Search results

The purpose of this paper is to explore the dynamic influence of WTI crude oil returns on the stock returns of China’s traditional energy sectors, including oil and gas exploitation, coal mining and processing, petroleum processing and coking, electricity, heat production and supply and mining services.

Hong’s information spill-over test and the DP Granger causality test are applied to investigate the relationship between the two markets. Moreover, a rolling window is introduced into the above two tests to capture time-varying characteristics of the influence of WTI crude oil returns.

The empirical results indicate that, first, there exists significant bidirectional linear causality between WTI crude oil returns and China’s traditional energy sectoral stock returns, but the nonlinear causality appears weaker. Second, the influence of WTI crude oil returns on traditional energy sectoral stock returns has time-varying characteristics and industry heterogeneity both in the linear and nonlinear cases. Finally, the decline of WTI crude oil prices may strengthen its linear influence on the stock returns of traditional energy sectors, while the excessive rise of market values in traditional energy sectors may weaken the linear and nonlinear influence of WTI on them.

The general nexus between international crude oil market and China’s traditional energy stock market is explored both in the linear and nonlinear perspectives. In particular, the dynamic linear and nonlinear influence of WTI crude oil returns on China’s traditional energy sectoral stock returns and its industry heterogeneity are analysed in detail.

High inflation levels remain a challenge in macroeconomic stabilization policies among developing economies. Oil price is identified as an important driver of inflation. In the wake of high and unstable international oil prices, the question regarding the relationship between inflation and crude oil prices, and its implication for economic welfare has become a fundamental empirical issue.

This question is explored by estimating a non-linear autoregressive distribution lags (NARDL) model of inflation-oil nexus that examined the asymmetric response of inflation to oil price changes. The study then derived the welfare implication of the asymmetric responses, with implications for the petroleum pricing regime in Ghana.

The study found that inflation responds asymmetrically to oil prices in the long-run but not in the short-run. The welfare cost associated with the asymmetric response increases with increasing rate.

The findings of this study have some implications for petroleum product pricing in Ghana. Recently, Ghana has moved from regulating petroleum prices to the automatic adjustment system. By this policy, petroleum prices change in tandem with the crude oil prices and exchange rates on the international market. Whiles this policy might be comparatively efficient, the evidence of asymmetric response of inflation to changes in oil prices raises some issues about the welfare effect of the policy.

The paper contributes to the literature on the inflation-oil price nexus by investigating critical questions that remain puzzling. These questions include; Does inflation respond asymmetrically to the positive and negative shock of equal magnitude in oil prices? Does inflation response to the asymmetry changes in oil prices have any implications for the welfare of the country? Is the effect of oil price changes pernicious?

While numerous empirical studies have tried to model and forecast the oil price volatility over the years, such attempts using the crude oil volatility index (OVX) rarely exist. In order to conceal this void, the purpose of this paper is to investigate whether including OVX in the realized volatility (RV) models improve the accuracy of predictions.

At the empirical stage, the authors employ several measures to frame the RV of crude oil futures returns. In particular, the authors use three different range-based RV estimators recommended by Parkinson (1980), Rogers and Satchell (1991) and Alizadeh et al. (2002), respectively.

The findings reveal that the information content of crude OVX helps to provide more accurate volatility predictions in comparison to the base-line RV model which contains only historical oil volatilities. Besides, the forecast encompassing test further suggests that the modified RV model (when OVX is introduced in the base-line RV model) forecast encompasses the conventional RV forecast in majority of the cases.

Since forecasting oil price volatility plays a vital role in portfolio optimization, derivatives pricing, optimum asset allocation decisions and risk management, the findings of this study thus carry important implications for energy economists, investors and policymakers.

This paper adds to the existing literature, since it is one of the initial studies to explore whether OVX is informative about the realized variance of the US oil market returns. The findings recommend that the information content of oil implied volatilities should be taken into account when modeling the US oil market volatility. In addition, range-based measures should be utilized while estimating the RV.

The purpose of this paper is to examine the dynamic relationship between crude oil price volatility and stock markets in the emerging economies like BRIC (Brazil, Russia, India and China) countries in the context of sharp continuous fall in the crude oil price in recent times.

The stock price volatility is partly explained by volatility in crude oil price. The author adopt an Asymmetric Power ARCH (APARCH) model which takes into account long memory behavior, speed of market information, asymmetries and leverage effects.

For Bovespa, MICEX, BSE Sensex and crude oil there is an asymmetric response of volatilities to positive and negative shocks and negative correlation exists between returns and volatility indicating that negative information will create greater volatility. However, for Shanghai Composite positive information has greater effect on stock price volatility in comparison to negative information. The study results also suggest the presence long memory behavior and persistent volatility clustering phenomenon amongst crude oil price and stock markets of the BRIC countries.

The present study makes a number of contributions to the existing literature in the following ways. First, the author have considered crude oil prices up to January 31, 2016, so that the study can reflect the impact of declining trend of crude oil prices on the stock indices which is also regarded as “new oil price shock” to measure the volatility between crude oil price and stock market indices of BRIC countries. Second, the volatility is captured by APARCH model which takes into account long memory behavior, speed of market information, asymmetries and leverage effects.

This paper aims to examine the impact of crude oil prices on Australian industry stock returns. With rising energy prices, it is important to consider oil as a pricing factor in asset pricing models.

