GRG School of Management Studies, Peelamedu, Coimbatore, TN, India Abstract Technical Analysis is a study of the stock market relating to factors affecting the supply and demand of stocks and also helps in understanding the intrinsic value of shares and to know whether the shares are undervalued or overvalued. The stock market indicators would help the investor to identify major market turning points. This is a significant technical analysis of selected companies which helps to understand the price behaviour of the shares, the signals given by them and the major turning points of the market price.Any investor or trader must certainly consider technical analysis as a tool whether to buy the stock at a particular point of time though it is fundamentally strong.
The objective of the present project is to make a study on the technical analysis on selected stocks of energy sector and interpret on whether to buy or sell them by using techniques. This in turn would help investors to identify the current trend and risks involved with the scrip on par with market. The study is purely based on secondary sources which includes the historical data available from the website. For the purpose of analysis, techniques like Beta, Relative Strength Index and Simple Moving average is used for the analysis to know if the stock is technically strong. Keywords Stocks market, Technical analysis, Risk, Investment.I.
Introduction Technical Analysis is a study of the stock market considering factors related to the supply and demand of stocks. Technical analysis is a method of evaluating securities by analyzing the statistics generated by market activity, such as past prices and volume.Technical analysts do not attempt to measure a securities intrinsic value, but instead use charts and other tools to identify patterns that can suggest future activity. In fact the decision made on the basis of technical analysis is done only after inferring a trend and judging the future movement of the stock on the basis of the trend. Technical Analysis assumes that the market is efficient and the price has already taken into consideration the other factors related to the company and the industry.It s because of this assumption that many think technical analysis is a tool, which is effective for shortterm investing.
The study on technical analysis of selected companies based on Stratified sampling technique is significant as it helps in understanding the intrinsic value of shares and to know whether the shares are undervalued or overvalued or correctly priced. It becomes essential to know the performance of the company so that the investment will be duly giving returns and ensure safety of the investment.Further it helps in understanding the price behaviour of the shares, the signals given by them and the major turning points of the market price. The Technical analysis concentrates on plotting the price movements of stock, drawing inferences from the price movements in the market. It is an approach by prediction of future prices through the forces like supply and demand.
It is very much useful for a speculator who aims at profit margins.II. Review of Literature Cooter (1962) found that the stock prices move at random when studied at one week interval. The data for his study was weekend prices of forty five stocks from New York stock exchange . He tested randomness of share by means of a mean square successive difference test.
He concluded that there was not one random walk model. He concluded that the share price trends could be predicted when studied at fourteen-week interval. But in total the stock prices followed a random walk at weekly intervals. [6]Eugene F. Fama (1965) has answered the questions to what extend can the past history of a common stock price can be used to make meaningful predictions concerning the future prices of the stock? The theory of random walk on stock prices is studied with two hypotheses.
They are i) Successive price changes are independent and ii) The price changes conform to some probability distribution. The data for this study consists of daily prices for each of the thirty stocks of the Dow –Jones industrial average. This study concludes that there is strong and voluminous evidence in favour of random walk theory.Ramaswami.
K (1996) assessed the relationship among book values, earnings, dividend and market price of share, impact of bonus issues, impact of security scam on equity return . to that end, the author used daily share price of 30 companies included in the construction of BSE sensitive index, daily data of BSESI and NYSE composite index, annual data on BV per share market price per share, EPS and DPS and data on bonus issue made ,during the period of study ,the researcher used correlation ,regression and frequency distribution for interpreting data.Sharma and Robert E. Kennedy (1977) tested the applicability of random walk hypothesis to the stock market in developing country namely India and compare this to that of stock markets in developed countries namely USA, and England. For this purpose the price behavior of Bombay stock exchange is statistically examined both for randomness and independence .
The test the random walk hypothesis. The test covers 132 monthly observations for each stock market index of common stock listed in Bombay exchange for eleven years from 1968-1973.The study indicates that price dependence while statistically significant, is comparably small in the developing countries. Based on the test, it is evident that the Bombay stock exchange stock obeys a random walk and is equivalent to developed countries stock exchange. [7]Fernando Fernandez –Rodriguez, Simon Sosvilla –Rivero, Julian Andrada –Felix (1999) assessed whether some simple forms of technical analysis can predict stock price movement in the Madrid stock exchange, covering thirty-one-year period from Jan 1966 –Oct 1997.
the results provide strong support for profitability of those technical trading rules.By making use of bootstrap techniques the author shows the returns obtained from these trading rules are not consistent with several null models frequently used in finance. [16]C. L.
Osler ( 2001) provides a microstructural explanation for the success of two familiar predictions from technical analysis: (1) trends tend to be reversed at predictable support and resistance levels, and (2) trends gain momentum once predictable support and resistance levels are crossed. The explanation is based on a close examination of stop-loss and take-profit orders at a large foreign exchange dealing bank.
