Different types of stock market analysis
The stock market plays a key role in economic development as it is a source of mobilizing domestic savings. A stock market typically has different financial instruments, giving investors an opportunity to diversify their portfolios. A liquid stock market facilitates the optimal allocation of capital resources and aids the accelerated economic growth of a country. The need of achieving efficiency in capital allocation makes the development of the stock market a necessity. The stock market analysis aims at predicting the movement of the stock market and price behaviour and can be classified into two categories: fundamental and technical analysis (Shah, Isah, & Zulkernine, 2019).
Importance of performing stock market analysis
Studies have been conducted in the past to prove the impact of the stock market on economic growth. For example, Antonio’s (2010) study shows a causal relationship between the stock market and Germany’s economic growth. The development of the stock market provides the economy with an opportunity to avail of the benefit of financial services and liberalize the financial system.
Paramati & Gupta, (2011) supported the results of Antonios in their analysis of the Indian stock market, asserting that the financial market is a platform that fulfils the investors’ need to transform funds into assets and mobilise them. As stock markets either increase the efficiency of investment by allocating funds efficiently through their financial intermediaries or provides more sources of investment. In both cases, the stock market stimulates the long-term development of the economy. The figure below demonstrates the benefits of the stock market to an economy.
Taking decisions from the stock market analysis
Mahajan & Singh, (2015) studied the data of the Bombay stock exchange and examined the linkage between the volume of trading, return, and volatility. The technical analysis of the stock market shows that as the volume of trading changes, the rate of return increases. On the contrary, large volumes of trading reduce the volatility rate of the stock market. Stock market data has challenges such as nonlinearity, nonparametric, nonlinear, dynamic, chaotic, and noisy nature.
Huang, Yang, Yang, & Sheng, (2014) studied the sentiment of investor and their impact on returns through Principle Component Analysis. This technical analysis has shown that the sentiment of investors about a stock does affect positively the return but in the case of a lag period, the effect is negative. Furthermore, the nature of the investor also differentiates the effect on return. An optimistic investor who is confident in the future tends to earn from the investment but a pessimistic investor with a feeling of doubt tends to lose.
Furthermore, the financial status of investors, the source of investment information, and the attitude of investors towards risk have a significant impact on investment decisions (Annamalah, Raman, Marthandan, & Logeswaran,2019). Hence, the behaviour of an investor is influenced by risk, return, and source of stock market information.
In this type of analysis, the investor analyzes the status of the stock by examining its financial statements. Critical ratios that the investor assesses are Return on Equity (ROE), Earning per share (EPS), Debt-Equity Ratio (DER), Price Book value ratio (P/B), and Price to Earnings ratio (P/E). Moreover, the investor assumes that the market price does not yield the true value of the company due to the presence of uncontrollable factors. The criteria while analysis is that the stocks having a high price-to-earnings ratio tend to perform better than the stocks having a low price-to-earnings ratio (Beneda, 2002). Value stocks tend to have a high value of Book to Market (B/M) ratio and E/P (Earning to Price) ratio compared to growth stocks and thus lead to having significantly better returns (Zacharia, 2009). Investors looking for higher returns invest in growth stocks, whereas those looking for long-term steady returns will invest in value stocks (Hoekjan, 2011).
In the existing volatile market, accurate prediction of the market’s future trends is important but complicated. The shortcoming of fundamental analysis is its inability to predict stock market trends accurately. Technical analysis examines the historical movement of the stocks via charts, trend analysis, statistical analysis, or machine learning to make predictions about future movements. Herein, the volatility of the stock market represents the dispersion of the returns. The presence of high volatility indicates a higher risk. An investor opts for less volatile stocks to reduce the risk (Yadav, 2017). Apart from volatility-based examination, time series analysis using closing prices can be used for predicting the movement of stock prices (Rajput & Bobde, 2016). Technical analysis assumes that it is difficult to predict stock market trends, therefore it either tracks the direction of the price movements or examines human sentiment (Devi et al., 2011; Shah et al., 2019a).
Risk-Return relationship as an effective technical form of analysis
In order to understand the technicality of the stock market, there is a need to understand the dynamics of the market along with studying the behaviour of investors. Technical analysis by categorizing stocks using the price-to-earnings ratio, price-to-book value ratio, and dividend yield, compares the performance of stocks. Hence, the stock market analysis by studying the risk-return relationship of stocks increases the possibility of sound returns along with creating an effective opportunity for the development of the stock market.
- Annamalah, S., Raman, M., Marthandan, G., & Logeswaran, A. K. (2019). An empirical study on the determinants of an investor’s decision in unit trust investment. Economies, 7(3), 1–23. https://doi.org/10.3390/economies7030080
- Antonios, A. (2010). Stock Market and Economic Growth: An Empirical Analysis for Germany. Business and Economics Journal. https://doi.org/10.3844/ajebasp.2012.135.143
- Beneda, N. (2002). Growth stocks outperform value stocks over the long term. Journal of Asset Management, 3(2), 112–123. https://doi.org/10.1057/palgrave.jam.2240070
- Devi, B. U., Sundar, D., & Alli, P. (2011). A Study on Stock Market Analysis for Stock Selection – Naïve Investors ’ Perspective using Data Mining Technique. International Journal of Computer Applications, 34(3), 19–25.
- Hoekjan, R. M. (2011). The Performance of Value Vs . Growth Stocks During the Financial Crisis.
- Huang, C., Yang, X., Yang, X., & Sheng, H. (2014). An empirical study of the effect of investor sentiment on returns of different industries. Mathematical Problems in Engineering, 2014. https://doi.org/10.1155/2014/545723
- Mahajan, S., & Singh, B. (2015). An empirical analysis of stock price-volume relationship in Indian stock Market. https://doi.org/10.1007/BF02880831
- Paramati, S. R., & Gupta, R. (2011). An empirical analysis of stock market performance and economic growth: Evidence from India. International Research Journal of Finance and Economics, 73(July 2018), 144–160. https://doi.org/10.2139/ssrn.2335996
- Rajput, V., & Bobde, S. (2016). Stock market forecasting techniques: Literature survey. International Journal of Computer Science and Mobile Computing, 5(6), 500–506.
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- Shah, D., Isah, H., & Zulkernine, F. (2019b). Stock market analysis: A review and taxonomy of prediction techniques. International Journal of Financial Studies, 7(2). https://doi.org/10.3390/ijfs7020026
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