Learning Dynamic Causal Relationships Among Sugar Prices

In this paper, we are interested in exploring the dynamic causal relationships among two sets of three variables in different quarters. One set is futures sugar closing price in Zhengzhou futures exchange market （ZC）, spot sugar price in Zhengzhou （ZS） and futures sugar closing price in New York fut...

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Bibliographic Details
Published in:Acta Mathematicae Applicatae Sinica 2017-07, Vol.33 (3), p.809-818
Main Authors: Xu, Jing, Tong, Xing-wei, Wang, Fang, Chen, Jian-ping
Format: Article
Language:English
Subjects:
Applications of Mathematics
Bayesian analysis
Data analysis
Exchanging
Futures
Markets
Math Applications in Computer Science
Mathematical and Computational Physics
Mathematical models
Mathematics
Mathematics and Statistics
Real variables
Sugar industry
Theoretical
交易所
因果关系
平均方法
数据分析
模型选择
现货价格
贝叶斯模型
食糖
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Summary:In this paper, we are interested in exploring the dynamic causal relationships among two sets of three variables in different quarters. One set is futures sugar closing price in Zhengzhou futures exchange market （ZC）, spot sugar price in Zhengzhou （ZS） and futures sugar closing price in New York futures exchange market（NC） and the other includes futures sugar opening price in Zhengzhou （ZO）, ZS and NC. For each quarter, we first use Bayesian model selection to obtain the optimal causal graph with the highest BD scores and then use Bayesian model averaging approach to explore the causal relationship between every two variables. From the real data analysis, the two conclusions almost coincide, which shows that the two methods are practical.
ISSN:0168-9673
1618-3932
DOI:10.1007/s10255-017-0699-5