Portfolio Construction through Price Earnings Ratio: Indian Evidence

Transcription

1 Portfolio Construction through Price Earnings Ratio: Indian Evidence Abhay Raja* Abstract: Fundamental and Technical analyses are bases for market participants to trade in. The objective of all tools is to identify and predict the direction in which prices are likely to move. The problem arises when contradictory results given by different tools lead to confusion. By considering this fact, stock markets are seldom compared with gambling and horse races with the argument of luck factor for creating winning strategies. The question underlying this study is whether single tool can help out in analysis of trends. Few experts have attempted applying one single as a base for portfolio construction. This study attempts to evaluate Price Earnings Ratio as a single tool for selecting securities to trade in. In this study, the sample of BSE 100 companies is taken and four portfolios are constructed by applying criterion of Price Earnings Ratio. Further, the portfolios are evaluated by Indices given by Sharpe, Treyner and Jenson based on 5 years returns. Key words: Portfolio, Price Earnings Ratio * Research Scholar, Department of Business Management Saurashtra University, Rajkot. 1

2 Portfolio Construction through Price Earnings Ratio: Indian Evidence Abhay Raja* Introduction: Stock markets are famous for its randomness in reacting over different situations. Studies conducted by Louis Bachelier (1900) and Maurice Kendall (1953) were foremost in initiating formal concepts of random walk theory. On the contrary, Fama, Fisher, Jensen and Roll (1969) gave birth to the concept of Efficient Market Hypothesis. However, there are many studies stating inefficiencies of stock markets. This incongruity is the reason why stock markets are often compared to operations in gambling dens where winning strategies can be achieved only if they are backed by luck factor. Different sentiments of faith and phobia lead investors to take a position in the market. There is no dearth of experts offering advice and strategies to investors. However, season investors like to manage their funds optimally. They bet their investments based on detailed analysis with different scientific methods and techniques. Analysts have developed various tools and techniques to forecast price trends. Several of these techniques are time-tested, while several are still in infancy. For this purpose, one needs to understand proper time, security, assets allocation, and most importantly proper tools for analysis. While constructing portfolio, one has to continuously measure performance of those individual securities and entire portfolio as well. In last few decades several techniques are evolved to measure and compare performance of various portfolios. In this study four portfolios were formed by keeping P/E ratio as a criterion and tools of portfolio performance evaluation (Sharpe, Treynor and Jensen) are applied thereon. The aims are very simple, i.e. to test soundness of P/E multiple as a sole criterion to construct portfolio and to test the result of the study as empirical evidence in Indian context. * Research Scholar, Department of Business Management Saurashtra University, Rajkot. abhay.raja@yahoo.com 2

3 Review of Literature: Study conducted by Nicholson (1960) was the pioneer in demonstrating P/E effect. He has chosen 100 industrial stocks for the periods of twenty years from 1939 to The portfolio with lowest P/E stocks was rebalanced after every five years. Investment in that portfolio would have delivered 14.7 times better returns at the end of 20 years compared to 4.7 times returns over highest P/E portfolios. Nicholson has extended his work in 1968 by choosing 189 companies for the period from 1937 to He has divided companies into five groups by keeping P/E multiple as a base. He found that average returns for 7 years were percent per annum (131 percent total) for the companies with P/E multiple of less than 10. At the same time it was 7.97 percent for the stocks with P/E multiple over 20. He concluded: The purchaser of common stocks may logically seek the greater productivity represented by stocks with low rather than high price earnings ratios. In Indian context, Basu published two papers in 1975 and The inferences were in the line with Nicholson s results. He studied price performance of NYSE from 1957 to He also ranked stocks based on the P/E multiple over 14 years. Average returns per annum were 9.3 percent for the highest P/E stocks, with a beta of 1.11, as compared to 16.3 percentage return with a beta of 0.99 for the lowest P/E stocks. Campbell and Shiller (1988) reported that almost 40 percent variance of future returns were because of initial P/E ratios. Contradicting over random walk theory they concluded that, up to considerable extent, equity returns can be predictable. A study with a little different view point was conducted by Fama, Eugene and French (1988). They inferred that a very little additional influence can be attributed to P/E multiples. They said that firm size and P/BV together provide considerable explanatory power for future returns. However, they did not disassociate P/E multiple as a tool for investment planning. A little different study carried out by Lakonishok, Schleifer and Vishny (1994) defined the phenomena of value strategies as buying shares with low prices by considering some indicators of fundamental value such as; earnings, book value, dividends or cash flows etc. They observed stock prices from 1963 to They divided firms into 'value' or 'glamour' stocks by keeping sales and future expected growth as base and impliedly focused on P/E 3

