{"title":"揭示中美动态风险溢出效应:来自农产品期货市场的证据","authors":"Han-Yu Zhu, Peng-Fei Dai, Wei-Xing Zhou","doi":"arxiv-2403.01745","DOIUrl":null,"url":null,"abstract":"Agricultural products play a critical role in human development. With\neconomic globalization and the financialization of agricultural products\ncontinuing to advance, the interconnections between different agricultural\nfutures have become closer. We utilize a TVP-VAR-DY model combined with the\nquantile method to measure the risk spillover between 11 agricultural futures\non the futures exchanges of US and China from July 9,2014, to December 31,2022.\nThis study yielded several significant findings. Firstly, CBOT corn, soybean,\nand wheat were identified as the primary risk transmitters, with DCE corn and\nsoybean as the main risk receivers. Secondly, sudden events or increased eco-\nnomic uncertainty can increase the overall risk spillovers. Thirdly, there is\nan aggregation of risk spillovers amongst agricultural futures based on the\ndynamic directional spillover results. Lastly, the central agricultural futures\nunder the conditional mean are CBOT corn and soybean, while CZCE hard wheat and\nlong-grained rice are the two risk spillover centers in extreme cases, as per\nthe results of the spillover network and minimum spanning tree. Based on these\nresults, decision-makers are advised to safeguard against the price risk of\nagricultural futures under sudden economic events, and investors can utilize\nthe results to construct a superior investment portfolio by taking different\nagricultural product futures as risk-leading indicators according to various\nsituations.","PeriodicalId":501487,"journal":{"name":"arXiv - QuantFin - Economics","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Uncovering the Sino-US dynamic risk spillovers effects: Evidence from agricultural futures markets\",\"authors\":\"Han-Yu Zhu, Peng-Fei Dai, Wei-Xing Zhou\",\"doi\":\"arxiv-2403.01745\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Agricultural products play a critical role in human development. With\\neconomic globalization and the financialization of agricultural products\\ncontinuing to advance, the interconnections between different agricultural\\nfutures have become closer. We utilize a TVP-VAR-DY model combined with the\\nquantile method to measure the risk spillover between 11 agricultural futures\\non the futures exchanges of US and China from July 9,2014, to December 31,2022.\\nThis study yielded several significant findings. Firstly, CBOT corn, soybean,\\nand wheat were identified as the primary risk transmitters, with DCE corn and\\nsoybean as the main risk receivers. Secondly, sudden events or increased eco-\\nnomic uncertainty can increase the overall risk spillovers. Thirdly, there is\\nan aggregation of risk spillovers amongst agricultural futures based on the\\ndynamic directional spillover results. Lastly, the central agricultural futures\\nunder the conditional mean are CBOT corn and soybean, while CZCE hard wheat and\\nlong-grained rice are the two risk spillover centers in extreme cases, as per\\nthe results of the spillover network and minimum spanning tree. Based on these\\nresults, decision-makers are advised to safeguard against the price risk of\\nagricultural futures under sudden economic events, and investors can utilize\\nthe results to construct a superior investment portfolio by taking different\\nagricultural product futures as risk-leading indicators according to various\\nsituations.\",\"PeriodicalId\":501487,\"journal\":{\"name\":\"arXiv - QuantFin - Economics\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-03-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"arXiv - QuantFin - Economics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/arxiv-2403.01745\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - QuantFin - Economics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2403.01745","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Uncovering the Sino-US dynamic risk spillovers effects: Evidence from agricultural futures markets
Agricultural products play a critical role in human development. With
economic globalization and the financialization of agricultural products
continuing to advance, the interconnections between different agricultural
futures have become closer. We utilize a TVP-VAR-DY model combined with the
quantile method to measure the risk spillover between 11 agricultural futures
on the futures exchanges of US and China from July 9,2014, to December 31,2022.
This study yielded several significant findings. Firstly, CBOT corn, soybean,
and wheat were identified as the primary risk transmitters, with DCE corn and
soybean as the main risk receivers. Secondly, sudden events or increased eco-
nomic uncertainty can increase the overall risk spillovers. Thirdly, there is
an aggregation of risk spillovers amongst agricultural futures based on the
dynamic directional spillover results. Lastly, the central agricultural futures
under the conditional mean are CBOT corn and soybean, while CZCE hard wheat and
long-grained rice are the two risk spillover centers in extreme cases, as per
the results of the spillover network and minimum spanning tree. Based on these
results, decision-makers are advised to safeguard against the price risk of
agricultural futures under sudden economic events, and investors can utilize
the results to construct a superior investment portfolio by taking different
agricultural product futures as risk-leading indicators according to various
situations.