Can the Chinese base Metal Futures Market become an Global Leading Market? : Measuring Information Spillover Effects between SHFE and LME Before and After Implementing SHFE Night Trading Session)

2019 ◽  
Vol 32 (5) ◽  
pp. 1793-1819
Author(s):  
Hyun-Bock Lee ◽  
Cheol-Ho Park
Keyword(s):  
Base Metal ◽  
Spillover Effects ◽  
Futures Market ◽  
Before And After ◽  
Information Spillover

An empirical study on information spillover effects between the Chinese copper futures market and spot market

2008 ◽  
Vol 387 (4) ◽  
pp. 899-914 ◽  
Author(s):  
Xiangli Liu ◽  
Siwei Cheng ◽  
Shouyang Wang ◽  
Yongmiao Hong ◽  
Yi Li
Keyword(s):  
Empirical Study ◽  
Spillover Effects ◽  
Spot Market ◽  
Futures Market ◽  
Information Spillover

scholarly journals Information Spillover Effects of Real Estate Markets: Evidence from Ten Metropolitan Cities in China

2021 ◽  
Vol 14 (6) ◽  
pp. 244
Author(s):  
Junjie Li ◽  
Li Zheng ◽  
Chunlu Liu ◽  
Zhifeng Shen
Keyword(s):  
Real Estate ◽  
Rapid Development ◽  
House Price ◽  
Principal Component ◽  
Spillover Effects ◽  
Real Estate Markets ◽  
The Real ◽  
The Real Estate ◽  
Information Interaction ◽  
Information Spillover

With the rapid development of information communication technology and the Internet, information spillover between cities in real estate markets is becoming more frequent. The influence of information spillover in real estate markets is becoming more and more prominent. However, the current research of information spillover between cities is still relatively insufficient. In view of this research gap, this paper builds a research framework on the information conduction effect in the real estate markets of 10 Chinese cities by using Baidu search data, text mining and principal component analysis and analyzes the information interaction and dynamic influence of the real estate markets in each city by using the vector autoregressive model empirically. The results show that the information interaction among the real estate markets in each city has a network pattern and there is a significant two-way information spillover effect in most cities. When the “information distance” becomes closer, the information interaction between the markets of the cities becomes closer and it is easier for cities to influence each other. The results help to explain the information spillover mechanism behind the house price spillover and to improve the ability to predict and analyze the information spillover process in real estate markets.

Analysis of risk spillover effect of copper option in China

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Wuyi Ye ◽  
Yiqi Wang ◽  
Jinhai Zhao
Keyword(s):  
Value At Risk ◽  
Risk Model ◽  
Spillover Effect ◽  
Spillover Effects ◽  
Futures Market ◽  
Content Type ◽  
Conditional Autoregressive ◽  
Derivative Markets ◽  
The Impact ◽  
Risk Spillover Effects

Purpose The purpose of this paper is to compare the changes in the risk spillover effects between the copper spot and futures markets before and after the issuance of copper options, analyze the risk spillover effects between the three markets after the issuance of the options and can provide effective suggestions for regulators and investors who hedge risks. Design/methodology/approach The MV-CAViaR model is an extended form of the vector autoregressive model (VAR) to the quantile model, and it is also a special form of the MVMQ-CAViaR model. Based on the VAR quantile model, this model has undergone continuous promotion of the Conditional Autoregressive Value-at-Risk Model (CAViaR) and the Multi-quantile Conditional Autoregressive Value-at-Risk Model (MQ-CAViaR), and finally got the current form of the model. Findings The issuance of options has led to certain changes in the risk spillover effect between the copper spot and its derivative markets, and the risk aggregation effect in the futures market has always been significant. Therefore, when supervising the copper product market and investors using copper derivatives to avoid market risks, they need to pay attention to the impact of futures on the spot market, the impact of options on the futures market and the risk spillover effects of spot and futures on the options market. Practical implications The empirical results of this paper can be used to hedge market risk investment strategies, and the changes in market relationships also provide an effective basis for the supervision of the copper product market by the supervisory authority. Originality/value It is the first literature research to discuss the risk and the impact of spillover effects of copper options on China copper market and its derivative markets. The MV-CAViaR model can capture the mutual risk influence between markets by modeling multiple markets simultaneously.

scholarly journals Impact of Food Contamination on Brands: A Demand Systems Estimation of Peanut Butter

2012 ◽  
Vol 41 (3) ◽  
pp. 327-339 ◽  
Author(s):  
Rafael Bakhtavoryan ◽  
Oral Capps ◽  
Victoria Salin
Keyword(s):  
Time Series Data ◽  
Peanut Butter ◽  
Food Contamination ◽  
Spillover Effects ◽  
Series Data ◽  
Peter Pan ◽  
Price Elasticities ◽  
Food Borne ◽  
Before And After ◽  
Food Borne Illness

A 2007 food-borne illness incident involving peanut butter is linked with structural change in consumer demand. Compensated and uncompensated own- and cross-price elasticities and expenditure elasticities were calculated for leading brands before and after the product recall using the Barten synthetic model and weekly time-series data from 2006 through 2008. Statistically significant differences in price elasticities for the affected brand, Peter Pan, were absent. After a period of 27 weeks, this brand essentially recovered from the food safety crisis. Significant differences in price elasticities were evident among non-affected brands. Hence, spillover effects and heightened competition are associated with the recall.

