A Nonlinear Autoregressive Model with Exogenous Variables Neural Network for Stock Market Timing: The Candlestick Technical Analysis
Publish Year: 1395
نوع سند: مقاله ژورنالی
زبان: English
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شناسه ملی سند علمی:
JR_IJE-29-12_010
تاریخ نمایه سازی: 9 خرداد 1396
Abstract:
In this paper, the nonlinear autoregressive model with exogenous variables as a new neural network is used for timing of the stock markets on the basis of the technical analysis of Japanese Candlestick. In this model, the nonlinear autoregressive model with exogenous variables is an analyzer. For a more reliable comparison, here (like the literature) two approaches of Raw-based and Signal-based are devised to generate the input data of the model. The correct predictions percentages for periods of 1- 6days with the total number of buy and sell signals are considered. The result proves that to some extent the approaches have similar performances while apparently, they are superior to a feed-forward static neural network. The created network is evaluated by the measure of Mean of Squared Error and the proposed model accuracy is calculated to be extremely high
Keywords:
Finance , Stock Market Forecasting , Technical Analysis , NARX Recurrent Neural Network , Levenberg–marquardt Algorithm
Authors
e Ahmadi
Department of Industrial Engineering, Yazd University, Yazd, Iran
m.h Abooie
Department of Industrial Engineering, Yazd University, Yazd, Iran
m Jasemi
Department of Industrial Engineering, Khajeh Nasir Toosi University of Technology, Tehran, Iran
y Zare Mehrjardi
Department of Industrial Engineering, Yazd University, Yazd, Iran