Stocks for Australian Agricultural Company - Report Example

Finance Your name: Institution name: Question 1: Question 1a 1. Australian Agricultural Company Ltd Jan, 2013-31st Dec 2013 Month Share Price (End of month) Share Price (Beginning of month) Monthly Return (M) Jan 1.22 1.17 4.27 % Feb 1.34 1.22 9.8% Mar 1.29 1.28 0.78% Apr 1.17 1.29 -9.3% May 1.12 1.17 -4.27% Jun 1.16 1.10 5.54% Jul 1.15 1.17 -1.71% Aug 1.11 1.16 -4.31% Sep 1.12 1.03 8.74% Oct 1.13 1.04 8.65% Nov 1.20 1.14 5.26% Dec 1.25 1.21 -0.83% Sum 22.62 Table 1: stocks for Australian Agricultural Company Ltd Formula (s) i. Monthly Return Monthly Return= (End of month share price/ Beginning of month share price)-1 x100% Monthly return for the month of January= (1.22/1.17)-1x100%= 4.27 % ii. Average Monthly Return () Average monthly return= sum of all the monthly returns/12 Average Monthly Return= 22.6/12= 1.885 iii. Variance Sum the squared differences. (0.0427-0.0189)^2=0.0057 (0.098-0.0189)^2=0.06257 (0.0078-0.0189)^2=0.00123 (0.093-0.0189)^2=0.0055 (0.042-0.0189)^2=0.0053 (0.054-0.0189)^2=0.00123 (0.0171-0.0189)^2=0.000003 (0.0431-0.0189)^2=0.00583 (0.0874-0.0189)^2=0.00457 (0.0865-0.0189)^2=0.00457 (0.0526-0.0189)^2=0.001136 (0.0087-0.0189)^2=0.00104 0.0915 = (0.0915/12-1)= 0.00832 iv. Standard Deviation sqrt (0.00832)= 0.076% 2. DuluxGroup Limited (ASX: DLX) Jan, 2013-31st Dec 2013 Month Share Price (End of month) Share Price (Beginning of month) Monthly Return (M) January 4.12 3.81 8.14 % February 4.12 4.19 -1.67% March 4.45 4.09 8.8% April 4.69 4.46 5.16% May 4.59 4.64 -1.078% June 4.21 4.51 -6.65% July 4.46 4.14 7.73% August 4.52 4.51 0.221% September 5.28 4.73 11.62% October 5.15 5.36 -3.92% November 5.49 5.15 6.602% December 5.36 5.48 -2.19% Sum 32.765% Table 2: stocks for DuluxGroup Limited i. Monthly Return Monthly Return= (End of month share price/ Beginning of month share price)-1 x100% Monthly return for the month of January= (4.12/3.81)-1x100%= 8.14 % ii. Average Monthly Return () Average monthly return= sum of all the monthly returns/12 Average Monthly Return= 32.765/12= 2.73 iii. Variance Sum the squared differences. (0.0814-0.0273)^2=0.0028 (0.167- 0.0273)^2=0.0195 (0.088-0.0273)^2=0.0037 (0.0516-0.0273)^2=0.00059 (0.01078-0.0273)^2=0.000273 (0.0665-0.0273)^2=0.00153 (0.0775-0.0273)^2=0.00252 (0.0221-0.0273)^2=0.000027 (0.1162-0.0273)^2=0.0079 (0.0392-0.027389)^2=0.000142 (0.06602-0.0273)^2=0.0014 (0.0219-0.0273)^2=0.00003 0.028072 = (0.028072/12-1) = 0.002552 iv. Standard Deviation sqrt (0.002552)= 5.05% 3. SKYCITY Entertainment Group Limited-Ord (ASX:SKC) (ASX:AAC) Jan, 2013-31st Dec 2013 Month Share Price (End of month) Share Price (Beginning of month) Monthly Return (M) January 3.17 3.04 4.276 February 3.42 3.17 7.886 March 3.52 3.40 3.53 April 3.70 3.46 6.94 May 3.57 3.70 -3.513 June 3.70 3.51 0.54 July 3.69 3.70 -0.27 August 3.39 3.71 -8.63 September 3.59 3.4 5.59 October 3.35 3.57 -6.16 November 3.33 3.41 -2.35 December 3.60 3.35 7.46 Sum 15.289 Table 3: SKYCITY Entertainment Group Limited i. Monthly Return Monthly Return= (End of month share price/ Beginning of month share price)-1 x100% Monthly return for the month of January= (3.17/3.04)-1x100%= 4.276% ii. Average Monthly Return () Average monthly return= sum of all the monthly returns/12 Average Monthly Return= 15.289/12= 1.274 iii. Variance Sum the squared differences. (0.04276-1.274)^2=1.516 (0.07886- 1.274)^2=1.43 (0.0353-1.274)^2=1.53 (0.0694-1.274)^2=1.45 (0.03513-1.274)^2=1.535 (0.0054-1.274)^2=1.61 (0.0027-1.274)^2=1.62 (0.0863-1.274)^2=1.41 (0.0559-1.274)^2=1.48 (0.0616-1.274)^2=1.47 (0.0235-1.274)^2=1.56 (0.746-1.274)^2=0.28 16.891 = (16.891/12-1) = 1.5355 iv. Standard Deviation sqrt (1.5355)= 123.91% Question 1b Although the expected return of stock is a good estimation that is available of future returns, the actual return is not likely to equal the expected return. For this simple reason, managers and investors would like to have an idea of how their estimate on stock might be. A stock investor will use two concepts: variance and its square root, the standard deviation to quantify their precision of their estimates. Australian Agricultural Company Ltd DuluxGroup Ltd SKYCITY Entertainment Group Ltd Monthly Return 4.27% 8.14% 4.28% Average Monthly Return 1.9% 2.73% 1.27% Variance 0.00832 0.0026 1.54 Standard Deviation 0.076% 5.05% 123.91% Return per unit of total risk 0.02 0.62 28.9 The stock that has highest return is DuluxGrup Ltd, followed by SKYCITY Entertainment Group Ltd, while Australian Agricultural Company Ltd has the least returns. The stock with the highest total risk is SKYCITY Entertainment Group Ltd followed by DuluxGroup Limited while Australian Agricultural Company Ltd has least total risk. Lastly, the stock with highest expected return per unit of total risk is SKYCITY Entertainment Group Ltd followed by DuluxGrup Ltd while the stock with least return per unit of total risk is Australian Agricultural Company Ltd. Question 1c: Three stocks may have the same expected returns, but have different levels of risk, as measured by variance and its square roots, standard deviation (Fabozzi and Francis, 2000). By using historical returns on a company’s stock, an investor can calculate the variance of past stock returns. Past returns are not always reliable