基于ARIMA-GARCH与VAR模型的玉米期货收益率波动序列特征与影响因素研究  

A Study on the Characteristics and Influencing Factors of the Volatility Series of Corn Futures Returns Based on ARIMA-GARCH and VAR Models

作　　者：梁皓华 虞雅哲 陈彦如 金煜恒 LIANG Haohua;YU Yazhe;CHEN Yanru;JIN Yuheng(Faculty of Accounting and Finance,Zhuhai College of Beijing Institute of Technology,519000,Zhuhai,Guangdong,China;Business School,Zhuhai College of Beijing Institute of Technology,519000,Zhuhai,Guangdong,China)

机构地区：[1]北京理工大学珠海学院会计与金融学院,广东珠海519000 [2]北京理工大学珠海学院商学院,广东珠海519000

出　　处：《特区经济》2025年第4期67-75,共9页Special Zone Economy

摘　　要：本文主要选取2004年9月至2024年4月大连商品交易所的玉米期货日收盘价数据,对数据进行处理后以该数据为样本建立ARIMA-GARCH模型。其中分别使用GARCH模型分析玉米期货市场的市场效率及玉米期货的价格发现功能;使用EGARCH模型判定玉米期货收益率存在“杠杆效应”,使用GARCH-M模型确定了玉米期货收益率的收益与风险并不存在正相关关系。本文进一步选取2004年至2022年大连商品交易所的玉米月期货收盘价数据和第二产业增加值,以向量自回归模型探讨“杠杆效应”的成因以及拟定工业增加值在“杠杆效应”中的影响并予以佐证。This article mainly selected the daily closing price data of corn futures on the Dalian Commodity Exchange from September 2004 to April 2024,processed the data,and used it as a sample to establish an ARIMAGARCH model.Among them,the GARCH model was used to analyze the market efficiency of the corn futures market and the price discovery function of corn futures;The EGARCH model was used to determine the“leverage effect”in the yield of corn futures,and the GARCH-M model was used to determine that there is no positive correla⁃tion between the return and risk of corn futures.This article further selected the closing price data of corn futures and the added value of the secondary industry from Dalian Commodity Exchange from 2004 to 2022,and used a vector auto-regressive model to explore the causes of the“leverage effect”and formulated the impact of industrial added value on the“leverage effect”,which was supported by evidence.

关 键 词：玉米期货收益率 ARIMA-GARCH模型 向量自回归模型(VAR) 

分 类 号：F832.5[经济管理—金融学]