[1]Andersen T G,Bollerslev T.Answering the skeptics:yes,standard volatility models do provide accurate forecasts[J].International Economic Review,1998,39(4):885-905. [2]Corsi F.A simple approximate long-memory model of realized volatility[J].Journal of Financial Econometrics,2009,7(2):174-196. [3]Tian F,Yang K,Chen L.Realized volatility forecasting of agricultural commodity futures using the HAR model with time-varying sparsity[J].International Journal of Forecasting,2017,33(1):132-152. [4]陈声利,关涛,李一军.基于跳跃、好坏波动率与百度指数的股指期货波动率预测[J].系统工程理论与实践,2018,38(2):299-316.(Chen Sheng-li,Guan Tao,Li Yi-jun.Forecasting realized volatility of Chinese stock index futures based on jumps,good-bad volatility and Baidu index[J].Systems Engineering-Theory & Practice,2018,38(2):299-316.) [5]Peng H,Chen R,Mei D,et al.Forecasting the realized volatility of the Chinese stock market:do the G7 stock markets help?[J].Physica A:Statistical Mechanics and Its Applications,2018,501(1):78-85. [6]Clements A,Liao Y.Forecasting the variance of stock index returns using jumps and cojumps[J].International Journal of Forecasting,2017,33(3):729-742. [7]Andersen T G,Bollerslev T,Diebold F X.Roughing it up:including jump components in the measurement,modeling,and forecasting of return volatility[J].Review of Economics & Statistics,2007,89(4):701-720. [8]宫晓莉,庄新田.调和稳定Lévy过程驱动的双重跳跃模型及期权应用[J].系统管理学报,2017,25(6):1089-1096.(Gong Xiao-li,Zhuang Xin-tian.Option pricing of a double jump model driven by tempered stable Lévy processes and its application[J].Journal of Systems & Management,2017,25(6):1089-1096.) [9]瞿慧,程思逸.考虑成分股联跳与宏观信息发布的沪深300指数已实现波动率模型研究[J].中国管理科学,2016,24(12):10-19.(Qu Hui,Cheng Si-yi.The role of cojumps and macro announcements in forecasting the realized volatility of Chinese CSI 300 index[J].Chinese Journal of Management Science,2016,24(12):10-19.) [10]陈声利,李一军,关涛.基于四次幂差修正HAR模型的股指期货波动率预测[J].中国管理科学,2018,26(1):57-71.(Chen Sheng-li,Li Yi-jun,Guan Tao.Forecasting realized volatility of Chinese stock index futures based on approved HAR models with median realized quarticity[J].Chinese Journal of Management Science,2018,26(1):57-71.) [11]Corsi F,Renò R.Discrete-time volatility forecasting with persistent leverage effect and the link with continuous-time volatility modeling[J].Journal of Business & Economic Statistics,2012,30(3):368-380. [12]Zhu X,Zhang H,Zhong M.Volatility forecasting using high frequency data:the role of after-hours information and leverage effects[J].Resources Policy,2017,54:58-70. [13]Duan Y,Chen W,Zeng Q,et al.Leverage effect,economic policy uncertainty and realized volatility with regime switching[J].Physica A:Statistical Mechanics and Its Applications,2018,493(1):148-154. [14]罗嘉雯,陈浪南.基于贝叶斯因子模型金融高频波动率预测研究[J].管理科学学报,2017,20(8):13-26.(Luo Jia-wen,Chen Lang-nan.High-frequency volatility forecast of financial futures based on Bayesian factor model[J].Journal of Management Sciences in China,2017,20(8):13-26.) [15]Pan Z,Liu L.Forecasting stock return volatility:a comparison between the roles of short-term and long-term leverage effects[J].Physica A:Statistical Mechanics and Its Applications,2018,492(1):168-180. [16]Wei Y,Wang P.Forecasting volatility of SSEC in Chinese stock market using multifractal analysis[J].Physica A:Statistical Mechanics and Its Applications,2008,387(7):1585-1592. [17]Chen H,Wu C.Forecasting volatility in Shanghai and Shenzhen markets based on multifractal analysis[J].Physica A:Statistical Mechanics and Its Applications,2011,390(16):2926-2935. [18]唐勇,陈艳茹.考虑杠杆效应的多重分形波动建模:基于中国股指的实证分析[J].系统工程学报,2015,30(1):94-103.(Tang Yong,Chen Yan-ru.Multifractal volatility modeling considering the leverage effect:an empirical analysis from China stock index[J].Journal of Systems Engineering,2015,30(1):94-103.) [19]魏宇,马锋,黄登仕.多分形波动率预测模型及其MCS检验[J].管理科学学报,2015,18(8):61-72.(Wei Yu,Ma Feng,Huang Deng-shi.Multi-fractal volatility forecasting model and its MCS test[J].Journal of Management Sciences in China,2015,18(8):61-72.) [20]Tao Q,Wei Y,Liu J,et al.Modeling and forecasting multifractal volatility established upon the heterogeneous market hypothesis[J].International Review of Economics & Finance,2018,54:143-153. [21]郭名媛,张世英.赋权已实现波动及其长记忆性,最优频率选择[J].系统工程学报,2006,21(6):568-573.(Guo Ming-yuan,Zhang Shi-ying.Weighted realized volatility and its long memory and optimal frequency[J].Journal of Systems Engineering,2006,21(6):568-573.) [22]Hansen P R,Lunde A,Nason J M.The model confidence set[J].Econometrica,2011,79(2):453-497. [15]关守平,房少纯.一种新型的区间-粒子群优化算法[J].东北大学学报(自然科学版),2012,33(10):1381-1384.(Guan Shou-ping,Fang Shao-chun.A new interval particle swarm optimization algorithm[J].Journal of Northeastern University(Natural Science),2012,33(10):1381-1384.)