indicators of future results (Glosten, Jaganathan and Runkle 1993). Nonetheless, when an investor calculate variance and its root square, standard deviation based on historical stocks returns is a preferred method, because these two methods will rely on historical facts, as opposed to unquantified speculations regarding the future. DuluxGrup Ltd (2.73%) has higher mean return than SKYCITY Entertainment Group Ltd (2.37%) and Australian Agricultural Company Ltd (1.9%). But SKYCITY Entertainment Group Ltd has more volatility (123.91%) than DuluxGrup Ltd (5.05%) and Australian Agricultural Company Ltd (0.0076%). This is consistent with Finance Theory- higher risk is associated with higher average return (Handa, Kothari and Wasley, 1989). Therefore, it is true the stock that has highest total risk is the ‘riskiest’ of the three stocks. Question 1d: Question 1e: ‘Beta’ is a measure of the systematic risk or volatility, of a portfolio or security in comparions to the market as a whole. Beta in CAPM model is used to calculates the expected return of an asset based on the expected market returns. A beta of 1 will indicate that the share price will move with the market; as in the case of DuluxGroup Limited. A beta of greater than 1 will indicate that the share price will be more volatile than the market price as in the case of SKYCITY Entertainment Group Limited. Lastly, a beta of less than 1 means the share price will be less volatile than the market price as in the case of Australian Agricultural Company Ltd. Question 1f: Lower risk free rates, holding all else constant, result in lower discount rates, and lower discount rates, all else held the same, will result in higher value (Fabozzi and Francis, 2000). Those lower risk free rates are good for the economy and markets. Therefore, if the risk free rate is at 6.5% the share price will be higher as compared to when the risk free rate is at 2.5% that will make the share price to be low. Question 2: Question 2a: Alternative to CARM is Multi Beta Models which encompasses ‘Arbitrage Pricing Model’ and Multifactor Model. And accounting information based Models. In Arbitrage Pricing Model is based on the idea that a firm’s assets returns is predicted using the relationship between assets and many common risk factors- the level of interest rates, growth rate in the GDP, the slope of the yield curve (Bello, 2008). This model predicts a relationship between the returns of portfolio and the returns of a single asset through linear combination of many independent macro-economic factors or variables (Fama and MacBeth, 1973). While Multifactor mode, used historical information or data to relate firm’s stock returns specific macro economic factors or variables and estimates betas for firms against macro factors (Bello, 2008). In accounting information based Models, for those investors who are suspicious of any market based measure, firm’s accounting information can be used to come up with a measure of risk (Rubinstein, 2006). In particular, firms that have high dividends, low debt rations, growing accounting earnings, stable and large cash holdings should be less risky to equity investors than companies or firms without these attributes or characteristics (Hill, 1975). Question 2b: Advantage of accounting information based Models is that risks that are related to a firm’s fundamentals, which seems more in keeping with intrinsic valuation view of the world (Rubinstein, 2006). While it disadvantage is Accounting numbers can be deceptive and the estimates can have significant errors associated with the firm. If an investor does not trust market prices, the investor can use accounting data to construct the risk measures (Bello, 2008). Multi Beta Models is an extension of the CAPM, with multiple betas replacing a single market beta, with risk premiums to go with each one (Rubinstein, 2006). The advantage of Multi Beta Models is that it do better than the CAPM in explaining to an investor the past return differences across the investments (Rubinstein, 2006). While it disadvantage, for forward looking estimates, the improvement over the CAPM is debatable. Reference List Arnott R, Kalesnik V, Moghtader P, Scholl C 2009, Beyond capweight:The search for efficient beta. J. Indexes, 13(1):1-25. Bello, Z.Y 2008, A statistical comparison of the CAPM to the Fama- French three factor model and the Cahart’s model. Global J. Financ.Banking, 2(2): 14-24. Fabozzi, F.J. and J.C. Francis 2000, “Beta as a random Coefficient.” Journal of Financial and Quantitative Analysis 13, pp. 101-116. Fama, E.F. and J.D. MacBeth 1973, “Risk, Return, and Equilibrium: Empirical Tests.” Journal of Political Economy 18, pp. 607-636. Glosten, L.R., R. Jaganathan and D. Runkle 1993, “ On the Relationship Between the Expected Value and the Volatility of the Normal Excess Return on Stocks.” Journal of Finance 3, pp . 1779-1801. Handa, P., S.P. Kothari, and C.E. Wasley 1989, “The Relation Between the Return Interval and Betas:Implicatioins for the Size Effect.” Journal of Financial Economics 23, 79-100. Hill, B. M. 1975, “A Simple Approach to Inference about the Tail of a Distribution.” Annals of Statistics 3, pp. 1163-1174. Rubinstein, M 2006, A History of the Theory of Investments, John Wiley & Sons, Inc, Hoboken, Read More