Combined Effect of Heat Stimulation and Delay Addition of Superplasticizer with Slag on Fresh and Hardened Property of Mortar
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 32799
Combined Effect of Heat Stimulation and Delay Addition of Superplasticizer with Slag on Fresh and Hardened Property of Mortar

Authors: Antoni Wibowo, Harry Pujianto, Dewi Retno Sari Saputro

Abstract:

The stock market can provide huge profits in a relatively short time in financial sector; however, it also has a high risk for investors and traders if they are not careful to look the factors that affect the stock market. Therefore, they should give attention to the dynamic fluctuations and movements of the stock market to optimize profits from their investment. In this paper, we present a nonlinear autoregressive exogenous model (NARX) to predict the movements of stock market; especially, the movements of the closing price index. As case study, we consider to predict the movement of the closing price in Indonesia composite index (IHSG) and choose the best structures of NARX for IHSG’s prediction.

Keywords: NARX, prediction, stock market, time series.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1132763

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 770

References:


[1] R. Dash & P. K. Dash, “A Hybrid Stock Trading Framework Integrating Technical Analysis with Machine Learning Techniques,” In The Journal of Finance and Data Science, Volume 2, Issue 1, March 2016, 42-57.
[2] M. B. Alam, M. Z. Hossain., A. M. Hossain, A. M. And M. M. Islam, “Price Prediction of Stock Market using Hybrid Model of Artificial Intelligence, “in International Journal of Computer Applications, 2015, 111(3), 5–10.
[3] U. A. Umoh and U. G. Inyang, “A Fuzzy-Neural Intelligent Intelligent Trading Model for f or Stock Price Prediction,” in International Journal of Computer Science Issues, 2015, 12(3), 36–44.
[4] S. H. Arbain and A. Wibowo, “Neural Networks Based Nonlinear Time Series Regression for Water Level Forecasting of Dungun River,” in American Journal of Computer Science, 2012, Science Publications.
[5] A. Wibowo and M. I. Desa, “Kernel Based Regression and Genetic algorithms for Estimating Cutting Conditions of Surface Roughness in End Milling Machining Process”, in Expert System with Applications, 2012, Elsevier.
[6] P. Hillion and M. Suominen, “The manipulation of closing prices,” in Journal of Financial Markets, 2004, 7, 351-375.
[7] T. Antolis and S. Dossugi, “Pengaruh Fluktuasi IHSG, Inflasi Dan Suku Bunga Terhadap Imbal Hasil Unitlink Berbasis Saham,” in Journal of Applied Finance and Accounting, Binus Journal, 2008, 1(1), 141–165 (in Bahasa).
[8] https://finance.yahoo.com/quote/^JKSE/history?period1=1343062800&period2=1488214800&interval=1d&filter=history&frequency=1d (Accessed: 1 July 2017).
[9] S. Cheng and M. Pecht,” Using cross-validation for model parameter selection of sequencial probability ratio test,” in Expert Systems with Applications, 2012, 39. pp. 8467-8473.
[10] P. Refaeilzadeh, L. Tang and H. Liu, Cross-validation, 2008, Arizona State University.