OIL VOLATILITY-OF-VOLATILITY AND TAIL RISK OF COMMODITIES

This article analyzes recent volatility spillovers in the United States from crude oil using futures prices. Crude oil spillovers to both corn and ethanol markets are somewhat similar in timing and magnitude, but moderately stronger to the ethanol market. The shares of corn and ethanol price variability directly attributed to volatility in the crude oil market are generally between 10%- 20%, but reached nearly 45% during the financial crisis, when world demand for oil changed dramatically. Volatility transmission is also found from the corn to the ethanol market, but not the opposite. The findings provide insights into the extent of volatility linkages among energy and agricultural markets in a period characterized by strong price variability and significant production of corn-based ethanol.

This paper examines the causes and behavior of price volatility in the US crude oil market. Although crude oil prices are among the most volatile, they have received limited academic scrutiny heretofore. This study shows that (1) the crude oil market is characterized by volatility persistence, (2) a negative shock has more impact on future volatility than an equal positive shock, (3) crude oil volatility is lower at higher prices, (4) OPEC meeting announcements and the Petroleum Status Report releases cause increased volatility, and (5) there is a day-of-the-week pattern in this market. I develop and employ an improved procedure for testing and quantifying the hypothesized volatility determinants within GARCH type model.

This paper studies the US crude oil (CO) market and its structural changes. The theory of exhaustible resources and the fundamentals of crude oil supply and demand form the theoretic foundation of our research. The role of a set of recent drivers of oil prices in creating short-term shocks is then investigated. Such shocks cause deviations in the US CO market from the efficient-market hypothesis. In our empirical investigations, we implemented the modified rescaled range analysis, the Brock-Dechert-Scheinkman test and the maximum Lyapunov exponent test. The sample period ranges from 1986 to 2008 and two subperiods are considered: the energy crisis of 1990-91 and the financial meltdown in 2007-8. The findings supplement prior works on chaos theory and show temporary low-dimensional chaotic processes in the US CO market during periods of shocks. However, there is no evidence of persistent chaotic dynamics in the US CO market. Although the results do not indicate any structural changes in the US CO market, we find clear evidence of cyclical changes. In short, despite short-term shocks creating biased random-walk behavior in CO prices in the short term, the behavior of the US CO market is consistent with supply and demand fundamentals.

PurposeThe crude oil market has experienced an unprecedented overreaction in the first half of the pandemic year 2020. This study aims to show the performance of the global crude oil market amid Covid-19 and spillover relations with other asset classes.Design/methodology/approachThe authors employ various pandemic outbreak indicators to show the overreaction of the crude oil market due to Covid-19 infection. The analysis also presents market connectedness and spillover relations between the crude oil market and other asset classes.FindingsOne of the essential findings the authors report is that the crude oil market remains more responsive to pandemic fake news. The shock of the global pandemic panic index and pandemic sentiment index appears to be more promising. It has also been noticed that the energy trader's sentiment (OVX and OIV) was measured at a too high level within the Covid-19 outbreak. Volatility spillover analysis shows that crude oil and other market are closely connected, and the total connectedness index directs on average 35% contribution from spillover. During the initial growth of the infection, other macroeconomic and political events remained to favor the market. The second phase amidst the pandemic outbreak harms the global crude oil market. The authors find that infectious diseases increase investor panic and anxiety.Practical implicationsThe crude oil investors' sentiment index OVX indicates fear and panic due to infectious diseases and lack of hedge funds to protect energy investments. The unparalleled overreaction of the investors gauged in OVX indicates market participants have paid an excessive put option (protection) premium over the contagious outbreak of the infectious disease.Originality/valueThe empirical model and result reported amid Covid-19 are novel in terms of employing a news-based index of the pandemic, which are based on the content analysis and text search using natural processing language with the aid of computer algorithms.

The crude oil price exhibits a high degree of volatility which varies significantly over time. Such characteristics imply that the oil market is a promising area for testing volatility models. Testing and predicting volatility using ARCH and GARCH models have grown in the literature. A useful application of the volatility models is in the formulation of hedging strategies. In this paper we compare the optimal hedge ratio for the crude oil using the classical minimum risk approach and use ARCH to incorporate the effect of heteroskedasticity in the residuals on the hedge ratio. In addition, we test for the existence of a variable risk premium in the crude oil market. We find that, assuming rational expectations, there is a non-zero risk premium. We test for the variability of the risk premia and find evidence in its support when we employed a multivariate GARCH model.

The relationship between monetary uncertainty and price volatility in the global crude oil market has attracted considerable attention in recent years. Understanding this relationship is extremely important for both policy makers and market participants and investors. The purpose of this article is to explore a modern approach to regime switching in order to shed light on the dynamic interaction between monetary uncertainty and price volatility in the crude oil market. If we consider that oil is one of the main sources of energy in the world, and the price of oil plays an important role in the global economy, then the formation of oil prices depends on many factors, including supply and demand, political stability in the production regions, geopolitical events, climate change and, of course, monetary policy. The scientific significance of the article lies in the fact that it allows for a deeper understanding of the relationship between the economic policy of central banks and the dynamics of commodity prices. The practical significance lies in the fact that understanding the impact of monetary policy on oil prices can be useful for both government agencies and businesses. In this research methodology, an empirical method of work was used, in which the influence of monetary uncertainty on the volatility of world crude oil prices was considered. We also touch upon the issue of political uncertainty on the price of oil during the pandemic. The relevance of this article lies in the fact that the price of oil is one of the key indicators for the global economy, the study of the impact of monetary policy on this market is important. The price of oil can influence monetary policy in various ways. For example, changes in the interest rates of central banks affect investors and their decisions to invest in oil companies. In addition, monetary policy also affects the exchange rate, which also has an impact on the price of oil. In conclusion, it can be said that studying the impact of monetary policy on oil prices is important for both science and practice, and may lead to the development of more effective methods of economic and business management.

This paper constructs a TVP-VAR model to examine the dynamic spillover effects among the EU carbon emission, crude oil, Chinese stock, and Chinese exchange rate markets. Our findings are as follows: (1) Spillover effects are primarily short-term, with strong inter-market connections observed across the four markets. (2) Stronger connections are observed between the EU carbon market, the crude oil market, and the Chinese stock market. China’s relaxed investment restrictions and RMB exchange rate policy lead to a significant negative relationship between the Chinese stock market and the RMB exchange rate. However, the effects of the EU carbon market and crude oil market on the RMB exchange rate remain uncertain. (3) The Ukraine conflict and the China-U.S. trade war significantly amplify spillover effects between the EU carbon market and the crude oil market. Additionally, the Paris Agreement, China-U.S. trade war, COVID-19, and the Russia-Ukraine conflict significantly increase the spillover effects of the crude oil and carbon emissions markets on Chinese stocks and exchange rates.

Dynamic risk resonance between crude oil and stock market by econophysics and machine learning

Crude oil price and cryptocurrencies: Evidence of volatility connectedness and hedging strategy

Economic sanctions engender the disturbance of financial transactions between the sanctioner and the targeted nations. The Russia-Ukraine war also restricted Russia's entry into financial and commodity markets, with reverberating effects on the global market. Hence, the study aims to elucidate the relationship between armed conflicts and economic sanctions enforced by the G7 nations, the crude oil market, and its corresponding volatility index, OVX. It seems that heightened levels of ambiguity, conflict, nervousness, and hostility have contributed to an increase in the fluctuation of the energy market, leading to an extreme response to economic sanctions. Our findings reveal that financial restrictions imposed by Australia, Japan, the UK, and the USA have led to higher uncertainty and increased volatility in the oil market. The news variable War exhibits higher volatility compared to Crude oil and Recession in the media press. The war-induced uncertainty has shown a significant impact on the oil volatility.

Fluctuations in the financial markets stem from the reactions of investors to both market activities and more wide-ranging macroeconomic indices. This research examines the interconnectivity between returns on exchange rates and crude oil prices for ten oil-importing countries. Quarterly data spanning the period from 2000Q1 to 2022Q4 was used in the estimation. Returns had to be calculated from raw data, which were exchange rates and crude oil prices. The research methodologies include quantile regression and VAR-GARCH estimations. The study revealed a long-term association between crude oil market returns and foreign exchange markets, with currency fluctuations negatively impacting crude oil returns. The spill-over effect from the currency market to the oil market is weaker than the transmission effect from the oil market to the currency market of oil-importing countries. In particular, it was empirically established that shocks from past volatility in the currency markets of countries that import oil had commensurately lower volatility in the oil market by 6 percent. Whereas, the spillover from the crude oil market to the currency market depicts that increased turbulence on the crude oil market in the current period stimulated 55.66 percent amplified volatility in the currency market for oil-importing nations. Oil returns had a volatility persistence value of 0.1255, ratifying the weak volatility persistence of oil returns. The size of the volatility persistence of exchange rate returns is 0.997, an indication of high volatility persistence for currency returns. The study found the absence of leverage effects for currency values given a positive coefficient with a magnitude of 0.8529. In other words, bad news does not cause higher turbulence in exchange rate returns than good news will. For crude oil returns, the size of the leverage effects term is -0.0529, which is negative and significant (p<.05), implying that bad news in oil-importing economies has asymmetric impacts on the volatility of returns on crude oil prices. In effect, the oil price returns react more strongly to bad news than these returns react to good news. The findings of the study underscore the intricate relationships between local currencies and energy prices within the context of a global financial market, highlighting the significance of understanding these dynamics for effective decision-making and risk management in an increasingly interconnected world. It was recommended, among others, that international collaboration amongst countries is crucial given the global nature of energy markets.

Oil prices remain an important determinant of global economic performance. The oil prices have climbed up steadily recently, and it has not only shocked the crude oil market, but also influenced the financial markets. Owing to the fear of inflation brought on by higher crude oil, and the depreciation in the value of the US dollar, more and more investors put money into gold market. Thus the investigation of the relationship among the crude oil, gold The third thesis named as “The Realized Distributions of Dynamic Conditional Correlation and Volatility Thresholds among Crude Oil, Gold, and US Dollar/ British Pound Markets” applies Engle (2002) dynamic conditional correlation model to analyze the relationship among the crude oil, gold and US Dollar/ British Pound markets. Both the timevarying correlations and high contemporaneous dynamic conditional correlation across volatilities are explored, and some differences between low volatility days and high volatility days in realized distributions are found. Applying Kasch and Caporin (2007) volatility threshold dynamic conditional correlation model, we find that the volatility thresholds, the First Gulf War in 1990 and the 911 terror attack in 2001. and US Dollar/ British Pound market is an important issue. This paper investigates probability distributions, weekday effect, and dynamic conditional correlation among the crude oil, gold and US Dollar/ British Pound market. All these findings are important to market traders and hedging strategies, these have important implications for international investors, multinational firms, and risk managers and so on. They consider the impact of commodity return and volatility on portfolio diversification and on management, risk assessment, pricing and hedging, asset allocation decisions. This doctoral dissertation is divided into three parts. The first thesis named as “Probability Distribution of Return and Volatility among Crude Oil, Gold, and US Dollar/ British Pound Markets” applies new methodology of probability distributions to analyze the statistical properties of daily returns and volatility in crude oil, gold and US Dollar/ British Pound market. After fitting the data into probability distributions and estimating the parameters of the Gaussian distribution, we find that crude oil market shows the highest return, followed by gold market and US Dollar/ British Pound market. After estimating the peak and width of the volatility of the log-normal distribution, the US Dollar/ British Pound market seems to have the least volatility in the log normal distribution, and the crude oil market is the most unstable and volatile market. The second thesis named as “Does Weekday Effect Exist in Crude Oil, Gold, and US Dollar/ British Pound Markets? An Analysis from Probability Distribution Approach” reshapes the data into a panel style from Monday to Friday to investigate whether or not the weekday effect exists in the intraday return of crude oil, gold, and US Dollar/ British Pound market. We document traditional weekend effect had been lengthened (from Thursday to the next Tuesday) in gold market. This weekend effect disappears given that the distribution shifted leftward in oil market; instead, the weekday effect (from Wednesday to Friday) seems to appear significantly. As for the US Dollar/ British Pound market the lowest negative returns appear on Mondays, while the highest returns appear on Thursdays rather than Fridays.

Multifractal detrended cross-correlations between crude oil market and Chinese ten sector stock markets

Value-at-risk estimation of crude oil price using MCA based transient risk modeling approach

Exploring the dynamic effects of financial factors on oil prices based on a TVP-VAR model