4 ratio. They observed differences in expected future growth rates between both types of securities. Ironically, their important observation was that glamour stocks had faster growth for first 2 odd years and thereafter growth rates of both groups were almost same. Dreman and Lufkin (1997) also investigated value strategies within industries. They picked largest 1500 companies from 1970 to They formed portfolio and conferred that portfolio with high P/E and dividend yield gave below market returns for the study period, where as portfolio with low P/E and dividend yield generated above market returns for the same period. They found that strategy to keep P/E as a sole criterion for portfolio construction gave statistically insignificant returns to the market average. Research Method: The basic postulate underlying this study is to test the phenomenon of P/E multiple as a tool for effective portfolio construction. Simultaneously, this study also aims to provide empirical evidences in Indian context to use P/E multiple as a standard to create portfolio. Along these lines, the objectives thereof lie twofold: i) to examine P/E ratio as an effective tool for portfolio construction; and ii) to provide Indian evidences to the similar studies carried out in past. For the purpose of addressing this problem and satisfying these objectives the researcher has selected BSE 100 stocks and analyzed them for last five years i.e to In order to calculate average monthly returns of last five years, the securities which were listed after April 2007 were removed from samples. Further, for a few securities required data was not available. In this process, final sample of the study reduced to 76 companies in all. By applying the criterion of P/E multiple, the sample stocks were arranged in ascending order from lowest P/E multiple to highest P/E multiple. By following this sequence, 76 sample stocks were divided into four different portfolios. Portfolio 1 consisted of the first 19 companies having lowest P/E multiple. In the same way, portfolio 2 was constructed out of next 19 companies having higher P/E multiple than the first portfolio. Third and fourth portfolios were constructed along the same lines. The required data related to stock prices, P/E multiple and Beta were sourced through the Prowess database of CMIE (Centre for Monitoring Indian Economy). In order to compare performance of these four portfolios average monthly returns were computed. 4

5 Portfolio Performance Indices: It is evident that only returns are not sufficient enough for measuring performance of any portfolio. Portfolio returns must be evaluated against risk undertaken by each portfolio. In order to couple return and risk, Sharpe, Treynor and Jensen are the proven tools, which are considered here as tools for measuring performance of all the four portfolios. Sharpe Si = (Portfolio Return Risk-Free Rate) / Standard Deviation Treyner Tn = (Portfolio Return Risk-Free Rate) / Beta Jensen Jensen's Alpha = Portfolio Return Benchmark Portfolio Return Where: Benchmark Return (CAPM) = Risk Free Rate of Return + Beta (Return of Market Risk-Free Rate of Return) Data Analysis and Interpretation Table: 1 Descriptive Statistics of Portfolios Average Return P/E Beta S.D. Portfolio Portfolio Portfolio Portfolio The above data table represents the descriptive statistics of all portfolios. The basic postulate of the research is to test P/E multiple as sole criterion to construct portfolio. Calculations of average returns suggest that the portfolio consisting stocks with lowest P/E generated best returns (average monthly returns) compared to all other portfolios i.e percent. However, it was worth noticing that the risk factor (beta and standard deviation) was also negatively 5

