Capital Asset Pricing Model with Asset Growth Muhammad Irfan
[email protected] Abstract Recent studies suggest that the conditional CAPM might hold, period-by-period, and that timevarying betas can explain the failures of the simple, unconditional CAPM. We argue, that significant betas are affecting the returns of firm. Capital Assets Pricing Model (CAPM) is the widely tested, accepted and rejected model of asset pricing. This study tested the CAPM with addition of asset growth on a specific Industry of Pakistan selected from KSE-100 index. After testing the CAPM with addition of asset growth this study suggested that CAPM is may be useful to forecast the required return but many other factors are there which are important to include and study. When this study assume all other factors are constant than we calculate the required return but these results are not 100% accurate may be some important things are miss here. This study suggested that many other factors have impact on future returns. Key word: Beta, Required Return, Actual Return, Risk Free Rate, Market Return, Capital Asset Pricing Model, Asset Growth. Etc
Introduction: The capital asset pricing model (CAPM) of William Sharpe (1964) and John Lintner (1965) marks the birth of asset pricing theory (in resulting a Nobel Prize for Sharpe in 1990). Four decades later, the CAPM is until now as far/much as possible applied in applications, in such a way determining the cost of capital for firms and assessing the performance of managed portfolios. The desirability of the CAPM is that it approaches well-built and congenitally pleasing predictions about how to quantify risk and the alliance between expected return and risk. CAPM is a model that illustrates the alliance between risk and expected return and which is applied in the pricing of risky securities. Previous researcher use CAPM for calculate the expected returns of stock and also for firms, many of them add more factors to test the model like Eugene F. Fama. Kenneth R. French. (2005) they use three factor model to test the CAPM, after reading the previous researches this study found that no one add asset growth in CAPM to test it on the stocks of Islamabad stock Exchange (ISE). Main objective of this study is to test the simple CAPM on ISE which is not done by a researcher in past and then test it with asset growth as a new factor include in CAPM. All studies done in past on NYSE, AMEX and NASDAQ, even a researcher cannot test to on ISE to check it is applicable in all over the world or not.
Method: Old researcher used quantitative method to check the significance of model and the also retrieved the historical data from the web sites of different stock exchanges. After collection of data they did some steps to get the required things and run some test on Excel and STATA, when they get the required things after that they put them in to the equation of model and check the significance of study and model also. 25 research studies on capital asset pricing model use to retrieve the data about the intro and changes done in past and also find out what are the future directions suggested by old researchers from some data bases (Wiley-Blackwell, J-store) and from some Journals (Journal of Finance and Accounting, Journal of business, journal of economics) and many more. When this study start to identify the changes and future directions suggested by other researcher at start time we have nothing else CAPM model proposed by (William Sharpe, 1964. and John Lintner, 1965). Now this study have enough information about all the things done in past and what should be need to done in future by others.
Chronological Literature Review: Fischer, Michael and Myron (1972, 1) found that the expected excess return on an asset is not strictly proportional to its beta. Stewart and Stuart (1977, 12) suggested that comparatively simple and extensive assessment formulas can be spread out the CAPM and the real determinants of beta are more complicated than is general suspected. George (1980) found that the aggregate property ensure the set of prices, which support the aggregate economy, also support the original economy. Rene (1981) found that the CAPM model does not take money into account clearly. Robert and
Eric (1984) suggested that the market portfolio contains a jump component although its immensity is small. The presence of weekends and holidays measured over larger intervals in time tends in to cover up the small jump component. Michael and Wayne (1984) suggested that the returns are consistent with a single, time-varying risk premium. Sanford, Angelo and Robert (1985) suggested that the consumption based asset pricing model predicts the excess yields and determined in a fairly simple way by the markets’ degree of relative risk aversion and by the pattern of covariance between per capita consumption growth and asset returns. Yakov and Haim (1986) found that the higher yields required on higher-spread stocks give firms an incentive to increase the liquidity of their securities, thus reducing their opportunity worth of capital. Resultantly, liquidity-growing financial policies may increase the value of the firm. Douglast, Michael and Robert (1989) suggested that the positive autocorrelation between consumption-oriented capital asset pricing model and market-oriented capital asset pricing model. Robert, Victor and Michael (1989) found that the factor-arch model as a parsimonious structure for the conditional covariance matrix of asset excess returns. Darrell and Wiliam (1989) suggested that the consumption-based capital asset pricing model extends, with limitations, to the case of multiple commodities. Ravi and Zhenyu (1996) found that the empirical support for conditional CAPM specification is rather