چکیده مقاله
In this study, arguing that both technical analysis and prediction using classical methods have a high potential for predicting price and stock behavior in the future; a model has been developed in the form of a wide ranging neural network for predicting stock prices For this purpose, at first, three databases were constructed to forecast the price of three shares of Parsian Bank, Mobarakeh Steel, Esfahan and Fars chemical industries Then, according to the clustering method, the row and column headings of the databases were reduced and the most similar time series to the target time series were identified in each database Finally, the remaining criteria in the databases were entered as neural network inputs with a hidden layer and the network learning algorithm was selected The results of the proposed network were compared with the predicted results by multiple regression and time series regression methods and two criteria of MSE and MAD were investigated The function of the neural network was well seen in predicting prices in all three databases and both
کلیدواژهها
نویسندگان
Elnaz Shahnaei
MSc Financial Engineering Kooshyar higher education institute Rasht,Iran
Ahmad Asl Hadad
Associate Professor of K N Toosi University of Technology Tehran,Iran
Somayeh Fallahpour
MSc Health Economic University of Tehran Tehran,Iran
شیوه ارجاع
Shahnaei, Elnaz and Asl Hadad, Ahmad and Fallahpour, Somayeh,1397,Stock price forecast using clustering and meta-initiative algorithm (Neural networks ),International Conference on Innovation and Research in Engineering Sciences
ارائهشده در
مجموعه مقالات کنفرانس بین المللی نوآوری وتحقیق در علوم مهندسی(ICIRES ۲۰۱۸)27 تیر 1397