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1 A Study on Determinants of Short Term on Stocks in the S&P00 Uday kumar Jagannathan 1, N Suresh 2 1,2 Faculty of Management and Commerce, Department of Management Studies M. S. Ramaiah University of Applied Sciences, Bangalore Contact Author E- mail: ujagannathan.ms.mc@msruas.ac.in Abstract Several research papers exist on whether stock market movement can be predicted or t. This paper uses data from 00 stocks in the Standards and Poor s (S&P) 00 and checks the level of prediction of the selected variables and actual stock price movements, appreciation/depreciation against the predictor variables. The independent variables used are Price to Earnings (PE), Price to Sales (PS), Price to Earnings Growth (PEG), Price to Book (PB), Deviation from 200 day moving average (200D MVA), deviation from 0 day moving average (0D MVA), deviation from 2 week hi (2WH), deviation from 2 week low (2WL). Finally the yahoo finance 1 year target price (TGTP) is used as a predictor variable for the short term appreciation or depreciation of the stock price. Short term returns are assumed to be share price returns for the 10 month period between October 2014 and August 201. The method used to calculate the return is the difference in stock price in August 201 and October 2014, plus any dividends paid in the time period, the result divided by the stock price in October 2014.The calculated return is regressed against the variables PE, PEG, PB, PS, 200DMVA, 0DMVA, 2WH, 2WL, TGTP. Results indicate that ne of PE, PB, PS, PB ratios is a good predictor of stock price changes (R-squared is less than.02 in each case). 200DMVA and 0DMVA are better predictors of stock price changes (R-squared is.10) and finally the stock returns are regressed against TGTP and the R-squared is close to.90, Thus, one can conclude safely that there is good correlation between 1 year target price stated in the yahoo finance portal and the actual stock price 10 months from that date. Given this level of predictive power, it may be tempting for the investor to create a portfolio of stocks where the target price exceeds the last trade price as on decision date. In order to test such portfolios, 2 random portfolios of 30 stocks were obtained from the data set of 00 stocks and the returns calculated for each of the random portfolio of stocks. If indeed the mean returns of the random portfolios exceeded the investment in an equal weighted portfolio of the 00 stocks for the same time period in question then target price is useful as a predictor. The results however indicate that the target price is t a predictor although the R-squared of the regression between target price and actual price is high and may tempt investors to use that parameter for equity purchases in the short term. Further research should explore on the disconnect between the high R-squared obtained in the regression and the inability for the investor to create a portfolio which can consistently beat the market. Key Words: Relative valuation ratios, Moving averages, 1 year Target price 1.0 INTRODUCTION: The investor needs kwledge on short term investments in the equity market. Often, he/she may be tempted to use relative valuation ratios as a determinant of equity prices in the short term - next few months to a year time frame. It is proven that over long periods of time, stocks with low PE ratios perform better than stocks with high PE ratios. But what of the short term? Does the PE ratio act as a determinant for the equity return? What of other parameters like PB ratio, PS ratio and the like? Yahoo finance puts out a 1 year target price number. We need to analyse the predictability of that number on the equity price in the short term (10 months). In addition to the relative valuation ratios, the parameters like deviation of current equity price from 200 day and 0 day moving averages as well as 2 week high and low need to be analysed. A conclusion on findings will be helpful to the short term investor as to what the expectation may be from the various parameters which are available to use as independent variables, where the dependent variable is the change in equity price (includes dividends paid if any during the time period of October 2014 and August 201). 2.0 REVIEW OF LITERATURE: Manas Mayur (2014) 1 finds that subsequent prices will increase and subsequent yields will decline in response to an increase in the P/E ratio, in large cap blue chip firms. Basu and O Shea (2014) 2 investigated equity returns in New Zealand and Australia and find evidence of a negative relationship between PE ratio and next years stock returns. Chua et al (201) 3 support that the increase in relative industry valuation Granger causes put-call parity 1 Mayur, Manas, Relationship between Price-Earnings Ratios and Stock Value in an Emerging Market (December 2, 2014). Available at SSRN: or 2 Basu, Anup K. and O'Shea, Luke, The Predictive Ability of P/E Ratio: Evidence from Australia and New Zealand (January 8, 2014) Financial Markets & Corporate Governance Conference. 3 Chua, A., DeLisle, R. J., Feng, S.-S. and Lee, B. S. (201), Price-to-Earnings Ratios and Option Prices. J. Fut. Mark., 3: doi: /fut

