Pattern Prediction in Stock Market

Financial Time Series Stock Price Prediction using Deep Learning

“…To demonstrate the proposed technique they considered the popular Nasdaq-100 index of Nasdaq Stock and analyzed the 24 months stock data for Nasdaq-100 main index as well as six of the companies listed in the Nasdaq-100 index. Support Vector Machines (SVM) and Support Vector Regression (SVR) [7,8] have also been used to predict financial time series and gain high predictive accuracy. In the financial time series modeling using SVR the key problem is the high noise.…”

“…The experimental results show that the proposed model outperforms the SVR model with non-filtered forecasting variables and a random walk model. The researchers [8] have proposed pattern prediction in stock market using least square support vector regression to predict next fifteen days of stock prices.…”

“…This gate used sigmoid function for computation. Furthermore, in the LSTM architecture peepholes connections (green line) form its internal cells were applied to all gates in the same cell for learning precise timing of the outputs [8] (see Fig 1).…”