Analysis of Financial Modelling - Assignment Example

PART ONE Figure1: Standard & Poor’s (S&P) SMALL CAP 600 Index Figure above shows that the portfolio is highly volatile and the returns are almost normally distributed. However, the stock is best suited for a risk taker. Figure 2: New York Stock Exchange (NYSE) World Leaders Index Figure 2 above shows the frequency distributed of the second stock, which is less volatile and more suitable for risk averse investors. The standard deviation can be used to estimate the risk of a stock portfolio. In essence, the standard deviation will be used in this model to measure volatility. In this sense, it will be considered that the stock that differs more from the stock’s average return is a more volatile stock. Use of standard deviation to measure volatility is considered effective because it incorporates all the values in the calculations unlike other methods such as the range, which considers only two extreme figures. From figure 3 below, it is clear that, as the volatility for Standard & Poor’s (S&P) SMALL CAP 600 Index increases, the average rate of return declines rapidly up to a point where, if the volatility level continues to increase, the average returns start to increase rapidly (Lachance, 2003). In effect, when this portfolio is less volatile, its average return tends to decline, but when the rate of volatility is very high, the average returns tend to increase. In situations of high volatility, the risk of a stock tends to be high while on the other hand, when a stock is less volatile, its return is almost assured and hence less risky. The characteristic exhibited by this portfolio is that an investor should expect to make more returns when the stock is highly volatile. As such this stock is suitable for those investors who are comfortable with highly volatile stocks, who invest with the expectation of getting high returns. Considering that I am a risk averse investor, and would prefer stocks with more stable incomes even if it means lower returns - I would not go for this stock (Merton, 1969). Figure3: Standard & Poor’s (S&P) SMALL CAP 600 Index (Annual average vs. standard dev.) From figure 4 below, the pattern of the graph has an implication that higher returns are expected in situations of less volatility. This is precisely the type of portfolio that suits my risk profile because I can invest in conditions of low volatility and still expect some returns albeit low. This also shows that this index performed better, as it is less volatile and hence almost guaranteeing investors some returns. The chance of getting returns from the S&P portfolio is very uncertain and hence considered as having performed poorly on such grounds (Milevsky, 1998). Figure4: New York Stock Exchange (NYSE) World Leaders Index (Annual average vs. standard dev.) Interpretation of the risk and return of the equally-weighted portfolio compared to those of the individual assets. If I invested in equal amount in the above two portfolios, I could have formed a diversified investment, which could have balanced my risk with return. The S & P portfolio is more risky, but attracts higher returns while the New York portfolio is less risky, but attracts less return. One of the most important steps for creating a successful portfolio is efficiently divided assets within scores of different investment types. The performance of these investments depends on the prevailing conditions of the economy. Therefore, a good balance is required to maintain the portfolio strong in different economic situations. Accordingly, the allocation of assets becomes the most important way of diversification. More so, classes of assets carry different amounts of risks. It is important that the investments are spread over a variety of stocks with different risk profiles like the ones analyzed in this paper. This is because each asset class performs differently from the others as a result of its unique balance of risks and rewards. Diversification calls for the need to know the security an investor needs. Therefore, there is a need to spread each asset investment over different types of securities (Little 2012). Rebalancing has proved to contribute to lowering the overall risk in a portfolio. This is only if periodic rebalancing is adhered to so that the portfolio’s asset allocation does not drift out of balance due to changing market conditions. It is, therefore, imperative to shun investments that are not adding quality to life. A prudent investment decision must must always take into consideration important diversification in the area of operation, asset allocation as well as an ideal rebalancing strategy. This ensures an easy to follow investment plan, which is geared towards attaining the investor’s need. The minimization