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作 者:吴甜甜 周雨田[1,2] WU Tiantian;CHOU Ray Yeutien(Jinhe Center for Economic Research,Xi'an Jiaotong University,Xi'an710049,China;Institute of Economics,Academia Sinica,Taipei 115201,China)
机构地区:[1]西安交通大学金禾经济研究中心,西安710049 [2]台湾“中央研究院”经济研究所,中国台北115201
出 处:《云南财经大学学报》2024年第11期67-85,共19页Journal of Yunnan University of Finance and Economics
摘 要:在国际粮食安全问题日益突出的背景下,识别和监管中国大豆市场面临的外部风险具有重要的现实意义。基于极差波动率,运用TVP-FAVAR-DY模型,研究了中美豆类期货市场特质性波动溢出效应,并揭示了时频视角下豆类期货波动溢出效应的异质性。研究发现,相对于收益率波动率,极差波动率能更好地捕捉极端波动风险;特质性波动成分对原序列的解释力强于公共波动成分;美国大豆期货在时域和高频波动溢出网络中处于主导地位,而中国豆油期货在中频和低频波动溢出网络中处于主导地位;时域波动溢出效应与高频结果基本保持一致,对中频和低频波动溢出效应的刻画能力有限;除了美国大豆期货,美国豆粕期货也成为中短期重要的波动溢出传递者。相关短线交易者、长期投资者和风险监管部门,均有必要增加对极差波动率、特质性波动成分和频域视角的关注。Under the background of increasingly prominent international food insecurity issues,it is of great practical significance to identify and monitor the external risks faced by China's soybean market.Based on extreme value volatility,the paper uses the TVP-FAVAR-DY model to study the idiosyncratic volatility spillover effect of legume futures markets in China and the United States,and reveals the heterogeneity of the volatility spillover effect of legume futures from time-frequency perspective.Research finds that compared with return volatility,range volatility can better capture extreme volatility risks.The idiosyncratic volatility component has a stronger explanatory power on the original sequence than common volatility component.US soybean futures dominate in both the time domain and high-frequency volatility spillover networks,while China's soybean oil futures dominate in medium and low-frequency volatility spillover networks.The volatility spillover effects in the time domain are basically consistent with the highfrequency results,and the ability to depict the volatility spillover effect in the medium and lowfrequency is limited.In addition to US soybean future,US soybean meal future has also become an important transmitter of volatility spillover in the short and medium term.It is necessary for short-term traders,long-term investors,and risk regulatory authorities to increase their attention to extreme value volatility,idiosyncratic volatility components,and frequency domain perspectives.
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