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This study aims to investigate the response of green investments of emerging countries to own-market uncertainty, oil-market uncertainty and COVID-19 effect/geo-political risks (GPRs), using the tail risks of corresponding markets as measures of uncertainty.

This study employs Westerlund and Narayan (2015) (WN)-type distributed lag model that simultaneously accounts for persistence, endogeneity and conditional heteroscedasticity, within a single model framework. The tail risks are obtained using conditional standard deviation of the residuals from an asymmetric autoregressive moving average – ARMA(1,1) – generalized autoregressive conditional heteroscedasticity – GARCH(1,1) model framework with Gaussian innovation. For out-of-sample forecast evaluation, the study employs root mean square error (RMSE), and Clark and West (2007) (CW) test for pairwise comparison of nested models, under three forecast horizons; providing statistical justification for incorporating oil tail risks and COVID-19 effects or GPRs in the predictive model.

Green returns responds significantly to own-market uncertainty (mostly positively), oil-market uncertainty (mostly positively) as well as the COVID-19 effect (mostly negatively), with some evidence of hedging potential against uncertainties that are external to the green investments market. Also, incorporating external uncertainties improves the in-sample predictability and out-of-sample forecasts, and yields some economic gains.

This study contributes originally to the green market-uncertainty literature in four ways. First, it generates daily tail risks (a more realistic measure of uncertainty) for emerging countries’ green returns and global oil prices. Second, it employs WN-type distributed lag model that is well suited to account for conditional heteroscedasticity, endogeneity and persistence effects; which characterizes financial series. Third, it presents both in-sample predictability and out-of-sample forecast performances. Fourth, it provides the economic gains of incorporating own-market, oil-market and COVID-19 uncertainty.

The purpose of this paper is to examine, in a global perspective, the oil, gold, US dollar and stock prices interdependencies and to identify instantaneously direct and indirect linkages among them.

A methodology based on simultaneous equations system was used to identify direct and indirect linkages for the period 1995-2015. The authors try initially to find theoretical answers to main question of the study by discussing causal bilateral relationships while focusing on multilateral interactions.

The results show significant interactions between all markets. The authors found a negative relation between oil and stock prices but oil price is significantly and positively affected by gold and USD. Oil price is also affected by oil futures prices and by Chinese oil gross imports. Gold rate is concerned by changes in oil, USD and stock markets. The US dollar is negatively affected by stock market and significantly by oil and gold price. Indirect effects always exist which confirm the presence of global interdependencies and involve the financialization process of commodity markets.

Motivation of this research paper is the substantial implications of price movements on real economy and financial markets. Understanding that co-movement has great value for investors, policy makers and portfolio managers. This paper differs from previous studies in several aspects. First, most of the research papers focus on bilateral linkages solely, while the authors’ investigation was implemented on all the four markets simultaneously. Second, the study was developed in a global framework using international data. The global analysis allows avoiding country specific effects.

The purpose of this paper is to study the efficiency of different oil and gas markets. Most previous studies examined the issue using low frequency date sampled at monthly, weekly, or daily frequencies. In this study, 30-minute intraday data are used to explore efficiency in energy markets.

Sophisticated statistical analysis techniques such as Granger-causality regressions, augmented Dickey-Fuller tests, cointegration tests, vector autoregressions are used to explore the transmission of information between oil and gas energy markets.

This study provides evidence for efficiency in energy markets. The new information that arrives either to futures markets or spot markets is digested correctly, completely, and in a fast manner, and is propagated to the other market. The evidence indicates high efficiency.

This study is one of the first papers that uses 30-minute interval intraday data to investigate efficiency in oil and gas commodity markets.

The 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.

The 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.

One 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.

The 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.

The 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.

原油市場在流行病肆虐的2020年的頭半年經歷史無前例的過度反應。本文旨在顯示全球原油市場在2019冠狀病毒病流行期間的表現及原油市場與其它資產類別之溢出關係.

我們使用各種大流行病爆發的指標，來顯示原油市場因2019冠狀病毒病的感染而過度反應。我們的分析亦涉及市場的關聯性及原油市場與其它資產類別之溢出關係.

