An Empirical Analysis of the Price Discovery Function of Shanghai Fuel Oil Futures Market

This paper analyzes the role of price discovery of Shanghai fuel oil futures market by using methods, such as unit root test, co-integration test, error correction model, Granger causality test, impulse-response fimction and variance decomposition. The results showed that there exists a strong relationship between the spot price of Huangpu fuel oil spot market and the futures price of Shanghai fuel oil futures market. In addition, the Shanghai fuel oil futures market exhibits a highly effective price discovery function.

Long memory and nonlinear dependence structure in crude oil futures returns and volatility

In order to investigate the nature of international crude oil futures and present evidence of long memory and nonlinear dependence for crude oil futures volatility as well as returns, a certain number of recent statistical tests, such as the powerful BDS test, the fractional integration test and other known statistics, are applied. The results show that though the returns themselves contain little serial correlation, the market volatility series have significant long-term dependence structures which may have important implications for volatility forecasts and derivative pricing. On the other hand, evidence of strong ARCH effect is also presented, and, moreover, the BDS statistics on the standardized residuals of the fitted GARCH model indicate that the ARCH-type process may generally explain the nonlinearities in the data. It seems that the crude oil futures market can be appropriately modeled by ARCH and fractal processes. These findings indicate that it would be beneficial to assess the behavior of the crude oil and price the oil derivative contracts by encompassing long memory and nonlinear structure.

Volatility Spillover Effect of the International Crude Oil Futures Price on Composite and Sector Indices between the Chinese and Australian Stock Markets

As a type of non-renewable industrial resource,petroleum is of great strategic significance to the development of each nation.Ever since the 19th century,an array of oil crises have incurred certain downturn of the world economy.Pertinent studies have implied that financial crisis is always prone to be accompanied with oil crisis,yet the relevance of crude oil to the stock market,the barometer of the macro-economy,is ambiguous.In order to avoid the risks induced by the volatility of oil price,the oil futures market has appeared,and at the same time,the financial property of crude oil has become far more evident.Owing to lack of mature mining and refining technology,China still imports large amounts of oil from abroad at present.Thus,the economy of China is susceptible to fluctuation in petroleum price.As for Australia,the only net importer among the member countries of the International Energy Agency(IEA),it fails to attain the target of holding 90 days of fuel reserves set by the agency.However,in 2013,Australian Lincoln Energy announced that a gigantic shale oil field with an estimated value of 21 trillion US dollars was found in the South of Australia,and that if that field is mined,Australia has the possibility to turn into a net exporter of crude oil.It can be expected that the Australia’s economic conditions would be closely related to the international oil to a certain extent.Based on the approaches of the first difference and co-integration,this paper delves into the volatility spillover effect of crude oil futures on the Chinese and Australian stock markets.According to the empirical findings,in the short run,the price of crude oil futures has a greater impact on the Australian composite index than on the Chinese composite index.However,crude oil futures are negatively related to the Chinese composite index in the long run.The price of crude oil futures has no significant impact on the Chinese sector indices,but it has a certain impact on the Australian utilities,energy,materials,and industrial sector indices.In the Chinese stock market,the movement of short-run effect to long-run effect of crude oil futures on sector indices is in the reverse direction.Finally,the price of crude oil futures has a significant volatility spillover effect only on the Australian utilities sector index.

Toward energy finance market transition:Does China's oil futures shake up global spots market?

China is breaking through the petrodollar system,establishing RMB-dominating crude oil futures market.The country is achieving a milestone in its transition to energy finance market internationalization.This study explores the price leadership of China's crude oil futures and identifies its price co-movement to uncover whether it truly shakes up the global oil spots market.First,we find that for oil spots under different gravities,China's oil futures is only a net price information receiver from light-,medium-,and heavy-gravity oil spots,but it has a relatively stronger price co-movement with these three spots.Second,for oil spots under different sulfur contents,China's oil futures still has weak price leadership in sweet,neutral,and sour oil spots,but it has strong co-movement with them.Third,for oil spots under different geographical origins,China's oil futures shows price leadership in East Asian and Australian oil spots at the medium-and longrun time scales and strong price co-movement with East Asian,Middle Eastern,Latin American and Australian oil spots.China's oil futures may not have good price leadership in global spots market,but it features favorable price co-movement.

