文章基本信息

标题：Forecasting Stock Market Trends by Logistic Regression and Neural Networks: Evidence from KSA Stock Market
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作者：Dr. Makram ZAIDI ; Dr. Amina AMIRAT Grace Ofori-Abebrese
期刊名称：Euro-Asian Journal of Economics and Finance
印刷版ISSN：2310-0184
电子版ISSN：2310-4929
出版年度：2016
期号：2
页码：9
语种：English
出版社：Academy of Business & Scientific Research
摘要：Forecasting stock market trends is very vital for investors to take action for the next period for sustainable competition. It is especially important for policy makers to predict actions for development. KSA stock market is evolving rapidly. Due to increasing importance; the aim of this study is to forecast the stock market trends by using logistic model and artificial neural network. Logistic model is a type of probabilistic statistical classification model. It is also used to predict a binary response from a binary predictor, used for predicting the outcome of a categorical dependent variable(i.e., a class label) based on one or more predictor variables (features). Artificial neural networks are models which are used for forecasting because of their capabilities of pattern recognition and machine learning. Both methods are used to forecast the stock prices of upcoming period. The model has used the preprocessed data set of closing value of TASA Index. The data set encompassed the trading days from 5th April, 2007 to 1st January, 2015. Both methods give us estimation with up to 80% accuracy.