for stock markets a fact which is reflected upon the net receiving character of the market for crude oil. Finally, we show that the Canadian stock market is a persistent net transmitter of volatility in recent years, following developments in international trade and the outbreak of the COVID-19 crisis.

As investing in clean energy equities grows, a better understanding of the impact of market uncertainty on clean energy systematic risk is required because the systematic risk is used to estimate the cost of capital and to formulate investment strategies. The focus of this paper is to use multivariate GARCH models (ADCC, GO-GARCH) to calculate time-varying conditional clean energy equity betas and to study the impact that market uncertainty (stock market, oil market, technology stock market), measured using implied volatility, has on clean energy equity betas. The clean energy equity beta values show considerable time variation. Evidence is presented to show that implied volatility does have a significant impact on clean energy equity beta. This result is consistent with a mean reversion response of beta to increases in market volatility and is robust to the choice of GARCH model used to estimate beta.

It is widely believed that climate change can affect the financial performance of firms. In this chapter, we conceptualise the effects of climate change on the financial performance of firms. We explain that these effects have a twofold justification. First, climate change has been induced in the modern business as a form of pollution prevention. Therefore, firms that decrease their emissions can avoid environmental regulations and attract shareholders. Second, behavioural finance literature has shown that investors prefer environmental firms because they extract utility by holding these stocks. We empirically test the former channel. Results indicate that decreasing Greenhouse gases can indeed improve firms’ performance. Although, results are robust across three different regions; North America, Europe and Asian-Pacific, firms in the EU enjoy the highest benefits by engaging in emissions reductions.

Socially responsible investing (SRI) such as issuing green bonds is increasingly widely adopted, moving into mainstream investment activity. In this study, we consider China, Europe and the US, in order to investigate (i) co-movements across and within the respective markets for green and traditional bonds in these regions and (ii) whether green bonds enhance the value of fixed-income investment portfolios. We pay particular focus on connectedness during the outbreak of the COVID-19 crisis. To achieve our objectives, we employ a time-varying parameter vector autoregressive (TVP-VAR) connectedness framework and four multivariate portfolio construction methods, for the period between July 2016 and December 2020. Following this, bond portfolios are constructed with dynamic weighting schemes (including a novel ‘minimum connectedness’ portfolio) to question, if, when and to what extent green bonds are part of an international fixed-income investor’s portfolio. Results indicate that connectedness is intensified in the first quarter of 2020; however, the effect is not permanent. During this period, both green and black Chinese bonds, as well as green US bonds intensify their role as net recipients while, both green and black EU bonds weaken as net transmitters of pricing shocks while, black US bonds assume a net transmitting role. Overall, investing in green bonds results in more efficient portfolios. Finally, we show that the minimum connectedness portfolio achieves the highest Sharpe ratio and significantly reduces the investment risk.

GHG emission increases the carbon footprint, the presence of greenhouse gases and finally of global warming. This study attempts to investigate the persistence of GHG emissions in 186 countries globally within 25 consecutive years (1990–2014), using three partially overlapping windows. It confirms the possible nature of policy stance on GHG emissions across those nations. We use Long Memory identification through Order of fractional differencing (d) and Hurst Exponent (H) using the ARFIMA process. The study found that all 186 countries within 25 years are exhibiting persistence or long memory in their respective GHG emission data to varying degrees. Of the total number of countries, 172 exhibit weak stationarity and thus a random policy shock would assist the policymakers. On the other hand, about 14 countries, mostly from the former USSR region showed that strong stationarity requires a firm policy stance. Furthermore, as the observations triple, the intensity of long memory diminishes by over 60%. This study would assist the policymakers on choosing a permanent/transitory policy for their respective countries in terms of productivity, income inequality and added-value in several sectors.