Impacts of CME Changing Mechanism for Allowing Negative Oil Prices on Prices and Trading Activities in the Crude Oil Futures Market

This study investigates and compares the effects of the Coronavirus disease 2019(COVID-19)pandemic,the Chicago mercantile exchange(CME)'s negative price suggestion on prices and trading activities in the crude oil futures market to discuss the cause of negative crude oil futures prices.Through event studies,the empirical results show that the COVID-19 pandemic no longer impacts crude oil futures prices in April,2020 after controlled market risk,while the CME's negative prices suggestion can explain the crude oil futures price changes around and even after April 8,2020 to some degree.Moreover,this study uncovers anomalies in prices and trading activities by analyzing returns,trading volume,open interest,and illiquidity measures using vector autoregressive(VAR)models.The results imply that CME's allowing negative prices strengthens the price impact on trading volume and makes illiquidity risk matter.This study's results coincide with the following lawsuit evidence of market manipulation.

Nonlinearities between oil spot and futures markets： Evidence from intraday data

This paper builds on the literature of the relationship between oil spot and futures prices from the NYNEX market, both in their means and in their conditional volatilities, to investigate whether the association is linear or not. The novelty of this work is based on intraday data from both markets. The empirical findings indicate the presence of nonlinearities both in means and conditional volatilities. Moreover, non-linear causality estimations both in means and in volatilities reveal the presence of bi-directional causality, a fact that provides additional support to the hypothesis that both markets are driven by the same information sets.

Analysis on the spatial pattern and evolution of China's petroleum trade under the dual effect of international oil price and “Belt and Road” Framework

“Belt and Road” is the important origin of oil import in China. Based on social network analysis and stochastic frontier gravity model, this paper studied the characteristic evolution and influence factor of oil import network between China and “Belt and Road” countries. Then by constructing a stochastic frontier gravity model including the crude oil future price and oil importing price, it found that the international crude oil future price, the oil importing price, the political situation, the trade agreements have the effects on the China's oil import from “Belt and Road” region. It provided suggestions for improving the spatial pattern of China's petroleum trade.

Cottonseed Oil as Promising Biodiesel in Future

With recent increases in petroleum prices,there is renewed interest in vegetable oil and their derivatives as alternative fuels for diesel engines.There are more than 350 oil-bearing crops identified,

To jump or not to jump:momentum of jumps in crude oil price volatility prediction

A well-documented finding is that explicitly using jumps cannot efficiently enhance the predictability of crude oil price volatility.To address this issue,we find a phenomenon,“momentum of jumps”(MoJ),that the predictive ability of the jump component is persistent when forecasting the oil futures market volatility.Specifically,we propose a strategy that allows the predictive model to switch between a benchmark model without jumps and an alternative model with a jump component according to their recent past forecasting performance.The volatility data are based on the intraday prices of West Texas Intermediate.Our results indicate that this simple strategy significantly outperforms the individual models and a series of competing strategies such as forecast combinations and shrinkage methods.A mean–variance investor who targets a constant Sharpe ratio can realize the highest economic gains using the MoJ-based volatility forecasts.Our findings survive a wide variety of robustness tests,including different jump measures,alternative volatility measures,various financial markets,and extensive model specifications.

Exploring Long-Memory Process in the Prediction of Interval-Valued Financial Time Series and Its Application

Long-memory process has been widely studied in classical financial time series analysis,which has merely been reported in the field of interval-valued financial time series.The aim of this paper is to explore long-memory process in the prediction of interval-valued time series(IvTS).To model the long-memory process,two novel interval-valued time series prediction models named as interval-valued vector autoregressive fractionally integrated moving average(IV-VARFIMA)and ARFIMAX-FIGARCH were established.In the developed long-memory pattern,both of the short term and long-term influences contained in IvTS can be included.As an application of the proposed models,interval-valued form of WTI crude oil futures price series is predicted.Compared to current IvTS prediction models,IV-VARFIMA and ARFIMAX-FIGARCH can provide better in-sample and out-of-sample forecasts.