Dynamic efficiency of China’s commodity futures market through the lens of high frequency data

2021 ◽  
pp. 2141012
Author(s):  
He Chengying ◽  
Huang Ke ◽  
Wen Zhang ◽  
Huang Qingcheng
Keyword(s):  
Time Window ◽  
Price Volatility ◽  
Warning Signal ◽  
Futures Market ◽  
Mean Value ◽  
Commodity Futures ◽  
Permutation Entropy ◽  
Biased Random Walk ◽  
Intraday Data ◽  
The Impact

In this paper, we use the permutation entropy algorithm to derive the static and dynamic permutation entropy of commodity futures, and to evaluate the effectiveness of main products in China’s commodity futures market. The intraday data of six varieties belonging to six categories in China’s commodity futures market are taken as samples. We find the following: (1) The return distribution of the main varieties shows high peaks, fat tails and asymmetry, and follows the biased random walk distribution characteristics; (2) The permutation entropy of all varieties decreases significantly in the same time window, during which the price volatility of major commodity markets rises. And the time window coincides with the impact time of COVID-19 epidemic; (3) By comparing the distribution of permutation entropy of main varieties in different stages of event shock, we found that the mean value of permutation entropy decreases significantly during the process of event shock, and the price fluctuates greatly. Therefore, the significant decrease of permutation entropy is a valuable warning signal for regulators and investors.

scholarly journals The Impact of Futures Price Volatility to Spot Market : Case of Coffee in Indonesia

2019 ◽  
Vol 15 (1) ◽  
pp. 1-15 ◽  
Author(s):  
Anis Erma Wulandari ◽  
Harianto Harianto ◽  
Bustanul Arifin ◽  
Heny K Suwarsinah
Keyword(s):  
Exchange Rate ◽  
Price Volatility ◽  
Spot Market ◽  
Futures Market ◽  
Spot Price ◽  
Price Risk ◽  
Price Inflation ◽  
Spot Prices ◽  
Futures Price ◽  
The Impact

Indonesia is the world 4th largest coffee producer after Brazil, Vietnam and Colombia with export potential and higher national consumption concluded in 2017 while the coffee production was relatively stagnant. This was led the producer to not only the production risk but also the price risk which then emphasize the importance of futures markets existence as price risk management. This study is performed to examine the impact of futures price volatility to spot market using ARCH-GARCH toward primary data of coffee futures and spot prices of 1172 trading days starting from January 2014 to June 2018. The ARCH-GARCH analysis result indicates that futures price volatility and monetary variables are impacting the volatility of spot price. Arabica spot price volatility is impacted by volatility of Arabica futures price, inflation and exchange rate while Robusta spot price is impacted by Robusta futures price volatility and exchange rate. This is confirming that futures market plays dominant role in spot price discovery. Local futures and spot prices are also found to be significantly influenced by volatility of offshore futures prices which indicates that emerging country futures market is actually influenced by offshore futures market which the price itself used as price reference.

The Impact of Trading Volumes by Trader Types in the KOSPI200 Futures Market

2003 ◽  
Vol 11 (2) ◽  
pp. 1-26
Author(s):  
Chang Hyeon Yun ◽  
Lee Seong Gu
Keyword(s):  
Price Volatility ◽  
Futures Market ◽  
Stock Index ◽  
Stock Index Futures ◽  
Foreign Investors ◽  
Index Futures ◽  
Persistent Effect ◽  
Trading Volumes ◽  
The Impact

In this study we examine the relationships between trader-type-specific trading volumes and the price volatility of the KOSPI200 stock index futures over the period of July 1997 through December 2001. The principal findings of this study are that the changes in trading volumes by foreign investors are positively associated with the return and the volatility of the index futures market. When trading volumes are decomposed into expected and unexpected components, unexpected shocks have more persistent effect on the volatility of the market than expected component. Meanwhile, individuals and domestic commercial investor seem to follow the lead made by foreign investors.

scholarly journals An Empirical Analysis of the Price Volatility Characteristics of China’s Soybean Futures Market Based on ARIMA-GJR-GARCH Model