string. When betas and expected returns are acknowledged to vary over time by assuming that the CAPM holds period by period, the size effect and the statistical rejections of the model specifications become much weaker. John (1996) found that the simple investment model performs surprisingly well. The investment return factors significantly value assets, the simple investment model is not rejected, and it is able to explain a wide spread in expected returns. Eugene and Kenneth (1996) rejects the proposed the central CAPM hypothesis that beta suffices to explain expected return. William and Cars (1998) suggested that asset pricing model with heterogeneous beliefs is very simple and stylized. James and Eugene (1999) suggested that three factor model is just and model and it is an incomplete description of expected returns. Jonathan and Stefan (2003) found that the conditional CAPM cannot explain asset pricing anomalies like momentum. Tsung-chi and shien-ju (2005) found that LTS betas have more variations than OLS betas, and the former as more successful in capturing the time-series variations of excess returns. Eugene and Kenneth (2005) found that there is no value premium among the largest stocks seems to be special to the U.S and the book-to-market ratio as the value growth indicator. Andrew and Joseph (2005) have propose and directly estimate a conditional CAPM with time-varying conditional betas, market risk premia, and stochastic systematic volatility. Ralista (2006) Investigated that the Fama, French factors HML and SML are related to stocks in state variables that describe time variation in investment opportunity. Eugene and Kenneth (2008) found that the anomaly variables they consider seems to have unique information about future returns. Fraydoon and Zahra (2011) found that there is no inverse and meaningful relation between interest rate and company’s sales. And also found that there is meaningful difference between measure of beta calculating by DEL and the beta computing by CAPM, D-CAPm and Adj-CAPM. Eugene and Kenneth (2012) investigate that there are common patterns in average returns in developed markets. Eugene and Kenneth (2014) suggested that the version of CAPM developed by sharpe (1964) and Lintner (1965) has never been an empirical success. In the early empirical work, the Black (1972) version of the model has some success.
Critical Assessment: Michael and Wayne (1984) suggested that methodology avoids risk which have a big effect on expected returns over time to estimate ratios of betas. They use the data on common stocks of the DOW jones 30. This study only co Yakov and Haim (1986) suggested that further research could also be carried out on the interplay between liquidity and risk, and on the relation between assets returns and a more comprehensive set of liquidity characteristics. They used that data in this paper from New York Stock exchange from 1960 to 1979. Douglast, Michael and Robert (1989) suggested that the estimated risk measures for both CAPM and conditional CAPM are highly correlated, this similarity in the performance by the CAPM and conditional CAPM is predictable. Data used in this paper are 1926 to 1982 whole data and 1926 to 1939 sub period. Robert and Michael (1989) proposed that the CAPM model can be useful in forecasting the yield curve, and also can be useful in evaluating the firm’s derivative assets and so on among the econometric problems which they left in this paper some statistical methods used in this paper to collect data and check the significance level of the model. Tsung-Chi, Hung-Neng and Chien-Ju (2005) they suggested that first of all, include all the other industries in the whole market this is compulsory. Secondly, more test should be required for considering a wide range of explanatory variables and including macroeconomic variable which are not determined by others and this study conducts only on LTS and OLS data. Ralista (2006) said that CAPM is not the best model to capture assets’ covariance with time-varying investment opportunities. Analysis run in this paper on the data from 1963 to 2005 of New York stock exchange. Eugene and Kenneth (2008) said that future cash flows predicting variables also predict the future returns it does not happen, but it can be useful in check the variation and calculate the risk involve in mispricing of the stocks. They take data from New York stock exchange for the period of 1963 to 2005. Old studies show that there is more need to prove CAPM model on different stocks and as well as on different markets to check the significance level of model and to predict the future returns and take managerial decision for investment in portfolios or single stock. Many researcher use different techniques to apply this model at different places just like Eugene and Kenneth use this model with a new equation of multifactor, this model called Fama and French multifactor model. This study use simple CAPM model to indicate the future returns and also check the significance level of model on Islamabad stock exchange, after that this study use same stocks with addition of another factor in simple model equation that is asset growth, after addition of asset growth this study get a new equation that could be apply for forecasting the results and at the end this study compares the both results get from simple and asset growth CAPM model and give some suggestion on it. It could be useful or not. 1. Ri = Rfr + β (Rm – Rfr) 2. Ri = Rfr + β1 (Rm – Rfr) + β2 (AG) These two equation are use in this paper to indicate the results and make some suggestion about CAPM model either it could be useful or not. These equation are useful after collecting the data and calculating the required factors by using statistical tools and techniques.
