人民币汇率变动与上市公司外汇风险暴露——基于双变量GJR-GARCH模型的实证分析
The RMB Exchange Rate Fluctuation and Foreign Exchange Risk Exposure of Listed Companies—The Empirical Analysis Based on Bivariate GJR-GARCH Model
摘要: 近年来,中国紧密融入全球经济体系,人民币汇率的持续波动使得企业在市场中面临着不可避免的汇率风险。本文基于2022年中国沪深A股市场16个典型行业中的3066家上市企业,利用双变量GJR-GARCH模型探究了人民币兑美元、兑欧元和兑日元三种外币的汇率波动对企业的汇率风险暴露产生的影响。结果显示:(1) 人民币兑美元、兑欧元和兑日元汇率波动通过影响企业的营业成本间接导致企业承受汇率风险,且美元与欧元汇率波动与企业汇率风险暴露呈正相关,日元汇率波动则相反;(2) 三种主要货币的非对称性汇率风险暴露分别占企业总数的97.62%、93.47%和91.81%;(3) 不同外币兑人民币汇率波动对企业的影响程度存在差异,大部分企业经历了人民币升值而带来的损失;(4) 对外投资占比高的企业受到外汇风险暴露的影响更大;通过这些结论和政策启示,帮助企业与政策更好地理解和应对全球化经济中的挑战。
Abstract: In recent years, China has been closely integrated into the global economic system. Moreover, the ongoing volatility in the RMB exchange rate subjects businesses to unavoidable currency risks within the market. In this paper, 3066 listed companies in 16 typical industries of China’s Shanghai and Shenzhen A-share markets in 2022 are taken as sample. Additionally, we utilize the bivariate GJR-GARCH model to conduct an in-depth investigation into how fluctuations in the RMB exchange rate concerning the US dollar, euro, and yen influence the exposure of enterprises to currency risk. It turns out that: (1) The fluctuations in the RMB exchange rate against the USD, EUR, and JPY indirectly impact enterprises’ exposure to currency risk by influencing their operational expenses, and the exchange rate fluctuations of USD and EUR are positively correlated with the exchange rate risk exposure of enterprises, while the exchange rate fluctuations of JPY are opposite. (2) Asymmetrical exchange rate risk exposure in the case of the three major currencies was predominant, accounting for 97.62%, 93.47%, and 91.81% of the total number of enterprises, respectively. (3) The influence of RMB exchange rate fluctuations against different foreign currencies on enterprises varies, with a majority of businesses suffering losses due to RMB appreciation. (4) Enterprises with a higher proportion of foreign investment are more affected by foreign exchange risk exposure; through these conclusions and policy implications, enterprises and policies can better understand and respond to the challenges in a globalized economy.
文章引用:李鑫亚. 人民币汇率变动与上市公司外汇风险暴露——基于双变量GJR-GARCH模型的实证分析[J]. 电子商务评论, 2024, 13(2): 1384-1398. https://doi.org/10.12677/ecl.2024.132170

参考文献

[1] 张明志, 季克佳. 人民币汇率变动对中国制造业企业出口产品质量的影响[J]. 中国工业经济, 2018(1): 5-23.
[2] 魏荣桓. 人民币汇率的双向波动及失衡程度——基于行为均衡模型的协整研究[J]. 经济管理, 2017, 39(11): 169-184.
[3] 陈奉先, 丁美琳. 人民币汇率变动与上市公司外汇风险暴露——以京津冀地区上市公司为例[J]. 会计与经济研究, 2020, 34(5): 107-127.
[4] 高程, 部彦君. 大国崛起中“以经稳政”的限度、空间和效力——对“经济压舱石”理论的反思与重构[J]. 世界经济与政治, 2022(10): 4-41, 164-165.
[5] 张策, 梁柏林, 何青. 人民币国际化与中国企业的汇率风险[J]. 中国工业经济, 2023(3): 58-76.
[6] 谢富胜, 匡晓璐. 制造业企业扩大金融活动能够提升利润率吗?——以中国A股上市制造业企业为例[J]. 管理世界, 2020, 36(12): 13-25.
