Literature Review on Prediction Analysis for Stock Market Investment and Return

  • R. Leela Devi, Dr. N. Puviarasan
Keywords: Prognostics of stock, volatility, technical analysis, ML techniques

Abstract

The stock market is one of the most vital components of a free-market economy. A stock market is a designated market for trading various kinds of securities of publicly-held companies and other eligible financial instruments in a controlled, secure and managed environment. Stock Market deals are primarily characterized by dynamic swift, unpredictability in stock prices and hence are non-linear in nature. A stock price depends on various factors viz. company’s product demand, financial performance, new economic policies as announced from time to time by the country as well as by other nations and ultimately on the political situation of the country. Further challenges like war, epidemic, natural calamities etc., have also its influence in the stock market. Hence predicting the movement of stock prices assumes an ever-challenging task, Stock market prognostics deals with finding the market trends, planning, investment tactics, identifying the stocks to purchase, time of purchase, holding period and the exit strategy.

Despite the fact that stock market transactions are primarily focused on maximising profits, it is unavoidable that losses may occur from time to time. Profit and loss maximisation are key objectives for forecasting stock prices. This job requires the assumption of publicly accessible fundamental information that has some predictive connections to future stock returns in order to maximise profit and minimise loss. Stock prediction is a field of study in which many academics have shown an interest over the last few years/decades, and this has continued into the present. In the past, there have been two major methods to forecasting the stock price: technical analysis and fundamental analysis. The first is fundamental / qualitative analysis, which is based on the performance of the business, and the second is technical analysis, which is based on the historical price of stocks, such as the open, high, low, close, and volume traded in the stock market over a period of time. According to the findings of this literature review, significant research has already been done on stock prediction across the globe, involving fundamental analysis, technical analysis, and sentiment analysis, all of which have been combined with machine learning techniques, and these studies have also produced positive results. The study comes to the conclusion that numerous research academics have shown an interest in the areas listed above, with a particular emphasis on the concrete benefits of stock return

Published
2021-08-10
How to Cite
Dr. N. Puviarasan, R. L. D. (2021). Literature Review on Prediction Analysis for Stock Market Investment and Return. Design Engineering, 7798- 7808. Retrieved from http://thedesignengineering.com/index.php/DE/article/view/3294
Section
Articles