Conclusion: The study examine that the CAPM model is not completed and there is a need of addition other factors which are important and affecting the returns of firm, like Size of an firm and value of an firm etc. The application of the CAPM with addition of asset growth on whole Industries of Pakistan or on a specific industry of Pakistan to form an opinion about its validity and reliable application in local institutional framework. For the analysis of Pakistan’s specific Industry is selected from KSE-100 index for a specific time period. After calculation of variables form and equation to calculate the future returns, after applying both equations this study compares the results that has been calculated and get from the CAPM equation. This equation is not perfect to forecast the future on the basis of CAPM simple model because there are many other variables which affect the required returns and have positive impact on it this claims by other researchers in past.
Bibliography: 1. Amihud, Y., & Mendelson, H. (1986). Asset pricing and the bid-ask spread.Journal of financial Economics, 17(2), 223-249. 2. Breeden, D. T., Gibbons, M. R., & Litzenberger, R. H. (1989). Empirical tests of the consumption‐oriented CAPM. The Journal of Finance, 44(2), 231-262. 3. Brock, W. A., & Hommes, C. H. (1998). Heterogeneous beliefs and routes to chaos in a simple asset pricing model. Journal of Economic dynamics and Control, 22(8), 1235-1274. 4. Cheng, T. C., Lai, H. N., & Lu, C. J. (2005). Industrial effects and the CAPM: from the views of robustness and longitudinal data analysis. Journal of Data Science, 3(4), 381-401. 5. Cochrane, J. H. (1996). A cross-sectional test of a production-based asset pricing model (No. w4025). National Bureau of Economic Research. 6. Constantinides, G. M. (1980). Admissible uncertainty in the intertemporal asset pricing model. Journal of Financial Economics, 8(1), 71-86. 7. Duffie, D., & Zame, W. (1989). The consumption-based capital asset pricing model. Econometrica: Journal of the Econometric Society, 1279-1297. 8. Engle, R. F., Ng, V. K., & Rothschild, M. (1990). Asset pricing with a factor-ARCH covariance structure: Empirical estimates for treasury bills. Journal of Econometrics, 45(1), 213-237. 9. Fama, E. F., & French, K. R. (1996). The CAPM is wanted, dead or alive. The Journal of Finance, 51(5), 1947-1958. 10. Fama, E. F., & French, K. R. (2004). The capital asset pricing model: Theory and evidence. Journal of Economic Perspectives, 18, 25-46. 11. Fama, E. F., & French, K. R. (2006). The value premium and the CAPM. The Journal of Finance, 61(5), 2163-2185.
12. Fama, E. F., & French, K. R. (2008). Dissecting anomalies. The Journal of Finance, 63(4), 1653-1678. 13. Fama, E. F., & French, K. R. (2012). Size, value, and momentum in international stock returns. Journal of financial economics, 105(3), 457-472. 14. Gibbons, M. R., & Ferson, W. (1985). Testing asset pricing models with changing expectations and an unobservable market portfolio. Journal of Financial Economics, 14(2), 217-236. 15. Grossman, S. J., Melino, A., & Shiller, R. J. (1987). Estimating the continuoustime consumption-based asset-pricing model. Journal of Business & Economic Statistics, 5(3), 315-327. 16. Jagannathan, R., & Wang, Z. (1996). The conditional CAPM and the crosssection of expected returns. journal of finance, 3-53. 17. Jarrow, R. A., & Rosenfeld, E. R. (1984). Jump risks and the intertemporal capital asset pricing model. Journal of Business, 337-351. 18. Jensen, M. C., Black, F., & Scholes, M. S. (1972). The capital asset pricing model: Some empirical tests. 19. Lewellen, J., & Nagel, S. (2003). The conditional CAPM does not explain assetpricing anomalies. Journal of financial economics, 82(2), 289-314. 20. Myers, S. C., & Turnbull, S. M. (1977). Capital budgeting and the capital asset pricing model: Good news and bad news. The Journal of Finance, 32(2), 321-333. 21. Petkova, R. (2006). Do the Fama–French factors proxy for innovations in predictive variables?. The Journal of Finance, 61(2), 581-612. 22. Roodposhti, F. R., & Amirhosseini, Z. (2011). Revised capital assets pricing model: an improved model for forecasting risk and return. Journal of Finance and Accountancy, 5, 1-10. 23. Sharpe, W. F. (1964). Capital asset prices: A theory of market equilibrium under conditions of risk*. The journal of finance, 19(3), 425-442. 24. Stulz, R. (1981). A model of international asset pricing. Journal of Financial Economics, 9(4), 383-406. 25. Thackeray, R., Neiger, B. L., & Roe, K. M. (2005). Certified health education specialists' participation in professional associations: Implications for marketing and membership. Journal of Health Education, 36(6), 337-360.
