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A New Kernel of Support Vector Regression for Forecasting High-Frequency Stock Returns
Joint Authors
Source
Mathematical Problems in Engineering
Issue
Vol. 2016, Issue 2016 (31 Dec. 2016), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2016-04-18
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Abstract EN
This paper investigates the value of designing a new kernel of support vector regression for the application of forecasting high-frequency stock returns.
Under the assumption that each return is an event that triggers momentum and reversal periodically, we decompose each future return into a collection of decaying cosine waves that are functions of past returns.
Under realistic assumptions, we reach an analytical expression of the nonlinear relationship between past and future returns and introduce a new kernel for forecasting future returns accordingly.
Using high-frequency prices of Chinese CSI 300 index from January 4, 2010, to March 3, 2014, as empirical data, we have the following observations: (1) the new kernel significantly beats the radial basis function kernel and the sigmoid function kernel out-of-sample in both the prediction mean square error and the directional forecast accuracy rate.
(2) Besides, the capital gain of a simple trading strategy based on the out-of-sample predictions with the new kernel is also significantly higher.
Therefore, we conclude that it is statistically and economically valuable to design a new kernel of support vector regression for forecasting high-frequency stock returns.
American Psychological Association (APA)
Qu, Hui& Zhang, Yu. 2016. A New Kernel of Support Vector Regression for Forecasting High-Frequency Stock Returns. Mathematical Problems in Engineering،Vol. 2016, no. 2016, pp.1-9.
https://search.emarefa.net/detail/BIM-1112245
Modern Language Association (MLA)
Qu, Hui& Zhang, Yu. A New Kernel of Support Vector Regression for Forecasting High-Frequency Stock Returns. Mathematical Problems in Engineering No. 2016 (2016), pp.1-9.
https://search.emarefa.net/detail/BIM-1112245
American Medical Association (AMA)
Qu, Hui& Zhang, Yu. A New Kernel of Support Vector Regression for Forecasting High-Frequency Stock Returns. Mathematical Problems in Engineering. 2016. Vol. 2016, no. 2016, pp.1-9.
https://search.emarefa.net/detail/BIM-1112245
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1112245