Friday, December 6, 2019

Analysis of Model Selection and Model Testing

Question: Discuss about the Analysis of Model Selection and Model Testing. Answer: Introduction: In the present case Mingalabar Inc is considering setting up a manufacturing unit in Myanmar. Capital budgeting is employed to analyze the risk and returns and thereby the financial feasibility of the project. In this respect of this project the biggest risk is that the company may not earn the returns as estimated and the project may fail (Bierman and Smidt, 2014). The risk of not earning the estimated returns may be due to the following factors: Inflation as estimated by the company in analyzing the project may increase in future resulting in reduction in the value of investments. The interest rates may rise in the future making the borrowings more costly and thus, reducing the profits earned by the company. There may be rise in the prices of the materials and labor over and above the anticipations of the company. Further, the company may not achieve the estimated demand or there be sudden hike in the competition resulting in market loss. The political conditions in Myanmar may also change in future resulting affecting the company adversely. The arbitrage pricing model (APM) provides the basis for computation of the theoretical return that is to be used in estimating the theoretical prices of the securities. The model postulates the mechanism to pave the way to determine the percentage return that an investor would expect by investing in a particular security or asset (Bhatti, Shanfari, and Hossain, 2006). In the determination of the expected return, the consideration of the risk attached with the investment is of paramount importance. However, different models provide different ways to incorporate the element of risk in determination of the expected return. As per the arbitrage pricing theory, the risk is not related to a single factor; rather it correlates with multiple factors. Those multiple factors may not necessarily be specific to the security being valued directly, but certainly affect the return on security in some or other way. Thus, apart from beta, consideration of the multiple factors such as gross domestic product, inflation, and interest rates was necessary, which was made possible by the APM (Rasiah and Kim, 2011). As discussed above, the arbitrage pricing model works on multifactor basis, therefore, the theoretical/expected return is computed by applying these multiple factors (Rasiah and Kim, 2011). The theoretical return in respect of a security under APM is determined by applying the equation given below: E(rj) = rf+bj1RP1+bj2RP2+bj3RP3+bj4RP4+..+bjnRPn Where, E(rj) = Theoretical/ expected return on security rf = Risk free rate bj = Sensitivity index RP = Risk premium of multiple factors Thus, it could be observed from the equation given above that the risk free rate is increased by the proportionate risk premium of multiple factors. Generally, the risk factors considered for computation of the return range from three to four involving GDP, inflation, and interest rates (Focardi and Fabozzi, 2004). The capital asset pricing model was in use before the arbitrage pricing model coming into use for computation of the theoretical return and security valuation. The capital asset pricing model was considered to be quite effective in incorporating the risk element in determination of the theoretical return (Wang and Xia, 2012). Though, this model was effective, but it was based on the single factor that is beta. Beta represents the sensitivity of the return on a particular security relative to the market as a whole. However, the risk of a security does not necessarily depend entirely on beta. There are other macroeconomic as well as security specific factors that affect the risk of the security. Therefore, the incorporation of the risk in computation of the theoretical return was considered by the Economists imperfect in the CAPM model. In order to overcome this imperfection in the CAPM model, the arbitrage pricing model was innovated with the consideration of the multiple factors in d etermination of the risk (Stowe, 2007). Apart from application of the multiple factors, the APM model is completely based on the premises set out in the CAPM model. Thus, the arbitrage pricing model is considered to be an extension of the CAPM model (Stowe, 2007). There are various advantages of the APM as claimed by the proponents of the APT theory. The biggest advantage of this model is that the investor is compensated for all the risks because of consideration of the multiple factors. Further, the proponents claim that the analysts are not required to make many more assumptions while applying APM because this model already takes into consideration a wide range of factors. The APM model provides a fair determination of the theoretical return, which results in fair valuation of the security. Thus, the probability that the decisions taken by the investors would be right is increased when APM is applied in decision making (Stowe, 2007). Though, the innovation of the arbitrage pricing model was appreciated by the world, but this model has certain disadvantages. The most crucial among them is the difficulty in applying this model in practical situations. Since, the model considers multiple factors, thus, the analytical exercise is also extended to a greater extent. The determination of the proportion of a particular risk factor in computing the return in APM may be subjective in certain situations (Stowe, 2007). Valuation of a Security Factors which affect the return of the security Sensitivity Index Risk premium (%) Sensitivity * Risk premium GNP 0.80 2.00% 1.60% Inflation 0.80 1.50% 1.20% Interest rate 1.30 2.00% 2.60% Market Index 1.20 5.00% 6.00% Industrial production 1.00 1.00% 1.00% 12.40% Add: Risk free rate 5.00% Return as per APM 17.40% Valuation of portfolio Input data Actual portfolio return 10% Expected return on portfolio 15% Risk free rate 4% Beta 1.15 Sensitivity to GDP 1.20 Proportion of Beta in total systematic risk of portfolio 0.60 Proportion of Sensitivity to GDP in total systematic risk of portfolio 0.40 Output data: Theoretical Return on Portfolio 1 Risk premium 5.00% 2 Beta*proportion in systematic risk 0.69 3 Sensitivity to GDP*proportion in systematic risk 0.48 4 Return (1*2*3) 1.66% 5 Risk free rate 4.00% 6 Theoretical Return on Portfolio (4+5) 5.66% References Bhatti, M.I., Shanfari, H.A., and Hossain, M.Z. 2006. Econometric Analysis of Model Selection and Model Testing. Ashgate Publishing, Ltd. Bierman, H. and Smidt, S. 2014. Advanced Capital Budgeting: Refinements in the Economic Analysis of Investment Projects. Routledge. Focardi, S.M. and Fabozzi, F.J. 2004. The Mathematics of Financial Modeling and Investment Management. John Wiley Sons. Rasiah, D. and Kim, P. 2011. The effectiveness of arbitrage pricing model in modern financial theory. International journal of economics, 2(3), pp. 125-135. Stowe, J.D. 2007. Equity Asset Valuation. John Wiley Sons. Wang, S. and Xia, Y. 2012. Portfolio Selection and Asset Pricing. Springer Science Business Media.

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