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We postulate, based on past research, three major drawbacks for using time series in forecasting stock prices as follows: (1) a simple time-series model provides insufficient explanations for inner and external interactions of the stock market; (2) the variables of a time series behave in strict stationarity, but economic time-series are usually in a nonlinear or nonstationary state and (3) the forecasting factors of multivariable time-series are selected based on researcher\u2019s knowledge, and such a method is a \u201csubjective\u201d way to construct a forecasting model. Therefore, this paper proposes a causal time-series model to select forecasting factors and builds a machine learning forecast model. The \u201cGranger causality test\u201d is utilized first in the proposed model to select the critical factors from technical indicators and market indexes; next, a \u201cmultilayer perceptron regression (MLPR)\u201d is employed to construct a forecasting model. This paper collected financial data over a 13-year period (from 2003 to 2015) of the Taiwan stock index (TAIEX) as experimental datasets. Furthermore, the root mean square error (RMSE) was used as a performance indicator, and we use five forecasting models as comparison models. The results reveal that the proposed model outperforms the comparison models in forecasting accuracy and performs well for three key indicators. LAG1, S&amp;P500 and DJIA, are critical factors in all 11 of our time sliding windows (T1\u2013T11). We offer these results to investors to aid in their decision-making processes. <\/jats:p>","DOI":"10.1142\/s0219622019500421","type":"journal-article","created":{"date-parts":[[2019,10,11]],"date-time":"2019-10-11T03:29:03Z","timestamp":1570764543000},"page":"1967-1987","source":"Crossref","is-referenced-by-count":5,"title":["A Causal Time-Series Model Based on Multilayer Perceptron Regression for Forecasting Taiwan Stock Index"],"prefix":"10.1142","volume":"18","author":[{"given":"Tai-Liang","family":"Chen","sequence":"first","affiliation":[{"name":"Department of Digital Content Application and Management, Wenzao Ursuline University of Languages, Kaohsiung, Taiwan 807, R.O.C."}]},{"given":"Ching-Hsue","family":"Cheng","sequence":"additional","affiliation":[{"name":"Department of Information Management, National Yunlin University of Science and Technology, Yunlin, Taiwan 640, R.O.C."}]},{"given":"Jing-Wei","family":"Liu","sequence":"additional","affiliation":[{"name":"Department of Sport Information and Communication, National Taiwan University of Sport, Taichung, Taiwan 404, R.O.C."}]}],"member":"219","published-online":{"date-parts":[[2019,12,3]]},"reference":[{"key":"S0219622019500421BIB001","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2014.02.137"},{"key":"S0219622019500421BIB002","doi-asserted-by":"publisher","DOI":"10.1016\/j.ejor.2019.03.009"},{"key":"S0219622019500421BIB003","doi-asserted-by":"publisher","DOI":"10.3846\/tede.2019.9383"},{"key":"S0219622019500421BIB004","doi-asserted-by":"publisher","DOI":"10.3846\/tede.2019.8740"},{"key":"S0219622019500421BIB005","first-page":"14","volume":"11","author":"Gupta S.","year":"2010","journal-title":"Australia Journal of Intelligent Information Processing System"},{"key":"S0219622019500421BIB006","first-page":"1","volume-title":"Proc. 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