[Home ] [Archive]   [ فارسی ]  
:: Main :: About :: Current Issue :: Archive :: Search :: Submit :: Contact ::
Main Menu
Journal Information::
Articles archive::
For Authors::
For Reviewers::
Contact us::
Site Facilities::
Search in website

Advanced Search
Receive site information
Enter your Email in the following box to receive the site news and information.
:: Volume 26, Issue 2 (3-2022) ::
Andishe 2022, 26(2): 21-32 Back to browse issues page
Support Vector Machines Regression Model and Comparison with Semi-parametric Regression
Mahdi Roozbeh * , Arta Rouhi , Fatemeh Jahadi , Saeed Zalzadeh
Semnan University
Abstract:   (1604 Views)

‎‎In this research‎, ‎the aim is to assess and analyze a method to predict the stock market‎. ‎However‎, ‎it is not easy to predict the capital market due to its high dependence on politics‎ ‎b‎ut by data modeling‎, ‎it will be somewhat possible to predict the stock market in the long period of time‎. ‎In this regard‎, ‎by using the semi-parametric regression models and support vector regression‎ ‎with different ‎kernels‎ and measuring the predictor errors in the stock market of one stock based on daily fluctuations and comparing methods using the root ‎of ‎mean ‎squared‎ error and mean absolute percentage error criteria‎, ‎support vector regression model ‎has ‎been‎ the most appropriate fit to the real stock market data with radial kernel and error equal to 0.1‎‎.

Keywords: ‎Regression Model‎, ‎Stock Forecasting‎, ‎Support Vector Regression Model‎.
Full-Text [PDF 255 kb]   (1704 Downloads)    
Type of Study: Applicable | Subject: Special
Received: 2021/07/4 | Accepted: 2022/03/30 | Published: 2022/09/8
1. روزبه، م. و امینی، م. ( ١٣٩٨ )، برآوردگر استوار مرزبندی شده تعمیم یافته محتمل در مدل رگرسیون نیمه پارامتری، مجله علوم آماری، ١٣، .۴۴١ -۴۶٠
2. [2] Amini, M. and Roozbeh, M. (2015), Optimal partial ridge estimation in restricted semiparametric regression models, Journal of Multivariate Analysis, 136, 26-40. [DOI:10.1016/j.jmva.2015.01.005]
3. [3] Araújo, R. D. A., Oliveira, A. L. and Meira, S. (2015), A hybrid model for high-frequency stock market forecasting, Expert Systems with Applications, 42, 4081-4096. [DOI:10.1016/j.eswa.2015.01.004]
4. [4] Blanchflower, D. G. and Oswald, A. J. (1994), The wage curve, MIT press.
5. [5] Choudhury, S., Ghosh, S., Bhattacharya, A., Fernandes, K. J. and Tiwari, M. K. (2014), A real time clustering and SVM based price-volatility prediction for optimal trading strategy, Neurocomputing, 131, 419-426. [DOI:10.1016/j.neucom.2013.10.002]
6. [6] Dash, R. and Dash, P. K. (2016), A hybrid stock trading framework integrating technical analysis with machine learning techniques, The Journal of Finance and Data Science, 2, 42-57. [DOI:10.1016/j.jfds.2016.03.002]
7. [7] Engle, R. F., Granger, C. W. J., Rice, J. and Weiss, A. (1986), Semiparametric Estimates of the Relation Between Weather and Electricity Sales, Journal of the American Statistical Association, 81, 310-320. [DOI:10.1080/01621459.1986.10478274]
8. [8] Fama, E. (1970), Efficient capital markets: A review of theory and empirical work, The journal of Finance, 25, 383-417. [DOI:10.1111/j.1540-6261.1970.tb00518.x]
9. [9] Gerlein, E. A., McGinnity, M., Belatreche, A. and Coleman, S. (2016), Evaluating machine learning classification for financial trading: An empirical approach, Expert Systems with Applications, 54, 193-207. [DOI:10.1016/j.eswa.2016.01.018]
10. [10] Kao, L. J., Chiu, C. C., Lu, C. J., and Yang, J. L. (2013), Integration of nonlinear independent component analysis and support vector regression for stock price forecasting, Neurocomputing, 99, 534-542. [DOI:10.1016/j.neucom.2012.06.037]
11. [11] Manahov, V., Hudson, R. and Gebka, B. (2014), Does high frequency trading affect technical analysis and market efficiency and if so, how Journal of International Financial Markets, Institutions and Money, 28, 131-157. [DOI:10.1016/j.intfin.2013.11.002]
12. [12] Nayak, R. K., Mishra, D. and Rath, A. K. (2015), A naïve svm-knn based stock market trend reversal analysis for indian benchmark indices, Applied Soft Computing, 35, 670-680. [DOI:10.1016/j.asoc.2015.06.040]
13. [13] Patel, J., Shah, S., Thakkar, P. and Kotecha, K. (2015), Predicting stock market index using fusion of machine learning techniques, Expert Systems with Applications, 42, 2162-2172. [DOI:10.1016/j.eswa.2014.10.031]
14. [14] Roozbeh, M. (2015), Shrinkage ridge estimators in semiparametric regression models, Journal of Multivariate Analysis. 136, 56-74. [DOI:10.1016/j.jmva.2015.01.002]
15. [15] Roozbeh, M. (2018), Optimal QR-based estimation in partially linear regression models with correlated errors using GCV criterion, 117, Computational Statistics & Data Analysis. 117, 45-61. [DOI:10.1016/j.csda.2017.08.002]
16. [16] Roozbeh, M. and Arashi, M. (2013), Feasible ridge estimator in partially linear models, Journal of Multivariate Analysis. 116, 35-44. [DOI:10.1016/j.jmva.2012.11.006]
17. [17] Vapnik, V. N. (1995), The Nature of Statistical Learning Theory, New York. [DOI:10.1007/978-1-4757-2440-0]
18. [18] Willis, R. J. (1986), Wage determinants: A survey and reinterpretation of human capital earnings functions. Handbook of labor economics, 1, 525-602. [DOI:10.1016/S1573-4463(86)01013-1]
19. [19] Xiao, Y., Xiao, J., Lu, F. and Wang S. (2014), Ensemble anns-pso-ga approach for day-ahead stock e-exchange prices forecasting, International Journal of Computational Intelligence Systems, 7, 272-290. [DOI:10.1080/18756891.2013.864472]
Send email to the article author

Add your comments about this article
Your username or Email:


XML   Persian Abstract   Print

Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

Roozbeh M, Rouhi A, Jahadi F, Zalzadeh S. Support Vector Machines Regression Model and Comparison with Semi-parametric Regression. Andishe 2022; 26 (2) :21-32
URL: http://andisheyeamari.irstat.ir/article-1-858-en.html

Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Volume 26, Issue 2 (3-2022) Back to browse issues page
مجله اندیشه آماری Andishe _ye Amari
Persian site map - English site map - Created in 0.06 seconds with 37 queries by YEKTAWEB 4624