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商品期货市场中的频域“涟漪效应”——一种基于避险视角的双向“涟漪”指数方法

Frequency Domain“Ripple Effect”in Commodity Futures Markets:A Bidirectional“Ripple”Index Method from a Hedging Perspective
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摘要 准确识别商品期货市场中的网络外溢和“涟漪效应”是防范金融市场系统性风险的重要依据。鉴于此,提出一种基于避险视角的双向“涟漪”指数检验方法,利用5分钟高频数据和小波包分解法,从频域视角检验商品期货市场中的双向“涟漪效应”。研究发现,商品期货在样本期内的平均风险传染效应均大于避险效应,在中频尺度下,避险型“涟漪效应”更加显著。玉米、豆油、动力煤、黄金分别为低频、中低频、中频和高频尺度下的避险中心,铁矿以及产业链相关的甲醇、乙烯和焦炭在各时间尺度下均为相对稳定的强风险中心。此外,股灾和贸易摩擦时期的避险效应存在明显的滞后性。因此,应提升市场透明度和公信力,以有效降低商品期货的异质性波动风险,防止由此产生的“涟漪效应”。 Accurately identifying network spillovers and"ripple effects"in commodity futures markets is crucial for mitigating systemic risks in financial markets.In light of this,a bidirectional"ripple"index test method based on a hedging perspective is proposed.Utilizing 5-minute high-frequency data and wavelet packet decomposition,this study examined the bidirectional"ripple effects"in commodity futures markets from a frequency domain perspective.The study revealed that,during the sample period,the average risk contagion effects in commodity futures were greater than the hedging effects.At medium frequency scales,hedging-oriented"ripple effects"were more pronounced.Corn,soybean oil,thermal coal,and gold served as hedging centers at low,lower-medium,medium,and high frequency scales,respectively.Iron ore,along with industry chain-related commodities such as methanol,ethylene,and coke,remained relatively stable strong risk centers across all time scales.Additionally,the hedging effects during stock market crashes and trade friction periods exhibited significant lag effects.Therefore,it is recommended to enhance market transparency and credibility to effectively reduce heterogeneous volatility risks in commodity futures and prevent the ensuing"ripple effects."
作者 张旭 杜钰婷 刘晓星 Zhang Xu;Du Yuting;Liu Xiaoxing
出处 《金融经济学研究》 北大核心 2024年第4期22-37,共16页 Financial Economics Research
基金 国家社会科学基金项目(23BJL106) 国家自然科学基金项目(71903097) 江苏省社会科学基金项目(20EYC011) 中国博士后科学基金特别资助项目(2021T140335) 中国博士后科学基金面上资助项目(2021M691635)。
关键词 商品期货 涟漪效应 双向检验 频域分析 高频数据 双向“涟漪”指数方法 commodity futures ripple effect bidirectional testing frequency domain analysis high-frequency data
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