2 deviations, implying investors price options with greater expectation of downward movement. Hillard and Zhang (201) 4 examine the size and priceto-book effects in Chinese markets.and find strong evidence for the size effect but little evidence for the price-to-book effect. Abidin et al (201) find that the performance between positive P/E firms and negative P/E firms was significantly different, especially in terms of stock price returns, EBIT margin, current ratio, cash, assets turver, EPS growth, EBIT growth, revenue growth, and market capitalization. Zhang (201) 6 finds that the year-to-year revenue growth is found to be the most significant variable predicting a stock s short-term performance in every sub-sample period. In contrast, neither the conventional measure price-to-book r the newly proposed measure of gross profitability is significant. Bodhanwala (201) 7 focuses on constructing portfolios on the basis of PE ratio and measuring its performance against the benchmark BSE sensex for the 10 years ( ) and by using a combination of statistical tools, it is proved that portfolios formed on the basis of low PE outperform the BSE Benchmark market returns Gurrib (2014) 8 finds that rather simple moving average strategy which fits easily in the investor s world due to his or her availability and representativeness bias, is preferred over the buy and hold strategy where the latter requires more effort when bearing the two correction waves witnessed during the period. Kerl (2011) 9 checked for the accuracy of target price and finds that target price is negatively related to analyst-specific optimism and stock-specific risk (measured by volatility and price-to-book ratio). 4 Hilliard Jitka and Zhang Haoran, 201, Size and price-tobook effects: Evidence from the Chinese stock markets, Pacific-Basin Finance Journal Volume 32, April 201, Pages 40 Abidin, Sazali and Hewa Wellalage, Nirosha and Yu, Youjie and Zhao, Zhixia, Do Positive P/E Firms and Negative P/E Firms Differ in Characteristics and Performance? (January 1, 201) 6 Zhang, Zhaohui (201) Financial Ratios and Stock s on China s Growth Enterprise Market, International Journal of Finance, Vol 6, No 3 7 Bodhanwala, Ruzbeh J, Testing the Efficiency of Price-Earnings Ratio in Constructing (June 10, 201). The IUP Journal of Applied Finance, Vol. 20, No. 3, July 2014, pp Available at SSRN: 8 Gurrib, Ikhlaas, The Moving Average Crossover Strategy: Does It Work for the S&P00 Market Index? (November 30, 2014). Available at SSRN: or 9 Kerl, Alexander Gabriel, Target Price Accuracy (April 1, 2011). BuR Business Research Journal, Vol. 1, No. 1, pp , March Available at SSRN: Houmes and Chira (2014) 10 investigate how insider ownership affects the relation of PE and stock price. They show that when insider ownership is high, returns decline for low P/E firms and improve for high P/E firms. Anderson and Brooks (200) 11 look at all UK companies since 197, and using the traditional P/E ratio find the difference in average annual returns between the value and glamour deciles to be 6, The authors are able to almost double the value premium by calculating P/E ratios using earnings averaged over the last eight year. Campbell and Shiller (1998, 2001) 12 contest that the time series P/E is mean reverting and evidence that valuation ratios have been historically accurate in forecasting changes in stock price. Assuming P/E is mean reverting and the ratio takes on a value substantially above or below the mean, mean reversion implies that future prices, earnings, or both must be at least partially forecastable. Fairfield (1994) 13 shows that P/E is a function of expected changes in future profitability while the Price to Book ratio (P/B) is a function of the expected level of future profitability. The model predicts that P/B should correlate positively with the future return on book value and P/E should correlate positively with growth in earnings. Basu (1983) 14 and Banz and Rolf (1981) 1, as well as others, evidence that stock returns are positively affected by their fundamental values. Contrary to this, research by Fama and French ( , ), and Basu (197) 18 give contradictory results. They find that stock returns are negatively affected by their fundamental values. 10 Houmes, Robert and Chira, Inga, The Effect of Ownership Structure on the Price Earnings Ratio-s Amaly (November 23, 2014). International Review of Financial Analysis, Forthcoming. Available at SSRN: 11 Anderson K. and Brooks C. (200), Decomposing the Price-Earnings Ratio, Journal of Asset Management, 6 (3), pp Campbell J.Y. and Shiller, R. R. (1988), The Dividend- Price Ratio and Expectations of Future Dividends and Discount Factors, Review of Financial Studies, 1 (3), pp Fairfield P. M. (1994), P/E, P/B and the Present Value of Future Dividends, Financial Analysts 14 Basu S. (1983), The Relationship between Earnings Yield, Market Value, and for NYSE Common Stocks: Further Evidence, Journal of Financial Ecomics, 12 (4), pp Banz and Rolf W. (1981), The Relationship between and Market Value Stocks. Journal of Financial Ecomics, 9 (1), pp Fama E. and French K. (1992), The Cross-Section of Expected Stock s, Journal of Finance, 47 (3), pp Fama E. and French K. (1988), Dividends Yields and Expected Stock s, Journal of Financial Ecomics, 22 (2), pp Basu S. (197), The Information Content of Price-Earnings Ratios, Financial Management, 4 (2), pp

