Institutional high frequency trading and price discovery: Evidence from an emerging commodity futures market

2017 ◽  
Vol 38 (2) ◽  
pp. 243-270 ◽  
Author(s):  
Yue Zhao ◽  
Difang Wan
Keyword(s):  
High Frequency ◽  
Price Discovery ◽  
Futures Market ◽  
Commodity Futures ◽  
High Frequency Trading

scholarly journals High Frequency Trading and Price Discovery

2013 ◽  
Author(s):  
Jonathan Brogaard ◽  
Terrence J. Hendershott ◽  
Ryan Riordan
Keyword(s):  
High Frequency ◽  
Price Discovery ◽  
High Frequency Trading

scholarly journals Research on the Influence of Volatility of International Energy Commodity Futures Market on CPI in China

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Keyao Lin ◽  
Chao Xun ◽  
Fei Wang ◽  
Angela Chi Chao ◽  
Zhenyu Du
Keyword(s):  
Prediction Model ◽  
Real Time ◽  
High Frequency ◽  
Prediction Accuracy ◽  
Low Frequency ◽  
Futures Market ◽  
Chinese Economy ◽  
Commodity Futures ◽  
Explanatory Variables ◽  
Daily Data

This article analyses the transmission path of the international commodity futures market’s impact on the Chinese economy. We use the MIDAS model and daily data to predict China’s CPI in real time. Empirical analysis results show that (1) the influence of high-frequency explanatory variables on low-frequency CPI is different. The optimal lag orders of domestic high-frequency variables are all around 23, which can be regarded as one month in practice, indicating that their CPI influence takes one month to show. (2) Both the univariate MIDAS model and the multivariate MIDAS combined prediction model have good performance in prediction accuracy. (3) The predicted results of the multivariate MIDAS combined prediction model for CPI in China’s normal months are relatively excellent. However, when exceptional circumstances occur, the prediction results will show a specific deviation, and the prediction accuracy will also be reduced. Finally, some feasible suggestions are put forward according to the research results.

An Empirical Analysis of Market Efficiency and Price Discovery in Indian Commodity Market

2018 ◽  
Vol 19 (3) ◽  
pp. 771-789 ◽  
Author(s):  
Shashi Gupta ◽  
Himanshu Choudhary ◽  
D. R. Agarwal
Keyword(s):  
Error Correction ◽  
Market Efficiency ◽  
Price Discovery ◽  
Correction Term ◽  
Futures Market ◽  
Commodity Futures ◽  
Spot Price ◽  
Futures Prices ◽  
Short Term ◽  
Important Indicator

The present article is an attempt to empirically investigate the long-term market efficiency and price discovery in Indian commodity futures market. The study has been conducted with eight commodities which include two agricultural commodities, two industrial commodities, two precious metal and two energy commodities. Sophisticated statistical methods like restricted cointegration and vector error correction model (VECM) are used to analyse the spot and futures prices time series. Restricted cointegration test shows that near-month futures prices for all the commodities are cointegrated with the spot prices but futures prices of all the commodities are inefficient to predict the future spot price. Indian commodity futures market evidenced as the thinly traded market (Kumar & Pandey, 2013, Journal of Indian Business Research, 5(2), 101–121) rejects the null hypothesis of efficiency and unbiasedness for all the eight commodities which reconfirms the result of Fortenbery and Zapata (1997, Journal of Futures Markets, 17(3), 279–301). The presence of short-term biases in the Indian futures market is evidenced in the results of VECM model which indicates the presence of informational efficiency. The statistically significant value of past prices of spot and futures confirm the short-term inefficiency and biasedness. The significant value of error correction term (ECT) of futures prices suggests that commodity futures are the most important indicator of commodity price movements. The important implication of the results is for market traders. They can use the futures prices to discover the new equilibrium and earn profits by transmitting it to the spot market. The better understanding of the interconnectedness of these market would be useful for policymakers who try to establish stability in the financial markets.

Price Discovery and Market Efficiency of Commodities Futures Market in India- A Cointegration and Causality Analysis

2015 ◽  
Vol 5 (2) ◽  
Author(s):  
Shaik Masood ◽  
T. Satyanarayana Chary
Keyword(s):  
Market Efficiency ◽  
Price Discovery ◽  
Spot Market ◽  
Futures Market ◽  
Commodity Futures ◽  
Causality Analysis ◽  
Long Run ◽  
Integration Test ◽  
Short Run

The paper studies the Indian commodity futures market in order to determine the price discovery, long run market efficiency and short run dynamics in futures market using by time series analysis tools. To test the market efficiency and long run equilibrium, tools like Engle and Granger co-integration test (1987) and Johansen co-integration test (1988) have been applied. The Granger Causality (1969) test is used test the market efficiency to infer cause and affect relationship between spot and futures market in India. To examine efficiency of commodity futures and spot market the MCXs1 four spot and futures commodity indices data are used. The paper observes that the role of commodity futures is very significant in price discovery, and improving efficiency of the market.

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