Analysis about High-frequency volatility and Impact of Shanghai copper futures price ——based on Markov state transformation model

Abstract

Abstract: This article divides the price of Shanghai copper futures into two categories: rising and falling, apply RS-GARCH modeling ,further its yield is divided into two types of high and low volatility, explain the fluctuation characteristics of Shanghai copper futures price from a dynamic perspective.The results show:Shanghai copper's yield has a strong lag effect;the volume of transactions has a positive effect on the yield, and the open interest has a negative impact on it;whether the price of Shanghai copper futures is up or down,yield fluctuations are longer in the low state and shorter in the high state;the positive value of the leverage factor indicates that the bad news has a greater impact on price fluctuations.

Key words: copper prices, volatility, RS-EGARCH model

CLC Number:

F224
F724.5

Sun Liping, Yang Jun. Analysis about High-frequency volatility and Impact of Shanghai copper futures price ——based on Markov state transformation model[J]. JOURNAL OF QUJING NORMAL UNIVERSITY, 2019, 38(3): 1-6.

References

[1]陈晓东.中国金融期货市场高频波动率预测模型比较研究[J].管理工程学报,2016(3):114-119.
[2]郑丰,崔积珏,马志伟.沪铜期货市场长记忆特征的R/S分析[J].辽宁大学学报(自然科学版),2013(1):14-22.
[3]张保银,陈俊.基于动态VECM的我国铜期货的价格发现功能研究[J].天津大学学报(社会科学版),2012(6):492-496.
[4]黄健柏,刘凯,郭尧琦.沪铜期货市场价格发现的动态贡献——基于状态空间模型的实证研究[J].技术经济与管理研究,2014(2):67-72.
[5]彭红枫,陈奕.中国铜期货市场最优套期保值比率估计——基于马尔科夫区制转移GARCH模型[J].中国管理科学,2015,23(5):14-22.
[6]董珊珊,冯芸.基于FCVAR模型研究SHFE和LME铜期货和现货市场价格发现功能[J].现代管理科学,2015(11):67-69.
[7]韩立岩,尹力博.投机行为还是实际需求？——国际大宗商品价格影响因素的广义视角分析[J].经济研究,2012(12):83-96.
[8]周仁才.基于风险分解的股指期货套期保值策略研究[J].中国管理科学,2013(2):17-23.
[9]付剑茹.中国铜期货套期保值蒙特卡洛模拟研究——基于ITO过程与持有成本理论的假设[J].技术经济与管理研究,2010(6):22-27.
[10]刘建和,胡琼,王玉斌.基于EGARCH-GED模型的中英铜期货风险溢出效应[J].华中农业大学学报(社会科学版),2015,120(6):92-100.
[11]朱学红,谌金宇,邵留国.信息溢出视角下的中国金属期货市场国际定价能力研究[J].中国管理科学,2016(9):28-35.
[12]崔海蓉,何建敏,张京波.我国有色金属期货溢出效应研究——以SHFE的铜和铝为例[J].北京理工大学学报(社会科学版):2011(4):29-32+57.
[13]孙泽生,孙便霞,黄伟.中国有色金属价格变化中的货币因素和预期形成:基于金属指数的实证研究[J].系统管理学报,2014(5):73-754.
[14]胡龙,胡太军.基于VEC-GARCH模型的沪铜指数与上证指数的联动分析[J].金融与经济,2011(6):62-66+70.
[15]朱学红,冯宇文,郭尧琦.金融因素对期铜价格波动影响的实证研究[J].中南大学学报(社会科学版),2015(2):124-129.
[16]薛丽冰,许林,董永琦,等.一种基于残差的单品种期货套利策略构建及有效性研究——以铜为例[J].金融理论与实践,2017,452(3):82-88.
[17]张茂军,王文华,王庆辉.基于便利收益的商品期货套期保值策略研究[J].运筹与管理,2016,25(3):232-238.
[18]Chou R Y.Volatility persistence,stock valuation:some empirical evidence using GARCH[J].Journal of Applied Econometrics,1988(50):279-294.
[19]Diebold F X.Modeling the persistence of conditional variance:a comment[J].Econometric Reviews,1994,64(1):307-333.
[20]Lamoureux C G,Lastrapes W D.Persistence in variance,structural change and the GARCH model[J].Journal of Business and Economic Statistics,1990(8):225-234.
[21]Hamilton J D,Susmel R.Autoregressive conditional heteroskedasticity and changes in regime[J].Journal of Economics,1994,64(1):307-333.
[22]Gray S.Modeling the conditional distribution of interest rates as a regime switching process[J].Journal of Financial Economics,1996,42(1):27-62.
[23]蒋祥林,王春峰,吴晓霖.基于状态转移ARCH模型的中国股市波动性研究[J].系统工程学报,2004,19(3):270-277.
[24]张锐,魏宇,金炜东.基于MRS-EGARCH模型的沪深300指数波动率预测研究[J].系统工程学报,2011,26(5):628-635.
[25]杨继平,张春会.基于马尔科夫状态转换模型的沪深股市波动率的估计[J].中国管理科学,2013(2):42-49.
[26]朱钧钧,谢识予.中国股市波动率的双重不对称性及其解释——基于MS-TGARCH模型的MCMC估计和分析[J].金融研究,2011(3):134-148.
[27]王娟.我国黄金现货价格波动研究[J].财经理论研究,2015(6):82-90.
[28]Engle R F.Autoregressive conditional heteroskedasticity with estimates of the variance of United Kingdom inflation[J].Econometrica,1982,50(4):987-1007.
[29]Bollerslev T.Generalized autoregressive conditional heteroskedasticity[J].Journal of Econometrics,1986,31(3):307-327.
[30]Engle R F,Lilien D M,Rsobins R P. Estimating time varying risk premia in the term structure: the ARCH-M model[J].Econometrica,1987,55(4):391-407.
[31]Rabemananjara R,Zakoian J M.Threshold ARCH models and asymmetries in volatility[J].Journal of Applied Econometrics,1987,55(4):391-407.
[32]Nelson D B.Conditional heteroskedasticity in asset returns: a new approach[J].Econometrica,1991,59(2):347-370.
[33]刘鹤飞,王坤,蒋成飞.隐状态个数未知的隐马尔科夫多元正态分布的贝叶斯推断[J].统计研究,2017(12):119-125.
[34]王坤,刘鹤飞,蒋成飞.隐马尔科夫结构方程模型及其贝叶斯估计[J].数理统计与管理,2018(2):272-279.