TY - GEN
T1 - A comparison between SVM and multilayer perceptron in predicting an emerging financial market
T2 - 2017 Congreso Internacional de Innovacion y Tendencias en Ingenieria, CONIITI 2017 - 2017 International Conference on Innovation and Trends in Engineering, CONIITI 2017
AU - Bustos, Oscar
AU - Pomares, Alexandra
AU - Gonzalez, Enrique
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2018/1/29
Y1 - 2018/1/29
N2 - Achieving accurate stock market forecast impacts strongly to investors, like retirement funds and private investors, giving them tools for making better data based decisions. This article studies the applicability of two soft computing methods, Artificial Neural Networks and Support Vector Machines, to forecast Colombian stock market. Technical indicators were selected as inputs of the machine learning techniques, and up/down movement was selected as output. Cross-validation was employed to improve generalization, and automatic parameter tuning was performed to improve model performance. The results showed that Support Vector Machines performance was better than Artificial Neural Networks, and the results are similar to those found in other studies.
AB - Achieving accurate stock market forecast impacts strongly to investors, like retirement funds and private investors, giving them tools for making better data based decisions. This article studies the applicability of two soft computing methods, Artificial Neural Networks and Support Vector Machines, to forecast Colombian stock market. Technical indicators were selected as inputs of the machine learning techniques, and up/down movement was selected as output. Cross-validation was employed to improve generalization, and automatic parameter tuning was performed to improve model performance. The results showed that Support Vector Machines performance was better than Artificial Neural Networks, and the results are similar to those found in other studies.
UR - http://www.scopus.com/inward/record.url?scp=85047350056&partnerID=8YFLogxK
U2 - 10.1109/CONIITI.2017.8273335
DO - 10.1109/CONIITI.2017.8273335
M3 - Conference contribution
AN - SCOPUS:85047350056
T3 - 2017 Congreso Internacional de Innovacion y Tendencias en Ingenieria, CONIITI 2017 - Conference Proceedings
SP - 1
EP - 6
BT - 2017 Congreso Internacional de Innovacion y Tendencias en Ingenieria, CONIITI 2017 - Conference Proceedings
A2 - Lozano-Garzon, Carlos Andres
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 4 October 2017 through 6 October 2017
ER -