详细信息
Early warning of bubbles in the agricultural commodity market: Evidence from LPPLS confidence indicators
文献类型:期刊文献
英文题名:Early warning of bubbles in the agricultural commodity market: Evidence from LPPLS confidence indicators
作者:Xu, Hai-Chuan[1,2];Tan, Yu-Zhen[1];Fan, Han-Xiao[1];Zhou, Wei-Xing[1,2]
机构:[1]East China Univ Sci & Technol, Sch Business, Shanghai 200237, Peoples R China;[2]East China Univ Sci & Technol, Res Ctr Econophys, Shanghai 200237, Peoples R China
年份:2025
卷号:10
期号:2
起止页码:245
外文期刊名:JOURNAL OF MANAGEMENT SCIENCE AND ENGINEERING
收录:WOS:【ESCI(收录号:WOS:001477795300001)】;
基金:We acknowledge financial support from the National Natural Science Foundation of China (71971081, 72171083) .
语种:英文
外文关键词:Bubbles; Early warning; LPPLS; Agricultural commodities
摘要:This study leverages the Log-Periodic Power Law Singularity (LPPLS) confidence indicator to effectively identify bubbles in agricultural commodity markets. We analyze five major grain price indices reported by the International Grains Council (IGC) from January 2000 to April 2023, successfully identifying several notable bubble periods. These include a positive bubble in 2004 driven by decreased food production, a substantial positive bubble during the 2008 global financial crisis, a negative bubble in 2016, and positive bubbles triggered by the COVID-19 pandemic and the Russo-Ukrainian conflict since 2020. As the critical point is approached, the LPPLS confidence indicator exhibits strong early warning capabilities. To verify the model's robustness, we employ the Bai-Perron test for multiple structural breaks, detecting five such breaks in each agricultural commodity price series. LPPLS indicators provide strong early-warning signals prior to these break dates. Finally, we investigate the predictability of price bubbles in the agricultural commodity market. Using a Markov regime-switching model, our findings confirm that the geopolitical risk index possesses significant predictive power for bubble formation. (c) 2025 China Science Publishing & Media Ltd. Publishing Services by Elsevier B.V. on behalf of KeAi Communications Co. Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
参考文献:
正在载入数据...