3 3.0 PROBLEM STATEMENT The need to observe short term (10 month) return of S&P 00 constituents where the independent variables include PE, PEG, PS, PB, 0 and 200 day moving average, 2 week high and low and finally Target price. 4.0 OBJECTIVES 1. To collect information on independent and dependent variables for the 00 constituents of the S&P00 as on October 2014 and equity price information for corresponding constituents in August To perform regression analysis on the selected independent variables and the dependent variable for the 10 month time period. 3. To observe and report the results of the regression. 4. To conclude on findings regarding the relationship if any between dependent and independent variables..0 METHODOLOGY The stock price information is downloaded from yahoo finance portal for the 00 constituents of the S&P 00 in the month of October The independent variables obtained for each stock include Price to earnings ratio, Price to Sales Ratio, Price to Book value Ratio, Price to earnings growth ratio, 0 day moving average, 200 day moving average, 2 week high value, 2 week low value, 1 year target price of stock. The dependent variables downloaded are the stock price as on October 2014, dividend paid per share and the final stock price as on August 201. The formula for return on each stock is as follows: Ri = (Pt+1 + Dt - Pt)/Pt where Pt refers to the time period of October 2014, Pt+1 refers to the time period of August 2014 and finally the Dt refers to the dividend paid in the time frame of the 10 months One regression is run for each of the independent variables PE, PS, PEG, PB, 200DMVA, 0DMVA, 2WH, 2WL, TGTP and the R-squared as well as the p-values of the x-coefficient is observed for each regression. A low R-squared indicates that the variable in question is t a good predictor of short-term equity returns. A high R-squared (.90 or higher) indicates that the variable should be put to further tests using random portfolios and observing the value of the return obtained from these random portfolios.. Abbreviation PE PER PB PBR PS PSR PEG PEGR Full form Price to Earnings Price to Earnings Ratio Price to Book Price to Book Ratio Price to Sales Price to Sales Ratio Price to Earnings Growth Price to Earnings Growth Ratio S&P TGTP 200DMVA 0DMVA 2WH 2WL Standard and Poor s Target Price 200 day moving average 0 Day moving average 2 week high 2 week low 6.0 RESULTS AND DISCUSSIONS Refer Table 1 for the results of each regression, the corresponding R-squared and the p-value for each variable i) PE ratio The assumption that low PE ratio stocks give higher returns in the long term is justified by prior research. This analysis is for testing the relationship between short term return and various independent variables. The regression is run for the number of stocks for which information is obtainable in both time periods August 201 as well as October 201. Results indicate that the relationship between PE ratio and the return on a given stock is weak. The R-squared for the regression is and the t-statistic is which has a p-value (significant at the.99 level). We can therefore conclude that the low PE stocks are in way creating a higher return and that the relationship between the PE ratio and stock price change in the short term is nexistent. ii) PS Ratio A Regression between PS ratio and returns indicates that the relationship between PS ratio and stock returns is weak (the R-squared is.01776) and the p-value of the coefficient is indicating that the coefficient is significant at the.99 level. We can therefore conclude that the relationship between PS ratio and the stock price change in the short term is n-existent. iii) PEG Ratio A Regression between PEG ratio and returns indicates that the relationship between PEG ratio and stock returns is weak (the R-squared is.00647) and the p- value of the coefficient is indicating that the coefficient is significant at the.9 level. We can therefore conclude that the relationship between PEG ratio and the stock price change in the short term is nexistent. iv) PB Ratio Regression between PB ratio and returns indicates that the relationship between PB ratio and stock returns is weak (the R-squared is.0012) and the p-value of the coefficient is.2060 indicating that the coefficient is t significant at any level. We can therefore conclude that the relationship between PB ratio and the stock price change in the short term is n-existent. v) 200DMVA A Regression between the difference of 200 day moving average and last trade price (200DMVA) and 20