6 correlated with P/E multiple. Beta and standard deviation for portfolio 1 were the highest, 1.21 and respectively. Chart 1 Average Returns and P/E Ratio Table: 2 Correlations Average Returns P/E Ratio Average Pearson Correlation Returns Sig. (2-tailed) P/E Ratio Pearson Correlation Sig. (2-tailed) Further, there was an attempt made by researcher to test correlations between P/E multiple and average returns. It was again at par with the basic hypothesis of the study that low P/E stocks generate higher returns. The correlation coefficient was negative 0.95 which supports the hypothesis of the study. The results were surprising as the corrlation is near to perfectly positive that means that any stock with lower P/E multiple always perform better than the stocks with lower P/E multiple. 6

7 Table: 3 Portfolio Performance Indices Sharpe Terynor Jenson Rank Portfolio Portfolio Portfolio Portfolio Chart 2 Portfolio Perfomance Indices From the above data tables; it is evident that portfolio composing of stocks with lowest P/E multiple (portfolio 1) has clearly outshined in comparison with other portfolios with higher P/E multiple stocks. According to all the three performance evaluation index portfolio 1 stands out and gave the best return of 3.10 percent with lowest P/E of Most importantly the portfolio rank accroding to performance indices were in descending order. This means that performance of the portfolio with higher P/E stocks was inferior to that of the portfolios with lower P/E stocks. 7

8 This finding is in line with the findings of Nicholson (1960 and 1968), Dreman and Lufkin (1997), who found that strategy to keep P/E as a sole base gave returns that were statistically insignificant to the market average. The inferences derived by Basu (1975 and 1977) in Indian context were also in the same line of the conclusion underlying this study: The purchaser of common stocks may logically seek the greater productivity represented by stocks with low rather than high price earnings ratios. Conclusion: The prime objective of investment is to generate optimum returns. To achieve this purpose one should try to anaylze various securities from the view point of future potential returns. Market participants use ample tools to undergo the analysis, which may lead to confusion. So, the most important job is to select the proper tool for analysis. It is evident form the above analysis that investing in stock with lower P/E multiple creates sound possibility for better returns. Even the correlation coefficient also gives the similar results. P/E multiple and returns are negatively correlated. The results are in line with the findings of almost all the literature that is reviewed. References: 1. Bachelier, Louis (1900) trans. James Boness. Theory of Speculation, in Cootner (1964) pp Basu, S., 1975, The Information Content of Price-Earnings Ratios, Financial Management: Basu, S.,1977, The Investment Performance of Common Stocks in relation to their Price-Earnings Ratios, Journal of Finance: Campbell, John Y. and Robert J. Shiller, 1988, Stock Prices, Earnings, and Expected Dividends, Journal of Finance: Dreman, D.N. & Lufkin, E.A.,1997 Do Contrarian Strategies work within Industries? Journal of Investing: Fama, Eugene, Lawrence Fisher, Michael Jensen and Richard Roll (1969). The Adjustment of Stock Prices to New Information, International Economic Review, 10, pp Fama, Eugene and Kenneth French, 1988, Permanent and Temporary Components of Stock Prices, Journal of Political Economy:

9 7. Jensen, M. C., The Performance of Mutual Funds in the Period , Journal of Finance, vol. 23, May 1968, pp Kendall, Maurice (1953). The Analysis of Economic Time Series, Journal of the Royal Statistical Society, Series A, 96, pp Lakonishok, J., Schleifer, A. & Vishny R, Contrarian Investment, Extrapolation, and Risk Journal of Finance: Nicholson, S.F., 1960, Price-Earnings Ratios Financial Analysts Journal: Nicholson, S.F., 1968, Price-Earnings Ratios in relation to Investment Results Financial Analysts Journal: Sharpe, W. F., Mutual Fund Performance, Journal of Business, January 1966, pp Treynor, J. L., How to Rate Management of Investment Funds, Harvard Business Review 43, January-February 1965, pp