A FEATURE LEVEL FUSION SYSTEM AND METHOD FOR STOCK PRICE FORECASTING

摘要

A method and system for predicting stock prices based on feature fusion is disclosed. The stock price prediction method performed by the prediction system according to an embodiment includes: extracting each feature as learning the KOSPI index data and the foreign index data using a stacked noise reduction autoencoder; Inputting each of the extracted features into an input layer of a deep artificial neural network, and storing a prediction model generated as each feature input to the deep artificial neural network is synthesized; And predicting a stock price of an item included in the KOSPI index using the stored prediction model, and in the storing of the prediction model, learning the stacked noise removal autoencoder and the deep artificial neural network to obtain a prediction model. Can be created.