Part 1 2
Part 1(a) 2
Part 1(b) 3
Part 1(c) 4
Part 2 5
Part 2(a) 5
Part 2(b) 5
Part 3 5
Part 3(a) 5
Part 3(b) 6
Part 3(c) 6
Part 3(d) 6
Part 4 7
The focus for the report aims to examine and analyse the behavior and performance of three stocks in different industries that are selected from the Australian Stock Exchange Market (ASX200). The three stocks have been selected from different industries, which include Telstra (Telecommunication industry), Lynas (Mining industry) and Wesfarmers Limited (Diversified Industry). From the data collected over 28 weeks for 27 periods, the ASX200 is used as a benchmarking proxy to evaluate the performances and trends on these three stocks. The 28-week historical stock price data is collected through the periods of 3rd February 2014 to 11th August 2014. The appendices display the calculations and historical data analysed throughout the report.
The discrete rate of return and the continuously compounded rate of return are two ways to calculate the returns on the three industry stocks and the ASX200. To determine the discrete rate of return, this is calculated by using the Holding Period Return (HPR) formula. Holding Period Return (HPR) shows how much the value of the investment has changed during the holding period, relative to the amount you invested (Bodie et.al 2013, 62). For our results, the adjusted closing price is used as a proxy instead of the closing price because it takes account of factors such as dividends, stock splits and new stock offerings (Hanks, 2008). The formula use for the discrete rate of return is shown in Equation 1. (1)
The formula used to calculate the continuously compounded rate of return is shown in Equation 2. (2)
Due to limited spacing, the discrete rate of return and continuously compounded rate of return are omitted in this section and it is shown in Appendix A.
The arithmetic mean return is an average of summing the value points in a data set and dividing them with the number of time periods (Mindlin, 2011). The calculation used to calculate the arithmetic mean return is shown in Equation 3. (3)
To calculate the geometric mean return, the period-to-period return is compounded and the equivalent per period return is obtained (Bodie et.al 2013, 63). This is shown as Equation 4 (4)
The calculated arithmetic mean returns and geometric mean returns, in addition to standard deviation and variance for each stock and the market index, is shown in Table 1, with sample calculations shown in Appendix A. It can be observed that the values of geometric returns are lower than the arithmetic mean. This is due to the prospective returns for the quarter-to-quarter variation in funds of the company being ignored in geometric returns.
Table 1: Arithmetic mean returns and geometric mean returns
- σ2 0.0001527
The variance is used to measure the spread between the data points and the mean value of the set of data. Variance can be calculated using Equation 5 below. (5)
Covariance measures the degree to which two sets of data change together. A positive covariance indicates the two stocks are moving together and a negative covariance indicates the two stocks will move inversely to the returns (Weisstein 2013). Investors who are risk-averse are more likely to buy stocks, which have a lower variance because this group of people dislikes the thought of risk. Hence, with a lower risk they will obtain a lower return. The covariance allows opportunities for investors to foresee the possible price movements in a portfolio where the portfolio can generate a higher return with lower risk. Equation 6 illustrates the formula used to calculate the covariance. (6)