技术分析能否帮助投资者获得超额收益率是金融理论界广泛关注的问题之一。早期理论界主要采用传统t检验方法,得出技术分析无效的结论;随着计算机的普遍应用,布鲁克等人(Brock et al)基于传统t检验存在的计量误差,采取脱靴检验方法,认为...技术分析能否帮助投资者获得超额收益率是金融理论界广泛关注的问题之一。早期理论界主要采用传统t检验方法,得出技术分析无效的结论;随着计算机的普遍应用,布鲁克等人(Brock et al)基于传统t检验存在的计量误差,采取脱靴检验方法,认为技术分析能够带来显著的超额收益率,随后,有学者认为股票收益率呈现非线性相关的特征,采用前向人工神经网络模型进行分析,得到技术分析有效的结论;然而,数据窥查效应的剔除使得技术分析获得的超额收益率减少,遗传规划模型的应用也使得技术分析有效的结论受到了较大的质疑。因此,目前对于技术分析是否有效这一问题,并没有形成一致的结论,依然有较大的研究空间。展开更多
An admissible manifold wavelet kernel is proposed to construct manifold wavelet support vector machine(MWSVM) for stock returns forecasting.The manifold wavelet kernel is obtained by incorporating manifold theory into...An admissible manifold wavelet kernel is proposed to construct manifold wavelet support vector machine(MWSVM) for stock returns forecasting.The manifold wavelet kernel is obtained by incorporating manifold theory into wavelet technique in support vector machine(SVM).Since manifold wavelet function can yield features that describe of the stock time series both at various locations and at varying time granularities,the MWSVM can approximate arbitrary nonlinear functions and forecast stock returns accurately.The applicability and validity of MWSVM for stock returns forecasting is confirmed through experiments on real-world stock data.展开更多
文摘技术分析能否帮助投资者获得超额收益率是金融理论界广泛关注的问题之一。早期理论界主要采用传统t检验方法,得出技术分析无效的结论;随着计算机的普遍应用,布鲁克等人(Brock et al)基于传统t检验存在的计量误差,采取脱靴检验方法,认为技术分析能够带来显著的超额收益率,随后,有学者认为股票收益率呈现非线性相关的特征,采用前向人工神经网络模型进行分析,得到技术分析有效的结论;然而,数据窥查效应的剔除使得技术分析获得的超额收益率减少,遗传规划模型的应用也使得技术分析有效的结论受到了较大的质疑。因此,目前对于技术分析是否有效这一问题,并没有形成一致的结论,依然有较大的研究空间。
基金the Hunan Natural Science Foundation(No. 09JJ3129)the Hunan Key Social Science Foundation (No. 09ZDB04)the Hunan Social Science Foundation (No. 08JD28)
文摘An admissible manifold wavelet kernel is proposed to construct manifold wavelet support vector machine(MWSVM) for stock returns forecasting.The manifold wavelet kernel is obtained by incorporating manifold theory into wavelet technique in support vector machine(SVM).Since manifold wavelet function can yield features that describe of the stock time series both at various locations and at varying time granularities,the MWSVM can approximate arbitrary nonlinear functions and forecast stock returns accurately.The applicability and validity of MWSVM for stock returns forecasting is confirmed through experiments on real-world stock data.