我們其中一個基本的發現是: 原油市場仍對大流行病的虛假新聞有更迅速的反應。全球大流行病恐慌性指數及大流行病情緒指數所帶來的震驚似乎是有希望的。大家亦察覺，能源交易商的情緒(OVX及OIV) 在2019冠狀病毒病爆發期間被測量為處於太高的水平。波動溢出分析顯示、原油與其它市場有密切的關係，而總關聯度指數引導平均35%來自溢出量的作用。在感染傳播初期，其它的宏觀經濟和政治事件仍對市場有利。在大流行病爆發期間的第二階段則損害全球原油市場。我們發現，傳染病會增加投資者的恐慌和焦慮.

原油投資者的情緒指數OVX顯示因傳染病及因缺乏對沖基金來保障能源投資而帶來的懼怕和恐慌。於OVX測算到的投資者空前的過度反應顯示市場參與者就這傳染病的感染爆發付出過量的賣權(保障)權利金.

我們的經驗模型和在2019冠狀病毒病肆虐期間匯報的研究結果，從使用以新聞為基礎的流行病指數的角度而言是新穎的。而這些全以內容分析和正文搜尋為基礎、使用自然語言處理，並輔以計算機算法.

The so-called “oil price war” of 2014-2016 took place between several main global oil producers; OPEC (led by Saudi Arabia), Russia and the newcomer; American tight oil or fracking oil. These oil producers were competing against each other over market shares in the global oil market, by maintaining their high oil production rates, even if this led to a decline in oil prices and a reduction in revenues from oil sales. As energy politics need more coverage in International Political Economy (IPE) theory, this paper aims to argue that Saudi Arabia's policies during the oil price war of 2014-2016 reflected a policy of neomercantilism, which is the IPE equivalent of the school of realism in International Relations (IR).

This paper tests for neomercantilism by testing three of its main definitional components. The first definitional component is that the state, as the political authority, intervenes in the economic decisions. The second component is the primacy of the state interests over business corporate profits, or the primacy of political and security considerations over short-term economic and corporate profit considerations. The third is the zero-sum or relative gains nature of dealings between states. Afterwards, this paper tests for neomercantilism in the Saudi policy by examining how each of these definitional components is reflected in the Saudi policy during the oil price war.

As energy politics need more coverage in International Political Economy (IPE) theory, this paper argues that Saudi Arabia's policies during the oil price war of 2014-2016 reflected a policy of neomercantilism, which is the IPE equivalent of the school of realism in International Relations (IR).

As energy politics need more coverage in International Political Economy (IPE) theory, this paper argues that Saudi Arabia's policies during the oil price war of 2014-2016 reflected a policy of neomercantilism, which is the IPE equivalent of the school of realism in International Relations (IR).

The purpose of the study is to find out the impact of gold and oil prices on the stock market.

This study uses the data on gold prices, stock exchange and oil prices for the period 1991–2016. This study applied descriptive statistics, augmented Dickey–Fuller test, correlation and autoregressive distributed lag test.

The data analysis results showed that gold and oil prices have a significant impact on the stock market.

Following empirical evidence of this study, the authors recommend that investors should invest in gold because the main reason is that hike in inflation reduces the real value of money, and people seek to invest in alternative investment avenues like gold to preserve the value of their assets and earn additional returns. This suggests that investment in gold can be used as a tool to decline inflation pressure to a sustainable level. This study was restricted to use small sample data owing to the availability of data from 1991 to 2017 and could not use structural break unit root tests with two structural break and structural break cointegration approach, as these tests require high-frequency data set.

This study provides information to the investors who want to get the benefit of diversification by investing in gold, oil and stock market. In the current era, gold prices and oil prices are fluctuating day by day, and investors think that stock returns may or may not be affected by these fluctuations. This study is unique because it focusses on current issues and takes the current data in this research to help investment institutions or portfolio managers.

This study aims to examine the ability of clean energy stocks to provide cover for investors against market risks related to climate change and disturbances in the oil market.

The study adopts the feasible quasi generalized least squares technique to estimate a predictive model based on Westerlund and Narayan’s (2015) approach to evaluating the hedging effectiveness of clean energy stocks. The out-of-sample forecast evaluations of the oil risk-based and climate risk-based clean energy predictive models are explored using Clark and West’s model (2007) and a modified Diebold & Mariano forecast evaluation test for nested and non-nested models, respectively.

