A FEATURE LEVEL FUSION SYSTEM AND METHOD FOR STOCK PRICE FORECASTING

摘要

Disclosed are a feature convergence based stock price prediction method and a system therefor. According to an embodiment of the present invention, a stock price prediction method performed by a prediction system comprises the steps of: extracting each feature by learning KOSPI index data and foreign index data by using a stacked noise elimination auto-encoder; inputting the extracted each feature into an input layer of a deep artificial neural network, and storing a prediction model generated by synthesizing each feature input to the deep artificial neural network; and predicting the stock price of a stock item included in the KOSPI index by using the stored prediction model. In the step of storing the prediction model, a prediction model can be generated by learning the stacked noise elimination auto-encoder and the deep artificial neural network.