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.

The Impact of Restricted Measures on Price Discovery in Stock Index Futures:Evidence from CSI 500 Stock Index Futures

This paper compares the impact of restricted measures on CSI 500 stock index futures market and its underlying spot market.It uses vector error correction(VECM)model and common factor analysis method to study the differences between the two markets before and after the restricted measures was implemented.This paper analyzes the price discovery function through three aspects,i.e.,response to new information,price ratio of new information,and price discovery contribution degree of two markets.Based on empirical results,it is clear that group one in the period of April 17th to September 2nd has an obvious price discovery function.However,group two in the period of September 7th to December 31th does not have.The result shows that stock index futures do have price discovery function to some extent.However,due to the impact of restrictive policies,the spot market price contribution may exceed the futures market in some special time periods,which implies that the price discovery function of CSI 500 stock index futures market is not stable.

Can the Shanghai LNG Price Index indicate Chinese market?An econometric investigation using price discovery theory

China became the world's second largest liquefied natural gas(LNG)importer in 2018 but has faced extremely high import costs due to a lack of bargaining power.Assessments of the Shanghai LNG Price Index,first released in 2015,are vital for improving the understanding of these cost dynamics.This paper,using the LNG price index data from the Shanghai Petroleum and Gas Exchange(SHPGX)coupled with domestic and international LNG prices from July 1,2015 to December 31,2018,estimates several econometric models to evaluate the long-term and short-term equilibriums of the Shanghai LNG Price Index,the responses to market information shocks and the leading or lagging relationships with LNG and alternative energy prices from other agencies.The results show that the LNG price index of the SHPGX has already exhibited a long-term equilibrium and short-term adjustment mechanisms to reflect the average price level and market movements,but the market information transparency and price discovery efficiency of the index are still inadequate.China's LNG market is still relatively independent of other natural gas markets,and marketization reforms are under way in China.The influence of the SHPGX LNG price index on the trading decisions of market participants is expected to improve with further development of China's LNG reforms,the formation of a natural gas entry-exit system,and the increasing liquidity of the hub.

Market efficiency of gold exchange-traded funds in India

Background:Gold exchange-traded funds,since introduction,are primarily aimed at tracking the price of physical gold in the financial market.This,a category of exchange-traded funds,whose units represent physical gold,is traded on exchanges like any other financial instrument.In the Indian financial market,gold exchange traded funds were introduced a decade ago to facilitate ordinary households'participation in the bullion market.They were also designed to assist in the price discovery mechanism of the bullion market.Presentation of the hypothesis:In this paper,it is attempted to check if one of the constituents of price discovery mechanism,informational efficiency,has been achieved in gold exchange-traded funds’market.Information efficiency becomes evident only when all available information is reflected in the market price of the instrument.Testing the hypothesis:Therefore,in order to assess the weak-form efficiency of the gold exchange-traded funds market,the daily returns of five gold exchangetraded funds traded on the Indian Stock Exchange over the period March 22,2010,to August 28,2015,were used.The non-parametric runs test,the parametric serial correlation test,and the augmented Dickey-Fuller unit root test are employed.Implications of the hypothesis:The test results provide evidence that the efficient market hypothesis does not hold for the gold exchange-traded funds’market in India.Further,the test results address several underlying issues with respect to price discovery in the market under study and suggest that the Indian market for this derivative is not weak-form efficient.Hence,the factors affecting gold exchange traded-funds’market warrant the attention of the country’s regulatory bodies,as appropriate legislation in support of market efficiency is needed.

Information Linkages between Chinese and World Copper Futures Markets

In this paper, we examine the price discovery process and volatility spillover effects in informationally linked futures markets. Using synchronous trading information from the Shanghai Futures Exchange （SHFE）, the New York Mercantile Exchange （NYMEX）, and the London Metal Exchange （LME） for copper futures from 2000 to 2012, we show that the cointegration relationships of these futures markets changed during 2006-2008. The results indicate that there is a bidirectional relationship in terms of price and volatility spillovers between the LME and NYMEX and the SHFE, with a stronger effect from the LME and NYMEX to the SHFE （versus the effect from the SHFE to the LME and NYMEX） prior to 2006. Our results also highlight the increasingly prominent role of the SHFE in the price formation process and cross-volatility spillover effects since 2008. Finally, we show that volatility spillover has important implications for constructing optimized portfolios for copper investors.