Three Stocks: Csl, Dmp and Tcl

FINC5001

 Capital Market and Corporate Finance Major Assignment

Group Name: Rich with Lix

Lecture Stream: Stream 6

Lecturer: Dr Tro Kortian

Three Stocks: CSL, DMP and TCL

Contents

EXECUTIVE SUMMARY        2

1.        Background of CSL, DMP and TCL        3

2.        Justification of data selection        3

2.1        Choice of timeframe and data frequency        3

2.2        Expected return and standard deviation        4

3.        Portfolio Combinations        5

3.1        Calculation of expected return and standard deviation of the portfolio        5

3.2        Portfolio constructions and the portfolio with the lowest risk        6

3.3        Graph of the portfolios        7

4.        Risk-free asset        8

4.1        Justification of the chosen risk-free asset        8

4.2        Calculation of expected return and standard deviation of the risk-free asset        8

5.        Investment strategy        9

5.1        Portfolio A with risk-free asset        9

5.2        New portfolio analysis        10

Reference list        13

EXECUTIVE SUMMARY

The primary objective of this analysis is to determine and recommend a portfolio investment combined by three stocks from different industries, which listed on the Australian Securities Exchange (ASX). Since investors in this case are prefer to long-term investments, hence, our analysis form the portfolio combine with three selected stocks: CSL Limited (CSL), Domino's Pizza Enterprises Limited (DMP) and Transurban Group Stapled (TCL). This analysis would starts with the justification of the appropriateness of data collection, which followed by particular calculation in expected return and standard deviation. Detailly, 10-year estimated period and monthly sample data would be used in the analysis. Subsequently, a suitable proxy risk-free asset would be selected based on the constructed portfolios which comprising different weights of CSL, DMP and TCL. Finally, corresponding investment recommendations would be given based on the rationale and underlying assumptions from the result of two different calculation methods.

1. Background of CSL, DMP and TCL

1. CSL Limited

CSL Limited is a global bio-technology company that specialized in biopharmaceutical and related products development, manufactory and marketing, which delivers innovative biotherapies that save lives to people who is suffering life-threatening (CSL Limited Annual Report, 2015).

1. Domino's Pizza Enterprises Limited

Domino’s Pizza Enterprises Ltd (DMP) has the largest pizza chain in Australia no matter in network store numbers or network sales (Domino's Pizza Enterprises Limited Annual Report, 2015). At the same time, DMP’s business extends across six countries and could be considered as the largest franchisee for the brand of Domino’s Pizza around the world (Domino's Pizza Enterprises Limited Annual Report, 2015).

1. Transurban Group Stapled

Transurban Group is a company that focuses on developing and maintaining urban toll road networks in both Australia and the United States of America (Transurban Annual Report, 2015).

1. Justification of data selection

1. Choice of timeframe and data frequency

Timeframe should be chosen on the basis of different needs, as alternative time frames could lead to different results (Blacklock et al, 2008). As we find out that the client in this case have better interest in permanent investment. Thus, comparing with short periods such as 1 year, Arnold (2005) deems it plays a small role in long-term investment estimation. For a period of 5 years horizon, it is more appropriate for investors who are seeking for intermediate returns (Ng and Wu, 2006).  In addition, