ABSTRACT
The oil industry is experiencing a critical situation as the Covid-19 pandemic outbreak. There are several challenges that facing the industry specially the investors as the global decline in demand for Energy merchandises, the future exploration and development drilling in new assets that require massive investments is still uncertain based on the current market price and conditions. The much-reported fall in oil prices and the acute pressure on IOCs to survive in this environment led the companies to stop many ongoing projects and shrink work profile that affected the oil production all over the world. The situation in Egypt is quite challenging for the investors as Egypt is a big consumer, along with the political stability that kept the economy running directed the big IOCs to embrace innovative approaches to lower the operating costs that has the direct impact on the cost per barrel to support maintaining the country growth and secure current energy demand. Dragon Oil company as newly introduced to Egypt's market after acquiring the market shares of one of the major joint ventures in Egypt (Gulf of Suez Petroleum Company- GUPCO) in October 2019 has faced the same dilemma of exerted pressure on the expenditures (Capex and Opex) in order to cope with the global market circumstances. However that didn't deter the company to embrace an innovative way of thinking and handling for the situation. Dragon Oil/GUPCO multi-disciplinary teams achieved successfully a production incremental increase of 10,000 barrels per day through the past six month by adapting a strategic management innovative plans, alternative lower cost technical solutions, production optimization and introducing new proved technologies to the 50 years old assets. This paper will highlight the complete workflow adopted by GUPCO/Dragon Oil teams covering the whole process aspects;appraise, select, define and execution phases to achieve the company goals. The work done was including restoring production from Shut-in offshore platforms or wells via fixing the surface network using neoteric solutions, widely applying rigless interventions using several new techniques in the current producers to maximize their production and optimizing the production cycle across the four production chokes In Summary, Dragon Oil/GUPCO teams managed to increase GUPCO's production despite of the restricted budget and the negative impact of COVID-19 pandemic on the oil price and reach an outstanding performance in operation excellence and safety aspects that results in arresting the natural decline and increase the growth production by about 15% from the 2019 Average production. Copyright © 2023, Society of Petroleum Engineers.
ABSTRACT
Given that natural gas is a vital input for the U.S. utility sector, this study empirically investigates the return connectedness between the natural gas and utility stocks in the U.S. market. Using the quantile connectedness approach, we show that the nexus between natural gas and utility stocks is more pronounced at the tails compared to the central of the conditional distribution. The return connectedness indices are time-varying with a net receiver role of natural gas and driven by various macro-variables. Finally, our portfolio implication analyses with alternative tail risk measures suggest that it can be more beneficial for risk-adverse investors to allocate substantial weights into the electricity utility stocks in normal market conditions. However, during the COVID-19- induced recession, it is critical to shift more fund to the natural gas futures to reduce tail risks. © 2023 Elsevier B.V.
ABSTRACT
In recent years, international crude oil prices have been subject to unusually high fluctuations due to the ravages of the COVID-19 epidemic. Under such extreme market conditions, online investor sentiment can strengthen the correlation between oil price changes and external events. We use a (rolling-window) structural vector autoregression method to investigate the dynamic impact of online investor sentiment on WTI crude oil prices before and after the COVID-19 pandemic across multiple topics of price, supply, demand, and so on, which aims to explore the fluctuation mechanism driven by sentiment and the price changes triggered by public health events. The proposed aspect-level sentiment analysis approach can effectively distinguish and measure sentiment scores of different aspects of the oil market. Our results show that the constructed oil price prosperity index contributes 49.84% to the long-term fluctuations of WTI oil price, ranking first among the influencing factors considered. In addition, the peak value of impulse shocks to WTI oil prices rose from 6.47% to 8.40% during the period of dramatic price volatility caused by the epidemic. The results sketch the mechanisms by which investor sentiment can affect crude oil prices, which help policymakers and investors protect against extreme risks in the oil market. © 2023 Elsevier Ltd
ABSTRACT
The current outbreak and the financial crisis occurred due to Coronavirus (COVID‐19);the global economy is melting like an ice-cream. This current pandemic and the market condition have affected not only the human but also greatly impacted the commodities prices, demand & supply especially into the industry those which believes on the traditional way of working such as oil & gas and other energy sectors. If I will talk about only the oil and Gas or Petroleum industry, then based on the current market information and statistics then the short team impact is nearly 25% to 30% decrease in the petroleum consumptions, but the long-term impact can be even more than 35% to 40%. The CAPEX and OPEX investment for research and development have been slashed like anything. When the world started investing into the other source of energy then it has started forcing oil and gas industry to think out of the box and industry must change rapidly prior to losing a substantial market share because of orthodox thinking in terms of utilizing the available technology or investing in the future technologies. This paper will discuss about the way how to shift the whole industry from man oriented to machine oriented, uses of traditional technologies to the modern technologies and implementation of digitization and automation of running plant as well as upcoming projects starting in the earliest phase e.g., Feasibility study, Pre-Feed, FEED and EPC stage (including Pre-Commissioning/Commissioning) and the operation phase of the projects. Copyright © 2022, International Petroleum Technology Conference.
ABSTRACT
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. © 2023 Elsevier Ltd
ABSTRACT
In the field of computation, the art of predicting the stock market has always been a tough nut to crack for researchers. This is because stock prices are highly influential values. The prices depend on many factors, ranging from physical to physiological, rational and irrational, from geopolitical stability to the sentiments of the investors - all play a crucial role. Investors anticipate market conditions in the future for a successful investment. Hence considering the past stock prices as an embodiment of the factors mentioned above, we propose a stacked long-short-term-memory (LSTM) model to predict the closing index of stock prices during this highly uncertain pandemic period using root mean square error (RSME) as the performance indicator. The model is optimized to improve the prediction accuracy in order to achieve high performance stock forecasting. The dataset considered is from NIFTY 50 scaling across four sectors, namely - auto, bank, healthcare and metal from a duration of 30th January 2020 to 31st March 2022. This paper aims to consider the historical data to analyze future patterns and insights. © 2022 IEEE.
ABSTRACT
Our goal is to examine the efficiency of different intraday electricity markets and if any of their price prediction models is more accurate than others. The focus is on the German intraday market for electricity. We want to find out whether the COVID-19 crisis has an influence on the price development. This paper includes a comprehensive review between Germany, France and Norway (NOR1) day-ahead and intraday electricity market prices. These markets represent different energy mixes which would allow us to analyse the impact of the energy mix on the efficiencies of these markets. To draw conclusions about extreme market conditions (i) we reviewed the market data linked to COVID-19. We expected a higher volatility in the lockdowns than before and therefore decrease in efficiency of the prediction models. With our analysis, (ii) we want to draw conclusions as to whether a mix based mainly on renewable energies such as that in Norway implies lower volatilities even in times of crisis. This would answer the question (iii) whether a market with an energy mix like Norway is more efficient in highly volatile phases. For the analysis we use data visualization and statistical models as well as sample and out-of-sample data. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
ABSTRACT
In northwest Florida, advanced manufacturing (AM) jobs far outpace the middle-skilled technician workforce, though AM constitutes almost a quarter of the region's total employment. From 2018-2028, of the available 4.6 million manufacturing jobs, less than half are likely to be filled due to talent shortages. This widening “skills gap” is attributed to many factors that range from new technologies in the AM industry (e.g., artificial intelligence, robotics), a need for newer recruiting methods, branding, and incentives in AM educational programs. Some professionals have even indicated that manufacturing industries and AM educational programs should be aligned more to reflect the needs of the industry. Even in the wake of Covid-19, when there have been over 658,000 manufacturing jobs lost due to market conditions, many states still have jobs that go unfilled further suggesting that there are challenges in filling AM technician positions. In a time when technicians in AM are in high demand and the number of graduates are in low supply, it is critical to identify whether AM education is meeting the needs of new professionals in the workforce and what they believe can be improved in these programs. This is especially true in rural locales, where economies with manufacturing industries are much more reliant on them. In the context of a NSF Advanced Technological Education (ATE), through a multi-method approach, we sought to understand: 1) Which AM competencies skills did participants report as benefiting them in gaining employment? 2) Which competencies are needed on the job to be a successful AM technician? 3) What are the ways in which AM preparation can be improved to enhance employment outcomes? This study's results will expand the research base and curriculum content recommendations for regional AM education, as well as build regional capacity for AM program assessment and improvement by replicating, refining, and disseminating study approaches through further research, annual AM employer and educator meetings, and annual research skill-building academies in which stakeholders transfer research findings to practices and policies that empower rural NW Florida colleges. To date, research efforts have demonstrated that competency perceptions of faculty, employers, and new professionals have notable misalignments that have opportunities for AM program curriculum revision and enhancement. This paper summarizes five years of research output, emphasizing the impactful findings and dissemination products for ASEE community members, as well as opportunities for further research. © American Society for Engineering Education, 2022.
ABSTRACT
While the overall level of food insecurity in the United States has remained stable during the COVID-19 pandemic, certain individuals and regions have fared worse than others. This study examines state-level variables affecting individual- and household-level food insecurity during the recent two years of the pandemic beginning in 2020 by utilizing the Household Pulse Survey, a new nationally representative dataset developed by the United States Census Bureau. The results of this study suggest a set of statewide factors, such as pandemic-driven market conditions, COVID-19 prevalence, and the implementation of federal programs, are associated with the level of food insecurity that individuals have experienced during the pandemic over the past two years. The associations varied by household income levels, indicating a strong relationship between higher-income households and market conditions, as well as the importance of federal programs and state policies in alleviating food insecurity among lower-income households. The food insecurity indices also overlapped with different socioeconomic and health hardships caused by the pandemic, such as employment income loss, housing instability, and mental health problems. The findings of this study highlight state-level contexts, particularly the role of state governments, in responding to pandemic-related food insecurity.
ABSTRACT
We examine intraday volatility spillover and interdependence between spot and futuresin different market conditions over two major events - covid-19 and 2008-09 global financial crisisand assess the evolution of hedging dynamics. Our findings indicate distinct differences and similarities in both the crises. During covid-19, we find evidence of increased symmetry in own-market volatility, decreased duration of bear phase and swift recovery to pre-crisis levels. In both 2008-09 crisis and covid-19 period, we findi) strong interconnectedness between spot and futures volatility spillover effect and the intensity varies widely across up and down trends ii) cross-marketvolatility spillover and correlation from futures to spot is relatively higherand provides stronger hedging opportunities during downtrends. The GARCH-BEKK findings demonstrate the importance of market condition-based time varying covariance estimations. © Indian Institute of Finance.
ABSTRACT
Our goal is to examine the efficiency of different intraday electricity markets and if any of their price prediction models are more accurate than others. This paper includes a comprehensive review of Germany, France, and Norway’s (NOR1) day-ahead and intraday electricity market prices. These markets represent different energy mixes which would allow us to analyze the impact of the energy mix on the efficiencies of these markets. To draw conclusions about extreme market conditions, (i) we reviewed the market data linked to COVID-19. We expected higher volatility in the lockdowns than before and therefore decrease in the efficiency of the prediction models. With our analysis, (ii) we want to draw conclusions as to whether a mix based mainly on renewable energies such as that in Norway implies lower volatilities even in times of crisis. This would answer (iii) whether a market with an energy mix like Norway is more efficient in highly volatile phases. For the analysis, we use data visualization and statistical models as well as sample and out-of-sample data. Our finding was that while the different price and volatility levels occurred, the direction of the market was similar. We could find evidence that our expectations (i–iii) were met. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.
ABSTRACT
This paper investigates the impact of different oil price shocks on systemic risk under different market conditions. We show that the negative impact of negative oil price shocks on systemic risk is greater than the positive impact of positive oil price shocks. Systemic risk is always negatively affected by oil-specific demand shocks but positively affected by oil supply shocks when the market is under medium and low systemic risk levels. By testing the effect of crises, we find that the influence of positive and negative oil price shocks on systemic risk was declined due to the COVID-19 pandemic. © 2022 Elsevier B.V.