Multifractal Detrended Cross-Correlation Analysis on Returns of Soybean Futures and Spot Markets
Authors
Jia Liu1, Hanfei Li2, *, Ping Yu3, Youyi Wu4
1Shanghai Dongzheng Future Co., Ltd, No. 318, Zhongshan South Road, Shanghai, China
2School of Economics and Management, Tongji University, No. 1239 Siping Road, Shanghai, China
3Tianhua College, Shanghai Normal University, No. 1661 Shengxin North Road, Shanghai, China
4The University of Chicago, Chicago, 60611, USA
*Corresponding author.
Email: 1343121813@qq.com
Corresponding Author
Hanfei Li
Available Online 2 December 2022.
- DOI
- 10.2991/978-94-6463-010-7_102How to use a DOI?
- Keywords
- Multifractal Characteristics; Soybean Futures; Soybean Spot; MF-DCCA
- Abstract
Considering that multifractal characteristics widely exists in financial markets, this paper adopts the multifractal detrended cross-correlation analysis (MF-DCCA) method to study the correlation between futures and spot returns in China's soybean market. Based on the data of soybean No. 1 futures and soybean spot price from January 4, 2011 to February 23, 2022, this paper shows that there is a high degree of multifractal cross-correlation between soybean futures and spot returns. Furthermore, this paper proves that the cross-correlation between the two time series are persistent.
- Copyright
- © 2023 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Jia Liu AU - Hanfei Li AU - Ping Yu AU - Youyi Wu PY - 2022 DA - 2022/12/02 TI - Multifractal Detrended Cross-Correlation Analysis on Returns of Soybean Futures and Spot Markets BT - Proceedings of the 2022 International Conference on Artificial Intelligence, Internet and Digital Economy (ICAID 2022) PB - Atlantis Press SP - 1012 EP - 1019 SN - 2589-4919 UR - https://doi.org/10.2991/978-94-6463-010-7_102 DO - 10.2991/978-94-6463-010-7_102 ID - Liu2022 ER -