of risks and the maximization of the potential returns is, therefore, imperative when investing (Ferri 2009; Lachance 2003). PART TWO This analysis involves Dow Jones Composite Average which represents the market average on one hand, and American Electric Power Co., Inc. (AEP) and Caterpillar Inc. (CAT) and the individual member portfolios on the other hand. The analysis will involve application of CAPM model and regression analysis to find out the stock’s systematic risk and theoretical return. Systematic risk is the risk that cannot be removed by investing in different companies as a way of diversification. This risk is represented by beta in a CAPM model. The CAPM model assumes that the portfolio is fully diversified and hence the objective of the investors in stocks is systematic risk only. The following is the CAPM formula used to calculate the theoretical return and systematic risk in this paper: E(ri) = Rf + βi(E(rm) - Rf) Rf = risk-free rate of return E(ri) = return required on financial asset i E (rm) = average return on the capital market βi = beta value of financial asset I (which is also the The formula is in the form of y= a+ bx, whereby: Βi = x Rf = Y-intercept E (ri) = SML (plotted on the straight line) (E (rm) = we substitute with 12.82364 which is the weighted average excess returns for the independent variable. The following is the table where these figures are computed. Y Average (y) DJA AEP CAT AEP(EXESS) CAT(EXESS) Average (independent variable) 2001 29.77 43.27 24.66 33.965 13.5 -5.11 4.195 2002 31.66 26.55 24.61 25.58 -5.11 -7.05 -6.08 2003 29.77 28.41 41.33 34.87 -1.36 11.56 5.1 2004 24.43 34.34 46.69 40.515 9.91 22.26 16.085 2005 29.98 37.67 60.45 49.06 7.69 30.47 19.08 2006 33.05 42.04 60.22 51.13 8.99 27.17 18.08 2007 36.99 46.29 68.53 57.41 9.3 31.54 20.42 2008 41.07 34 43.6 38.8 -7.07 2.53 -2.27 2009 42.3 36 60.34 48.17 -6.3 18.04 5.87 2010 35.66 35.62 93.73 64.675 -0.04 58.07 29.015 2011 35.66 40.79 93.66 67.225 5.13 58 31.565 3.149090909 22.498182 12.8236364 The following is the output from SPSS, which is used to run a regression analysis. This will be used to substitute for the above constituent of the formula. Coefficientsa Model Unstandardized Coefficients Standardized Coefficients t Sig. B Std. Error Beta 1 (Constant) 33.935 2.497 13.593 .000 Excess returns .979 .144 .915 6.819 .000 a. Dependent Variable: Ave. returns Therefore: y = 12.82(0.979) + 0.339 Y = 0.979(12.82364) + 0.339 = 12.88% Therefore, an investor will expect to get a return of 12.88%. The beta for this portfolio is quite high and that is why the expected return is also quite high. However, it is important to note that the stock has a beta, which is close to one, meaning that its volatility is very close to that of the market or the benchmark (Kapur & Orszag, 1999). This model will be very useful as it has shown us the relationship between risk and return, and also distinduished between non-diversifiable risk and diversifianble risk. However, the model is not devoid of limitations. For example, it is not very realistic to assume that investors consider only the risk while making their investment decisions. There are a multiple of other factors that are essential, which this model has not considered. Firstly, it is hard to calculate the covariance of returns between assets. Secondly, mathematical method makes it difficult in practice. Third, portfolio model is assumed to be stable. The model was developed from the portfolio choice model introduced by French (2004), which states that an investor selects a portfolio at time t-1, and gets his return at time t. CAPM was constructed on an assumption that investors are risk averse, and the mean and variance (risk and return relationship) of their one-period investment is the key points they give attention to. References Ferri, T 2009, The ETF book: All you need about Exchange trade Funds, Wiley, NewYork. French, R 2004, The Capital Asset Pricing Model: Theory and Evidence. New York: Sage. Kapur, S & Orszag, M 1999, A portfolio approach to investment and annuitization during retirement, Birkbeck College press, London. Lachance, M 2003, Optimal investment behavior as retirement looms, Wharton School, University of Pensylvania, Philadelphia. Little, K 2012, Major Types of Risks for Stock Investors, viewed 30 May 2012, Merton, R 1969, ‘Lifetime portfolio selection under uncertainty: The continuous time case’, Review of Economics and Statistics, vol. 51 no.3, pp.247-257, Milevsky, M 1998, Optimal asset allocation towards the end of the life cycle: to annuitize or not to annuitize?, The Journal of Risk and Insurance, vol 65 no.3, pp.401-426. Milevsky, M 2001, ‘Optimal annuitization policies: analysis of the options’, North American Actuarial Journal, vol. 5 no.1, pp.57-69. Read More