The study finds ample evidence that clean energy stocks may hedge against oil market risks. This result is robust to alternative measures of oil risk and holds when applied to data from the COVID-19 pandemic. In contrast, the hedging effectiveness of clean energy against climate risks is limited to 4 of the 6 clean energy indices and restricted to climate risk measured with climate policy uncertainty.

The study contributes to the literature by providing extensive analysis of hedging effectiveness of several clean energy indices (global, the United States (US), Europe and Asia) and sectoral clean energy indices (solar and wind) against oil market and climate risks using various measures of oil risk (WTI (West Texas intermediate) and Brent volatility) and climate risk (climate policy uncertainty and energy and environmental regulation) as predictors. It also conducts forecast evaluations of the clean energy predictive models for nested and non-nested models.

This study aims to establish the dynamic relationship between international crude oil prices and Indian stock prices represented by the Bombay Stock Exchange (BSE) energy index.

Using Johansen’s cointegration test, vector error correction (VEC) model, impulse response function and variance decomposition test the study tries to ascertain the short-term and long-term dynamic association between the oil price shock and the movement of stock price and Granger causality test is applied to find out the nature of causality.

Considering vector autoregression estimation, the present study analyzes the relationship between the variables and tries to make a valid conclusion. The result of the co-integration test exhibits the presence of a long-term association between these two macro-economic variables during the period under study. Also, in the short-run VEC Granger causality result reveals that the movement of international crude oil price significantly influences the Indian stock price.

To get a more robust result the study can be further extended by taking a longer time period with data of shorter time-frequency such as daily or weekly and further by using more sophisticated econometric and statistical tools. Further, the study can be extended to firm-level investigation considering the forward trading concentration with the Indian oil basket.

In today’s globalized era, forecasting of share price movement helps investors in predicting the market and invest accordingly. Through this liquidity of the markets enhance and markets become more active in the global arena.

This study represents fresh findings in the changing time period the linkage between crude oil prices and stock prices which are of value to the academicians, researchers, policymakers, investors, market regulators, etc.

This study aims to explore the linkage between fluctuations in the global crude oil price and equity market in fast emerging economies of India and China.

The present research uses wavelet decomposition and maximal overlap discrete wavelet transform (MODWT), which decompose the time series into various frequencies of short, medium and long-term nature. The paper further uses continuous and cross wavelet transform to analyze the variance among the variables and wavelet coherence analysis and wavelet-based Granger causality analysis to examine the direction of causality between the variables.

The continuous wavelet transform indicates strong variance in WTIR (return series of West Texas Instrument crude oil price) in short, medium and long run at various time periods. The variance in CNX Nifty is observed in the short and medium run at various time periods. The Chinese stock index, i.e. SCIR, experiences very little variance in short run and significant variance in the long and medium run. The causality between the changes in crude oil price and CNX Nifty is insignificant and there exists a bi-directional causality between global crude oil price fluctuations and the Chinese equity market.

To the best of the authors’ knowledge, very limited work has been done where the researchers have analyzed the linkage between the equity market and crude oil price fluctuations under the framework of discrete wavelet transform, which overlooks the bottleneck of non-stationarity nature of the time series. To bridge this gap, the present research uses wavelet decomposition and MODWT, which decompose the time series into various frequencies of short, medium and long-term nature.

This study mainly focuses on the potentiality of the e-commerce industry's opportunities and limitations in the Kingdom of Saudi Arabia (KSA) specifically toward non-oil revenue sectors.

E-commerce contribution to the retail market industry becomes more global and more flexible with the rapid growth of the Internet and information technology revolution. A new way of conducting business is rendered by e-commerce, which helps to make a profit electronically.

The main contributions of e-commerce are management of company operations, easy and cheaper ways of extending their markets and coordinating with the value chain across different borders. In addition, the Internet and e-commerce are responsible for removing language barriers, cultural diversification and extending the market to the national boundaries. The countries would have many innovative and dynamic aspects by the beginning of the global market that increases national revenue, market, employment opportunity, capital and access to technology and information.

At present, KSA's national revenue mostly depends on oil and its related commodities, while other trades compete with the global market and increase national income. So, it is essential to increase other Saudi products to reach a global business level through e-commerce. Moreover, the study suggests accessing new markets and participating in global production to improve e-commerce structure without affecting current employment patterns, industry structure, productivity and Saudi culture.