商品价格对全球系统性风险重要吗?多变量选择的证据

Q1 Mathematics
Mikhail Stolbov , Maria Shchepeleva
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引用次数: 0

摘要

我们在 2004 年 1 月至 2021 年 12 月期间的一整套商品价格中找出了以条件资本缺口(SRISK)为代表的全球系统性风险的稳健预测因素。该搜索基于一系列 ML 变量选择算法,适用于存在控制变量的价格水平和价格冲击,包括 SRISK 的第一个滞后期、世界工业生产、全球经济政策的不确定性、地缘政治风险以及全球货币和宏观审慎政策的立场。我们发现,在预测全球系统性风险方面,这些控制因素的作用超过了商品价格。就商品本身而言,农产品(包括鸡肉、香蕉、牛肉、茶叶、可可等食品)价格比能源商品(如天然气和石油价格)价格更能预测全球系统性风险。农产品的金融化、生物能源的扩张以及造成全球系统性风险的主要经济体(如中国)对特定商品的依赖性是我们的主要发现。我们还记录了大多数商品价格与系统性风险之间的正向联系。因此,监控商品价格以避免其失衡增长,对于遏制全球系统性金融风险至关重要。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Do commodity prices matter for global systemic risk? Evidence from ML variable selection
We identify robust predictors of global systemic risk proxied by conditional capital shortfall (SRISK) among a comprehensive set of commodity prices for the period between January 2004 and December 2021. The search is based on a battery of ML variable selection algorithms which apply both to price levels and price shocks in the presence of control variables, including the first lag of SRISK, world industrial production, global economic policy uncertainty, geopolitical risk as well as the global stance of monetary and macroprudential policies. We find that these controls outweigh commodity prices as the predictors of global systemic risk. Of the commodities themselves, the prices for agricultural commodities, including food, e.g. chicken, bananas, beef, tea, cocoa, are more important predictors of global systemic risk than the prices for energy commodities, e.g. natural gas and oil prices. The financialization of agricultural commodities, bio-energy expansion as well as commodity-specific dependence of the major economies contributing to global systemic risk, e.g. China, account for our main finding. We also document the positive linkage between commodity prices and systemic risk for the majority of commodities. Thus, monitoring commodity prices to avoid their unbalanced growth is of vast importance to curb global systemic financial risk.
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来源期刊
Journal of Finance and Data Science
Journal of Finance and Data Science Mathematics-Statistics and Probability
CiteScore
3.90
自引率
0.00%
发文量
15
审稿时长
30 days
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