| [1] Wang Jujie,Wang Jianzhou,Zhang Z,et al. Stock index forecasting based on a hybrid model[J].Omega,2012,40(6):758-766.[2] Pal Pingfeng,Lin C.A hybrid ARIMA and support vector machines model in stock price forecasting[J].Omega,2005,33(6):497-505.[3] 曹广喜,曹杰,徐龙炳.双长记忆GARCH族模型的预测能力比较研究-基于沪深股市数据的实证分析[J].中国管理科学,2012,20(2):41-49.[4] 张锐,魏宇,金炜东.基于MRS-EGARCH模型的沪深300指数波动预测[J].系统工程学报,2011,26(5):628-635.[5] 姜婷,周孝华,董耀武.基于Markov机制转换模型的我国股市周期波动状态研究[J].系统工程理论与实践,2013,33(8):1934-1939.[6] 杨继平,张春会.基于马尔可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,2013,21(2):42-49.[7] 于志军,杨善林,章政,等. 基于误差校正的灰色神经网络股票收益率预测[J].中国管理科学,2015,23(12):20-26.[8] 王文波,费浦生,羿旭明.基于EMD和神经网络的中国股票市场预测[J].系统工程理论与实践,2010,30(6):1028-1033.[9] Kim K. Financial time series forecasting using support vector machines[J].Neurocomputing,2003,55(1-2):307-319.[10] Huang Wei,Nakamori Y,Wang Shouyang.Forecasting stock market movement direction with support vector machine[J].Computers & Operations Research,2005,32(10):2513-2522.[11] Engle R F. Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation[J]. Econometrica,1982,50(4):987-1007.[12] Bollerslev T.Generalized autoregressive condi-tional heteroskedasticity[J].Journal of Econometrics,1986,3 1(3):307-327.[13] 侯利强,杨善林,王晓佳,等.上证综指的股指波动:基于模糊FEGARCH模型及不同分布假设的预测研究[J].中国管理科学,2015,23(6):32-40.[14] Mohammadi H, Su Lixian.International evidence on crude oil price dynamics:Applications of ARIMA-GARCH models[J].Energy Economics,2010,32(5):1001-1008.[15] Liu Heping, Shi Jing.Applying ARMA-GARCH approaches to forecasting short-term electricity prices[J].Energy Economics,2013,37:152-166.[16] 吴恒煜,朱福敏,温金明.基于ARMA-GARCH调和稳态Levy过程的期权定价[J].系统工程理论与实践,2013,33(11):2721-2733.[17] 周璞,李自然.基于非线性Granger因果检验中国大陆和世界其他主要股票市场之间的信息溢出[J].系统工程理论与实践,2012,32(3):466-475.[18] 沈传河,王向荣.金融市场联动形态结构的非线性分析[J].管理科学学报,2015,18(2):66-75.[19] Loh L.Co-movement of Asla-Pacific with European and US stock market returns:A cross-time-frequency analysis[J].Research in International Business and Finance,2013,29:1-13.[20] Kotkatvuori-Örnberg J,Nikkinen J,Äijö J.Stock market correlations during the financial crisis of 2008-2009:Evidence from 50 equity markets[J].International Revlew of Financial Analysis,2013,28:70-78.[21] 黄飞雪,谷静,李延喜,等.金融危机前后的全球主要股指联动与动态稳定性比较[J].系统工程理论与实践,2010,30(10):1729-1740.[22] 林宇. 中国股市与国际股市的极值风险传导效应研究[J].中国管理科学,2008,16(4):36-43.[23] Xiong Tao,Li Chongguang,Bao Yukun,et al.A combination method for interval forecasting of agricultural commodity futures prices[J].Knowledge-Based Systems,2015,77:92-102.[24] Zhang G P.Time series forecasting using a hybrid ARIMA and neural network model[J].Neurocomputing,2003,50:159-175.[25] Zhu Bangzhu,Wei Yiming.Carbon price forecasting with a novel hybrid ARIMA and least squares support vector machines methodology[J].Omega, 2013,41(3):517-524.[26] 陈海英. 基于支持向量机的上证指数预测和分析[J].计算机仿真,2013,30(1):297-300.[27] 张贵生,张信东.基于时间相关性的股票价格混合预测模型[J].经济问题,2015,(9):23-28.[28] 于志军,杨善林.基于误差校正GARCH的股票价格预测模型[J].中国管理科学,2013,21(S1):341-345.[29] 张维,赵帅特,熊熊,等.计算实验金融、技术规则与时间序列收益可预测性[J].管理科学,2008,21(3):74-84.[30] 张维,李悦雷,熊熊,等.计算实验金融的思想基础及研究范式[J].系统工程理论与实践,2012,32(3):495-507.[31] Cao Lijuan. Support vector machines experts for time series forecasting[J].Neurocomputing,2003,51:321-339.[32] 谢国强.基于支持向量回归机的股票价格预测[J].计算机仿真,2012,29(4):379-382.[33] Vapnik V.The nature of statistical learning theory[M].1995,New York:Springer Verlag Press.[34] Atsalakis G S.Valavanis K P.Surveying stock market forecasting techniques-Part II:Soft computing methods[J].Expert Systems with Applications,2009,36(3):5932-5941.[35] 熊涛,鲍玉昆,胡忠义,张金隆.基于SOM和SVMs的沪深300指数多步预测[J].系统工程,2012,30(10):36-42.[36] 李海燕.基于支持向量机算法的股市拐点预测分析[J].郑州大学学报(哲学社会科学版),2015,48(1):96-99.[37] 苏治,傅晓媛.核主成分遗传算法与SVR选股模型改进[J].统计研究,2013,30(5):54-62.[38] 王晴.组合模型在股票价格预测中应用研究[J].计算机仿真,2010,27(12):361-364.[39] Hossein H,Andreia D,Mansoureh G.Effct of noise reduction in measuring the linear and nonlinear dependency of financial maricets[J].Nonlinear Analysis:Real World Applications,2010,11(1):492-502.[40] Dionisio A,Menezes R,Mendes D A.Mutual information:A measure of dependency for nonlinear time series[J].Physica A,2004,344(1-2):326-329.[41] Hu Qinghua,Zhang Lei,Zhang D,et al.Measuring relevance between discrete and continuous features based on neighborhood mutual information[J].Expert Systems with Applications,2011,38(9):10737-10750.[42] 章宇轩.基于ARMA模型的日经225指数实证研究[J].中国外资,2013(8):174-175.[43] Hansen P R,Lunde A.A forecast comparison of volatility models:Does anything beat a GARCH(1,1)[J].Journal of Applied Econometrics,2005,20(7):873-899. |
