Cargando…
Using Internet Search Trends and Historical Trading Data for Predicting Stock Markets by the Least Squares Support Vector Regression Model
Historical trading data, which are inevitably associated with the framework of causality both financially and theoretically, were widely used to predict stock market values. With the popularity of social networking and Internet search tools, information collection ways have been diversified. Instead...
Autores principales: | Pai, Ping-Feng, Hong, Ling-Chuang, Lin, Kuo-Ping |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2018
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6081535/ https://www.ncbi.nlm.nih.gov/pubmed/30140278 http://dx.doi.org/10.1155/2018/6305246 |
Ejemplares similares
-
Quasi-least squares regression
por: Shults, Justine, et al.
Publicado: (2014) -
A new regularized least squares support vector regression for gene selection
por: Chen, Pei-Chun, et al.
Publicado: (2009) -
A Nonlinear Adaptive Beamforming Algorithm Based on Least Squares Support Vector Regression
por: Wang, Lutao, et al.
Publicado: (2012) -
SOC stocks prediction on the basis of spatial and temporal variation in soil properties by using partial least square regression
por: Usman, Jawaria, et al.
Publicado: (2023) -
Circular and linear regression: fitting circles and lines by least squares
por: Chernov, Nikolai
Publicado: (2010)