[7] 陈俊, 徐怡然, 董望, 等. 汇率政策、内部控制与风险对冲——基于“8.11汇改”冲击的市场感知视角[J]. 管理世界, 2023, 39(8): 40-59, 95.
[8] 宋科, 侯津柠, 夏乐, 等. “一带一路”倡议与人民币国际化——来自人民币真实交易数据的经验证据[J]. 管理世界, 2022, 38(9): 49-62.
[9] 赵峰, 祖博男, 程悦. 企业国际化是外汇风险对冲的动因吗[J]. 国际贸易问题, 2019(8): 157-174.
[10] Jorion, P. (1990) The Exchange-Rate Exposure of US Multinationals. Journal of Business, 63, 331-345. [Google Scholar] [CrossRef
[11] Bartov, E. and Bodnar, G.M. (1994) Firm Valuation, Earnings Expectations, and the Exchange-Rate Exposure Effect. The Journal of Finance, 49, 1755-1785. [Google Scholar] [CrossRef
[12] Lee, C.C. and Wen, X.L. (2023) How Does Exchange Rate Policy Uncertainty Affect Corporate Performance: Evidence from China. Emerging Markets Finance and Trade, 59, 3060-3075. [Google Scholar] [CrossRef
[13] 袁凯彬, 李万利, 张伟俊. 人民币参与国际结算能否激励出口企业创新?——基于跨境贸易人民币结算试点的研究[J]. 金融研究, 2023(6): 94-112.
[14] Muller, A. and Verschoor, W.F.C. (2007) Asian Foreign Exchange Risk Exposure. Journal of the Japanese and International Economies, 21, 16-37. [Google Scholar] [CrossRef
[15] Feng, F., Lin, F.Q. and Wang, T.Y. (2022) Exchange Rate Appreciation and Outward FDI in China. The Journal of International Trade & Economic Development, 31, 995-1016. [Google Scholar] [CrossRef
[16] Dai, Y.K., Li, B.X. and Xu, Y.F. (2023) International Transmission of Exchange Rate Volatility: Evidence from FIEs’ Investments in China. Journal of Multinational Financial Management, 68, Article ID: 100797. [Google Scholar] [CrossRef
[17] 张策, 王文清, 刘尔卓, 等. 汇率风险和中国产业的国际竞争[J]. 经济理论与经济管理, 2022, 42(5): 36-49.
[18] Xie, H.B., Zhou, M. and Ruan, T.H. (2020) Pricing VIX Futures under the GJR-GARCH Process: An Analytical Approximation Method. The Journal of Derivatives, 27, 77-88. [Google Scholar] [CrossRef
[19] 孙晶. 我国货币市场的政策传导渠道及其效应观察[J]. 改革, 2010(11): 65-73.
[20] 唐韬, 谢赤. 基于双变量GJR-GARCH模型的汇率风险暴露研究——关于对外投资企业的实证分析[J]. 社会科学家, 2015(2): 79-84.
[21] 刘超, 张瑞雪, 朱相宇. 金融风险与宏观经济风险的交互行为研究[J]. 管理评论, 2022, 34(2): 46-61.
[22] 张晓燕, 姬家豪. 金融科技与金融监管的动态匹配对金融效率的影响[J]. 南开管理评论, 2023, 26(1): 43-56.
[23] 杨达. 人民币汇率变动对中国企业对外直接投资风险的影响研究[J]. 东北大学学报(社会科学版), 2020, 22(6): 24-30.
[24] 姜英兵, 班旭. 社会信任与股权资本成本[J]. 经济经纬, 2021, 38(6): 150-160.
[25] 赵晓涛, 邱斌. 汇率波动性、汇率水平与异质性企业出口[J]. 财贸研究, 2020, 31(8): 38-51, 98.
[26] 綦建红, 尹达, 刘慧. 经济政策不确定性如何影响企业出口决策?——基于出口频率的视角[J]. 金融研究, 2020(5): 95-113.
[27] 温忠麟, 方杰, 谢晋艳, 等. 国内中介效应的方法学研究[J]. 心理科学进展, 2022, 30(8): 1692-1702.