Is China the price taker in soybean futures?

2015 ◽  
Vol 7 (3) ◽  
pp. 389-404 ◽  
Author(s):  
Bruce Jianhe Liu ◽  
Yubin Wang ◽  
Jingjing Wang ◽  
Xin Wu ◽  
Shu Zhang
Keyword(s):  
Genetically Modified ◽  
Spillover Effects ◽  
Futures Market ◽  
Error Distribution ◽  
Conditional Heteroskedasticity ◽  
Subprime Crisis ◽  
Genetically Modified Soybean ◽  
Content Type ◽  
Generalized Error Distribution ◽  
Futures Price

Purpose – The purpose of this paper is to examine whether China is still a passive price taker from the US soybean futures, or instead domestic futures market has developed certain degrees of pricing power through time. The finding helps to identify the importance of China soybean futures in the perspective of portfolio selection for international futures traders. If China soybean futures market is no longer a price taker after the subprime crisis, traders need to include it as a separate category in their portfolio. Design/methodology/approach – This paper uses exponential generalized autoregressive conditional heteroskedasticity-generalized error distribution (EGARCH-GED) and generalized autoregressive conditional heteroskedasticity-generalized error distribution (GARCH-GED) models to test spillover effects between Dalian Commodity Exchange (DCE) and Chicago Board of Trade (CBOT) soybean futures. The authors divide daily samples into three subperiods based on the subprime crisis. Three research questions – whether China is still the price taker, the importance of Chinese soybean futures in international futures portfolio selection, and the influences of subprime crisis on soybean futures volatility relationship – are examined by comparing estimation results through time and different contracts. Findings – The spillover effect from CBOT soybean futures to DCE No. 1 soybean futures becomes weaker through time. China is no longer a soybean futures price taker after the subprime crisis. The authors also find the shocks of bearish news on DCE soybeans are greater than those of bullish news. Potential volatility of DCE in long positions is bigger than that in short positions. Practical implications – China is the largest soybean importer. DCE is a very important futures market for non-genetically modified soybeans. It is necessary for both international and domestic futures traders to understand the changes in international soybean futures price relationship and take corresponding strategies. It is also important for market to realize that DCE soybean futures are to a less degree price taker after the subprime crisis. Originality/value – The paper applies EGARCH-GED and GARCH-GED models to identify changes in spillover effects before, during, and after the subprime crisis. Different from other studies, this paper finds after the subprime crisis, China is no longer the soybean futures price taker. This paper also compares the spillover effects of non-genetically modified soybean futures (No. 1 soybean futures) with genetically modified soybean futures (No. 2 soybean futures).

How Does COVID-19 Affect the Volatility Spillover Between the Exchange Rate and the Export-oriented Businesses in Iran?

2022 ◽  
pp. 097215092110606
Author(s):  
Zahra Honarmandi ◽  
Samira Zarei
Keyword(s):  
Exchange Rate ◽  
Stock Exchange ◽  
Spillover Effects ◽  
Garch Models ◽  
Volatility Spillover ◽  
Exogenous Shocks ◽  
Risk Period ◽  
Before And After ◽  
The Exchange Rate ◽  
Fractal Market Hypothesis

This study concentrates on examining the volatility spillover effects between the exchange rate (IRR to USD) and the leading export-oriented industries (i.e., petrochemical, basic metals and minerals) in Tehran Stock Exchange before and after the COVID-19 pandemic. Using DCC- and asymmetric DCC-GARCH approaches, the data sample (from 15 December 2018 to 24 April 2021) has been partitioned into two sub-samples: before and after the official announcement of COVID-19 outbreak. The results demonstrate that from the pre- to post-COVID-19 periods, first, the average returns of all industries have sharply fallen; second, the volatility of all variables has been significantly augmented in different horizons; third, for all industries, not only has the fractal market hypothesis approved in both separated periods, but also analysing the values of the fractional difference parameter, together with the outcomes of GARCH models, supports in the higher-risk post-COVID-19 period, wherein the effects of exogenous shocks last longer than their impacts in the alternative lower-risk period. Furthermore, our investigations demonstrate that the asymmetric spillover (based on the ADCC-GARCH models) in both pre- and post-COVID-19 periods are confirmed in all three industries, except for minerals after the novel coronavirus.Ultimately, the results not only corroborate the increase in the volatility spillover effects right after the COVID-19 but also substantiate that the exchange rate contributes most of the spillover effects into the petrochemical and minerals industries, which have been almost twice as much as those of the basic metals.

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