An Analysis of Stock Price Prediction Techniques

Abstract

As the stock market is an intricate, complex activity influenced by hundreds of factors, predicting such prices with accuracy or absolute conviction is quite difficult. This chapter focuses on the potential use of support vector machines (SVM), decision tree algorithm, and ARIMA model for predicting stock market prices using specific data obtained from Yahoo Finance. The authors train the model using daily price data derived from Yahoo Finance and make great efforts to estimate how well the model predicts market prices. The chapter adds value to the existing knowledge by showing that algorithms tend to work in this field. Insights from the study will help investors and traders take a better course of action in the market.