Abstract:

Machine Learning plays an important role in the society. It is increasing the dependency on the ML techniques to increase the efficiency and accurate decision making on investments. One of the places where the smart decision is to be applied is the Stocks. Stocks are the main instruments of investment in the market which are helpful to the society and also to the individual. There is a saying that “Right Decision at Right Time” will effect the financial position with in no time. If wrong decision is taken this may lead to problems. A simple Calculation of predicting the price fluctuations in the Stock Market is the main smart decision to follow. So, for this situation, in this study we are trying to apply the Machine Learning Techniques for correct guidance in decision Making. As this is related to Time series data, ie., recording the previous day to day transaction and making the machine learn the things and predict for the future dates. . In this paper we propose a Machine Learning (ML) approach that will be trained from the available stocks data and gain intelligence and then uses the acquired knowledge for an accurate prediction. In this context this study uses a machine learning technique called Support Vector Machine (SVM) to predict stock prices

Description:

Time Series, Machine Learning, Stock Market, Prediction, Logistic Regression, Support Vector Machine, XG Boost