Data Analysis, Visualization and Prediction of Stock Market Prices of K-Electric

Predicting stock price is a trend yet very challenging task. It because the prices depend upon several internal and external factors. Stock prediction can be useful for financial sectors government help in informed decision-making. This paper analyzes market of K-Electric Karachi. found that K-electric on refinery sector. The data two sectors. Also, compares based moving average, auto-regressive integrated average (ARIMA), convolutional neural network long short-term memory (LSTM) model. ARIMA outperforms other algorithms. A set experiments were conducted to test performance algorithms analyzed different metrics such as root mean square error (RMSE), absolute (MAE) percentage (MAPE).