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Yang Xu ◽  
Zhihao Xia ◽  
Chuanhui Wang ◽  
Weifeng Gong ◽  
Xia Liu ◽  
...  
Keyword(s):  
Trading Volume ◽  
Price Volatility ◽  
Futures Market ◽  
Conditional Variance ◽  
Agricultural Product ◽  
Price Fluctuation ◽  
Open Interest ◽  
Volume Coefficient ◽  
The Impact ◽  
The Relationship

As the main force in the futures market, agricultural product futures occupy an important position in the China’s market. Taking the representative soybean futures in Dalian Commodity Futures Market of China as the research object, the relationship between price fluctuation characteristics and trading volume and open position was studied. The empirical results show that the price volatility of China’s soybean futures market has a “leverage effect.” The trading volume and open interest are divided into expected parts and unexpected parts, which are added to the conditional variance equation. The expected trading volume coefficient is estimated. Also, the estimated value of the expected open interest coefficient is, respectively, smaller than the estimated value of the unexpected trading volume coefficient and the estimated value of the unexpected open interest coefficient. Therefore, the impact of expected trading volume on the price fluctuation of China’s soybean futures market is less than that of unexpected trading volume on the price of soybean futures market. This paper adds transaction volume as an information flow to the variance of the conditional equation innovatively and also observes transaction volume as the relationship between conditional variance and price fluctuations.

scholarly journals Is Futurization the Culprit for the Violent Fluctuation in China’s Apple Spot Price?

Agriculture ◽  
2021 ◽  
Vol 11 (4) ◽  
pp. 342
Author(s):  
Lin Xie ◽  
Jiahua Liao ◽  
Haiting Chen ◽  
Xuefei Yan ◽  
Xinyan Hu
Keyword(s):  
Price Volatility ◽  
Futures Market ◽  
Agricultural Products ◽  
Spot Price ◽  
Agricultural Product ◽  
Interrupted Time Series Analysis ◽  
Product Price ◽  
Price Fluctuation ◽  
Spot Prices ◽  
The Impact

China aims to utilize the futures market to stabilize agricultural product price fluctuation by quantifying the effects of risk transfer and price discovery. However, the role of futurization has been questioned and even posited as the cause of drastic fluctuations in spot market prices. This research aims to clarify the impact of futurization on the price fluctuation of agricultural products and to provide policy reference for the development of the agricultural futures market through the research. Here, we examine the spot price data for apples and use Interrupted time-series analysis (ITSA) and GARCH models to estimate the impact of apple futures on the volatility of spot prices. Our findings demonstrate that the launch of China’s apple futures did not increase the volatility of apple spot prices; that is, futurization was not the cause of skyrocketing apple spot prices. In the long term, our results suggest that futures will help reduce the volatility of apple spot prices and that the introduction of futures will ultimately reduce the price volatility of agricultural products.

scholarly journals Analysis of Capital Flow in Commodity Futures Market Based on SVM

2018 ◽  
Vol 10 (8) ◽  
pp. 28
Author(s):  
Zi-ang Lin ◽  
Shaozhen Chen ◽  
Hongtao Liang ◽  
Hong Zhang
Keyword(s):  
Time Window ◽  
Principal Component ◽  
Futures Market ◽  
Capital Flow ◽  
Kernel Functions ◽  
Commodity Futures ◽  
Futures Contracts ◽  
Support Vector ◽  
Analysis Method

Commodity futures are futures contracts based on the physical commodities. Unlike commodity stocks, which must be “bought first and then sold”, commodity futures can also be “sold first and then bought”. Therefore, it is not possible to directly use the formula of capital flow in the stock market to characterize the capital flow in futures contracts. In this paper, the principal component analysis method is used to construct the principal component factors based on the K-line basic market data and one based on the K-line index data. Then the factors mentioned above are cross-validated using the Holdout verification form to generate the training set and test of the support vector machine. Then, this paper applies genetic algorithm to optimize the penalty parameters and kernel functions of SVM, and obtains the parameters with the highest accuracy of classification and prediction of capital flow. Finally, this paper uses the traversal algorithm to find the time window with the highest accuracy of the SVM classification to predict the capital flow. The research results of this paper show that the SVM-based classification of capital flow in commodity futures market is highly accurate.

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