Multifactor static and dynamic models consider crude oil and other macroeconomic factors as pricing factors in industry excess returns from January 1980 to August 2006. The macroeconomic factors comprise the market portfolio, oil prices, exchange rates and the term premium. The industries consist of banking, diversified financials, energy, insurance, media, property trusts, materials, retailing and transportation.

Oil prices are an important determinant of returns in the banking, energy, materials, retailing and transportation industries. The findings also suggest oil price movements are persistent. Nonetheless, the proportion of variation in excess returns explained by the contemporaneous and lagged oil prices appears to have declined during the sample period.

Macroeconomic factors are important for multifactor asset pricing at the industry level. Apart from oil prices, the market portfolio is a significant pricing factor in all industry excess returns. Exchange rates are also an influential factor for excess returns in the banking and diversified financials industries, and the term premium as a proxy for future real activity is a priced factor in the energy, insurance and retailing industries.

While past studies have provided some evidence that oil prices constitute a source of systematic asset price risk and that exposure varies across industries, no recent work is known in the Australian context.

The purpose of the study is to investigate the long-run and short-run dynamic relationship between crude oil prices and the movement of Sensex for the period of 2000–2018.

The study uses the augmented Dickey–Fuller test for the presence of unit root, Johansen cointegration test for estimating the cointegration among the variables. Further, in the case of no cointegration found, the study employed the vector autoregression (VAR) model to estimate the long-run relationship and the Granger causality/Wald test for short-run relationship. The study also conducted tests for the prerequisites of the model: serial correlation, heteroskedasticity and normality of data.

The study found that both the variables, crude oil prices and Sensex are integrated of order 1, that is, I (1), and there is no cointegration between them. Further, the results proliferated from the VAR model unfold the marked effect of previous month crude oil prices (lag 1) on the movement of Indian stock market represented by Sensex considered as the benchmark index. Furthermore, VAR–Granger causality/block exogeneity Wald tests results indicated that there is a causal relationship between the crude oil prices and Sensex under the VAR environment. The model does not have any serial correlation and heteroskedasticity indicating toward the unbiased and robust estimates.

The study is conducted till the year 2018, and data for the present period (post-2018) is excluded due to ongoing trade issues between the USA and oil-exporting countries such as Iran. The current COVID-19 outbreak has also put serious issues. Due to limited time and availability of standardized data, researchers have considered Sensex as equity index only, but for more generalized research outcome few other equity indexes could have been taken for study.

The study is completely original in nature and is an extensive study of the relationship between the crude oil price and Indian stock market with reference to causality between the variables.

The desire to increase investor interest in emerging markets has motivated many studies of return and risk characteristics of equity prices in these markets. Using data from January 1999 to December 2002, we examine the dynamic relationships between oil, currency, and stock prices in the four major markets in the Middle East. Three of the four are highly correlated with the major stock markets. The potential for diversifying in Middle East markets is limited. The Egyptian and Jordanian markets, on one hand, and the Israeli and Saudi markets, on the other, are marginally integrated. While Israeli shekels significantly explain their equity prices, crude oil futures prices fairly explain oil‐rich Saudi and Egyptian equity prices. We conclude that it takes a long time for crude oil futures prices to reach equilibrium with stock prices in Israel when there is a shock to the system. However, it takes relatively a short time for crude spot oil prices and currency price to reach equilibrium with stock prices when there is a shock in the system of Saudi Arabia or Egypt. Our results suggest that, in the short and long term, investor decisions in these markets are influenced by oil and currency prices.

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.

Fundamentally, a commodity exchange, such as the New York Mercantile Exchange, serves a dual purpose. The first is hedging price risk, in which the exchange offers a fair and orderly market for shifting risk via the trading of future obligations. The second major function is price discovery, in which the exchange provides a centralized, open, and liquid forum for buyers and sellers to conduct business, by which the prices of all transactions conducted on the exchange are publicly disseminated. This article surveys the role of exchange traded futures and options contracts within the worldwide energy markets and the concepts, applications, and strategies that have evolved to a level of sophistication and versatility that could not have been foreseen 150 years ago.

The aim of this study was to determine if there are asymmetries in the pass-through of West Texas Intermediate (WTI) crude oil prices to its derivatives (diesel and gasoline) in the Brazilian market.

Initially, the future WTI oil price series was analyzed using the self-exciting threshold autoregressive (SETAR) and logistic smooth transition autoregressive (LSTAR) non-linear models. Subsequently, the threshold autoregressive error-correction model (TAR-ECM) and Markov-switching model were used.

The findings indicated high prices throughout 2008 due to the subprime crisis. The findings indicated high prices throughout 2008 due to the subprime crisis. The results indicated that there is long-term pass-through of oil prices in both methods, suggesting an equilibrium adjustment in the prices of diesel and gasoline in the analyzed period. Regarding the short term, the variations in contemporary crude oil prices have positive effects on the variations in fuel prices. Lastly, this behavior can partly be explained by the internal price management structure adopted during almost all of the analyzed period.

This paper contributes to the literature at some points. The first contribution is the modeling of the oil price series through non-linear models, further enriching the literature on the recent behavior of this time series. The second is the simultaneous use of the TAR-ECM and Markov-switching model to capture possible short- and long-term asymmetries in the pass-through of prices, as few studies have applied these methods to the future price of oil. The third and main contribution is the investigation of whether there are asymmetries in the transfer of oil prices to the price of derivatives in Brazil. So far, no work has investigated this issue, which is very relevant to the country.