Stock market trends forecast is one of the most current topics and a significant research challenge due to its dynamic and unstable *** stock data is usually non-stationary,and attributes are non-correlative to each *...
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Stock market trends forecast is one of the most current topics and a significant research challenge due to its dynamic and unstable *** stock data is usually non-stationary,and attributes are non-correlative to each *** traditional Stock Technical Indicators(STIs)may incorrectly predict the stockmarket *** study the stock market characteristics using STIs and make efficient trading decisions,a robust model is *** paper aims to build up an evolutionary deep learning model(EDLM)to identify stock trends’prices by using *** proposed model has implemented the deeplearning(DL)model to establish the concept of *** analysis of the dataset of three most popular banking organizations obtained from the live stock market based on the National Stock exchange(NSE)-India,a Long Short Term Memory(LSTM)is *** datasets encompassed the trading days from the 17^(th) of Nov 2008 to the 15^(th) of Nov *** work also conducted exhaustive experiments to study the correlation of various STIs with stock price *** model built with an EDLM has shown significant improvements over two benchmark ML models and a deeplearning *** proposed model aids investors in making profitable investment decisions as it presents trend-based forecasting and has achieved a prediction accuracy of 63.59%,56.25%,and 57.95%on the datasets of HDFC,Yes Bank,and SBI,*** indicate that the proposed EDLA with a combination of STIs can often provide improved results than the other state-of-the-art algorithms.
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