Abstract
An admissible manifold wavelet kernel is proposed to construct manifold wavelet support vector machine (MWSVM) for forecasting stock returns. 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 forecast is confirmed through experiments on real-world stock data.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