4 returns indicates that the relationship between these two variables is weak (the R-squared is.08) and the p-value of the coefficient is close to zero indicating that the coefficient is significant at any level and that there is a negative relationship between the 200DMVA and last trade price and the change in stock price. Thus, stocks with a last trade price lower than the 200 day moving average have a higher chance of dropping in price while the stocks which have a last trade price higher than the 200 Day moving average have a lower chance of dropping in price. The variable cant be used as a predictor because the overall fit of the regression is low. vi) 0DMVA A Regression between the difference of 0 day moving average and last trade price (0DMVA) and returns indicates that the relationship between these two variables is weak (the R-squared is.1082) and the p- value of the coefficient is close to zero indicating that the coefficient is significant at any level and that there is a negative relationship between the 0DMVA and last trade price and the change in stock price. Thus, stocks with a last trade price lower than the 0 day moving average have a higher chance of dropping in price while the stocks which have a last trade price higher than the 0 Day moving average have a lower change of dropping in price. The variable cant be used as a predictor because the overall fit of the regression is low vii) 2WH A Regression between the difference of 2 week high and last trade price (2WH) and returns indicates that the relationship between these two variables is weak (the R-squared is.1306) and the p-value of the coefficient is close to zero indicating that the coefficient is significant at any level and that there is a negative relationship between the 2WH and last trade price and the change in stock price. Thus, stocks with a last trade price lower than the 2 week high have a higher chance of increasing in price while the stocks which have a last trade price higher than the 2 week high have a lower change of increasing in price. The variable cant be used as a predictor because the overall fit of the regression is low viii) 2WL A Regression between the difference of last trade price and 2 week low (2WL) and returns indicates that the relationship between these two variables is weak (the R- squared is.01489) and the p-value of the coefficient is.0004 indicating that the coefficient is significant at any level and that there is a positive relationship between the 2WL and last trade price and the change in stock price. Thus, stocks with a last trade price lower than the 2 week high have a higher chance of increasing in price while the stocks which have a last trade price higher than the 2 week high have a lower change of increasing in price. The variable cant be used as a predictor because the overall fit of the regression is low. ix) TGTP A Regression between the yahoo finance 1 year target price and returns indicates that the relationship between these two variables is strong (the R-squared is.8972) and the p-value of the coefficient is zero indicating that the coefficient is significant at any level and that there is a positive relationship between the Target price set 10 months earlier (October 2014) and short term stock price 10 months later (August 201). The high R- squared makes it tempting to invest in shares where the target price of the stock is more than the last trade price as on October Then, how do random portfolios based on target price perform relative to the broad market? If the broad market is defined as an equal weighted portfolio of shares in the S&P00 then a comparison of the performance of the broad portfolio and random portfolios is drawn. (random portfolios are formed from the subset of the population where the target price exceeds the last trade price), the mean of the random portfolios performed better than the mean of the equal weighted portfolio of the broad market. Further, when the data was segregated such that only companies where the target price was exceeding the last trade price by more than 10 percent were selected in the random sample, the result showed that the sample mean was suggesting that decisions based on target price are certainly t able to predict superior returns and the target price on yahoo finance might be overly bullish, especially when the target price exceeds the last trade price by larger percentages. Are the sample means of the random samples significantly different from the population means (broad market)? The population has a mean of 3.6 and a standard deviation of 27 while the random sample ( constraint) has a sample mean of 3. and a standard deviation of.1. The random sample (with constraint of 10 percent or greater) has a sample