A Critical Transformation of Trend Deterministic Technical Indicators for the Short Term Prediction of Stock Market Trading Strategies

A stock market is a market where company stocks or share offers are issued and exchanged through trades. Stock prices are defined by five price characteristics: open, high, low, close, and volume over a particular period. By analyzing the historical prices of the stocks, one can get better predictions of stock prices. Technical analysis of stocks is often performed using various statistical measures known as Technical indicators which can be used to predict the future price trends and patterns. A large number of machine learning techniques are available for technical analysis of the stock market with the help of indicators. This paper addresses in-depth exploration of various technical indicators which can be effectively utilized for machine learning-based technical analysis and thereby contributing to the prediction of stock prices over a short time frame. We have used a 10 years historical dataset of NIFTY-50 index of Indian stock market. This dataset is then transformed to indicator wise buy/sell dataset and which then applied on machine learning algorithms: MP-ANN, SMO, and RF. Based on indication or trading signal given by indicators, traders can formulate the strategy to earn maximum profit.