TY - GEN
T1 - Stock composite prediction using nonlinear autoregression with exogenous input (NARX)
AU - Primasiwi, Claudia
AU - Sarno, Riyanarto
AU - Sungkono, Kelly Rossa
AU - Wahyuni, Cahyaningtyas Sekar
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/7
Y1 - 2019/7
N2 - The stock composite cost is utilized as a marker to tell the presentation of the recorded open organizations. The past stock costs in the financial exchange can be utilized for anticipating the future cost of the stock. Because of the snafu circumstances of the stock value, the best-performed forecast model remains a test. This investigation study predicts the stock composite cost by utilizing Nonlinear Autoregression with Exogenous Input (NARX). This technique is contrasted and the Neural Network model. In light of the examination, the NARX model outcome has moderately lower Mean Squared Error (MSE) esteem than the Neural Network model outcome. The little MSE of NARX model is 4.2, which is acquired by five deferrals and six neurons. Notwithstanding, the most reduced MSE of the NN model is 4.62 by utilizing ten neurons.
AB - The stock composite cost is utilized as a marker to tell the presentation of the recorded open organizations. The past stock costs in the financial exchange can be utilized for anticipating the future cost of the stock. Because of the snafu circumstances of the stock value, the best-performed forecast model remains a test. This investigation study predicts the stock composite cost by utilizing Nonlinear Autoregression with Exogenous Input (NARX). This technique is contrasted and the Neural Network model. In light of the examination, the NARX model outcome has moderately lower Mean Squared Error (MSE) esteem than the Neural Network model outcome. The little MSE of NARX model is 4.2, which is acquired by five deferrals and six neurons. Notwithstanding, the most reduced MSE of the NN model is 4.62 by utilizing ten neurons.
KW - Bayesian regularization
KW - Forecasting
KW - NARX
KW - Stock composite price
UR - http://www.scopus.com/inward/record.url?scp=85073516188&partnerID=8YFLogxK
U2 - 10.1109/ICTS.2019.8850956
DO - 10.1109/ICTS.2019.8850956
M3 - Conference contribution
AN - SCOPUS:85073516188
T3 - Proceedings of 2019 International Conference on Information and Communication Technology and Systems, ICTS 2019
SP - 43
EP - 48
BT - Proceedings of 2019 International Conference on Information and Communication Technology and Systems, ICTS 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 12th International Conference on Information and Communication Technology and Systems, ICTS 2019
Y2 - 18 July 2019
ER -