mean of and standard deviation of CONCLUSIONS There is relationship between the Price to Earnings Ratio and the gain in stock price. Therefore low PE ratio shares are t expected to perform any better than the high PE ratio shares in the short run Similarly, the effect of PB, PEG, PS ratios are also expected to play a small or role in the prediction of equity prices in the short term. Investors are thus advised to t use these relative valuation ratios for portfolio selection in the short term. 0 day moving average and 200 day moving average are somewhat more effective in prediction of equity price however the investor cant rely on the moving averages as an indicator because the power of its prediction is low. Any portfolio constructed on the basis of these parameters would 21

5 yield an expected return better than that of the market return. The 2 week high and low parameters again yield low predictive power and stocks trading away from their high or low do t necessarily make good investments. 1 Year Target price promises to be a good predictor of future equity price in the initial observation. When further analysis is conducted on the target price by use of random portfolios, it is seen that random portfolios based on target price perform between than portfolios from the broad market. When random stocks from the population are selected from a subset of the population where the target price exceeds the last trade price by over 10 percent, then the random portfolios perform much worse than the broad market. In sum, it is t a good strategy for the investor to use any of the variables included in this research to predict short term gains in equity prices. Table 1 Results from regression with various parameters Adj Parame R 2 ter PER PSR PEGR PBR DMV A 2 200DM VA 2 2WKH WKL TGTP x-coeff p- value x-coeff Signifi cant at 0.0 level? Yes Yes Yes No Yes Yes Yes Yes Yes Table 2 Random portfolio (of 30 stocks) performance with constraint on target price 2 samples Broad market return: 3.6 Standard Deviation: 27, Mean St dev Table 3 Random portfolio (of 30 stocks) performance with constraint on target price 2 samples Broad market return: 3.6 Standard Deviation: Mean St dev REFERENCES 1. Abidin, Sazali and Hewa Wellalage, Nirosha and Yu, Youjie and Zhao, Zhixia, Do Positive P/E Firms and Negative P/E Firms Differ in Characteristics and Performance? (January 1, 201). Available at SSRN: or 2. Anderson K. and Brooks C. (200), Decomposing the Price-Earnings Ratio, Journal of Asset Management, 6 (3), pp Banz and Rolf W. (1981), The Relationship between and Market Value Stocks. Journal of Financial Ecomics, 9 (1), pp Basu S. (197), The Information Content of Price-Earnings Ratios, Financial Management, 4 (2), pp Basu S. (1977), Investment Performance of Common Stocks in Relation to Their Price- Earnings Ratios: A Test of the Efficient Market Hypothesis, The Journal of Finance, 32 (3), pp Basu S. (1983), The Relationship Between Earnings Yield, Market Value, and for NYSE Common Stocks: Further Evidence, Journal of Financial Ecomics, 12 (4), pp Basu, Anup K. and O'Shea, Luke, The Predictive Ability of P/E Ratio: Evidence from Australia and New Zealand (January 8, 22

6 2014) Financial Markets & Corporate Governance Conference. Available at SSRN: or 8. Bodhanwala, Ruzbeh J, Testing the Efficiency of Price-Earnings Ratio in Constructing (June 10, 201). The IUP Journal of Applied Finance, Vol. 20, No. 3, July 2014, pp Available at SSRN: 9. Campbell J.Y. and Shiller, R. R. (1988), The Dividend-Price Ratio and Expectations of Future Dividends and Discount Factors, Review of Financial Studies, 1 (3), pp Chua, A., DeLisle, R. J., Feng, S.-S. and Lee, B. S. (201), Price-to-Earnings Ratios and Option Prices. J. Fut. Mark., 3: doi: /fut Fama E. and French K. (1988), Dividends Yields and Expected Stock s, Journal of Financial Ecomics, 22 (2), pp Fama E. and French K. (1992), The Cross- Section of Expected Stock s, Journal of Finance, 47 (3), pp Gurrib, Ikhlaas, The Moving Average Crossover Strategy: Does It Work for the S&P00 Market Index? (November 30, 2014). Available at SSRN: or Hilliard Jitka and Zhang Haoran, 201, Size and price-to-book effects: Evidence from the Chinese stock markets, Pacific-Basin Finance Journal Volume 32, April 201, Pages Houmes, Robert and Chira, Inga, The Effect of Ownership Structure on the Price Earnings Ratio-s Amaly (November 23, 2014). International Review of Financial Analysis, Forthcoming. Available at SSRN: Kerl, Alexander Gabriel, Target Price Accuracy (April 1, 2011). BuR Business Research Journal, Vol. 1, No. 1, pp , March Available at SSRN: Mayur, Manas, Relationship between Price- Earnings Ratios and Stock Value in an Emerging Market (December 2, 2014). Available at SSRN: or Zhang, Zhaohui (201) Financial Ratios and Stock s on China s Growth Enterprise Market, International Journal of Finance, Vol 6, No Fairfield P. M. (1994), P/E, P/B and the Present Value of Future Dividends, Financial Analysts 23