Nonlinear Support Vector Machines Can Systematically Identify Stocks with High and Low Future Returns

SSRN Electronic Journal ◽

10.2139/ssrn.1930709 ◽

2011 ◽

Cited By ~ 6

Author(s):

Ramon Huerta ◽

Charles Elkan ◽

Fernando Corbacho

Keyword(s):

Support Vector Machines ◽

Support Vector ◽

Vector Machines ◽

Nonlinear Support

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Nonlinear support vector machines can systematically identify stocks with high and low future returns

Algorithmic Finance ◽

10.3233/af-13016 ◽

2013 ◽

Vol 2 (1) ◽

pp. 45-58 ◽

Cited By ~ 6

Author(s):

Ramon Huerta ◽

Fernando Corbacho ◽

Charles Elkan

Keyword(s):

Support Vector Machines ◽

Support Vector ◽

Vector Machines ◽

Nonlinear Support

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Efficient Application of Gabor Filters with Nonlinear Support Vector Machines

2012 International Conference on Computing Sciences ◽

10.1109/iccs.2012.31 ◽

2012 ◽

Author(s):

Ajitesh Srivastava ◽

Pritish Mohapatra ◽

A.S. Mandal

Keyword(s):

Support Vector Machines ◽

Gabor Filters ◽

Support Vector ◽

Vector Machines ◽

Nonlinear Support

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Bayesian Nonlinear Support Vector Machines for Big Data

Machine Learning and Knowledge Discovery in Databases - Lecture Notes in Computer Science ◽

10.1007/978-3-319-71249-9_19 ◽

2017 ◽

pp. 307-322 ◽

Cited By ~ 4

Author(s):

Florian Wenzel ◽

Théo Galy-Fajou ◽

Matthäus Deutsch ◽

Marius Kloft

Keyword(s):

Big Data ◽

Support Vector Machines ◽

Support Vector ◽

Vector Machines ◽

Nonlinear Support

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Efficient and robust classification of seismic data using nonlinear support vector machines

2017 51st Asilomar Conference on Signals, Systems, and Computers ◽

10.1109/acssc.2017.8335156 ◽

2017 ◽

Author(s):

Kyle S. Hickmann ◽

Jeffrey Hyman ◽

Gowri Srinivasan

Keyword(s):

Support Vector Machines ◽

Seismic Data ◽

Support Vector ◽

Robust Classification ◽

Vector Machines ◽

Nonlinear Support

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Learning algorithm for nonlinear support vector machines suited for digital VLSI

Electronics Letters ◽

10.1049/el:19990950 ◽

1999 ◽

Vol 35 (16) ◽

pp. 1349 ◽

Cited By ~ 19

Author(s):

D. Anguita ◽

A. Boni ◽

S. Ridella

Keyword(s):

Support Vector Machines ◽

Learning Algorithm ◽

Support Vector ◽

Digital Vlsi ◽

Vector Machines ◽

Nonlinear Support

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Incorporating Invariances in Nonlinear Support Vector Machines

Advances in Neural Information Processing Systems 14 ◽

10.7551/mitpress/1120.003.0083 ◽

2002 ◽

Keyword(s):

Support Vector Machines ◽

Support Vector ◽

Vector Machines ◽

Nonlinear Support

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Nonlinear Support Vector Machines Through Iterative Majorization and I-Splines

Studies in Classification, Data Analysis, and Knowledge Organization - Advances in Data Analysis ◽

10.1007/978-3-540-70981-7_18 ◽

2007 ◽

pp. 149-161 ◽

Cited By ~ 3

Author(s):

Patrick J. F. Groenen ◽

Georgi Nalbantov ◽

J. Cor Bioch

Keyword(s):

Support Vector Machines ◽

Support Vector ◽

Vector Machines ◽

Iterative Majorization ◽

Nonlinear Support

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Nonlinear Support Vector Machines for Solving the PMC-Based System-Level Fault Diagnosis Problem

2013 IEEE 16th International Conference on Computational Science and Engineering ◽

10.1109/cse.2013.11 ◽

2013 ◽

Author(s):

Mourad Elhadef

Keyword(s):

Fault Diagnosis ◽

Support Vector Machines ◽

System Level ◽

Support Vector ◽

Vector Machines ◽

Nonlinear Support

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Morphological classification of medical images using nonlinear support vector machines

2004 2nd IEEE International Symposium on Biomedical Imaging: Macro to Nano (IEEE Cat No. 04EX821) ◽

10.1109/isbi.2004.1398606 ◽

2005 ◽

Cited By ~ 1

Author(s):

C. Davatzikos ◽

Dinggang Shen ◽

Zhiqiang Lao ◽

Zhong Xue ◽

B. Karacali

Keyword(s):

Support Vector Machines ◽

Medical Images ◽

Support Vector ◽

Morphological Classification ◽

Vector Machines ◽

Nonlinear Support

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Recursive Finite Newton Algorithm for Support Vector Regression in the Primal

Neural Computation ◽

10.1162/neco.2007.19.4.1082 ◽

2007 ◽

Vol 19 (4) ◽

pp. 1082-1096 ◽

Cited By ~ 29

Author(s):

Liefeng Bo ◽

Ling Wang ◽

Licheng Jiao

Keyword(s):

Support Vector Machines ◽

Support Vector Regression ◽

Loss Function ◽

Support Vector ◽

Training Support ◽

Newton Algorithm ◽

Newton Step ◽

Vector Machines ◽

Nonlinear Support

Some algorithms in the primal have been recently proposed for training support vector machines. This letter follows those studies and develops a recursive finite Newton algorithm (IHLF-SVR-RFN) for training nonlinear support vector regression. The insensitive Huber loss function and the computation of the Newton step are discussed in detail. Comparisons with LIBSVM 2.82 show that the proposed algorithm gives promising results.

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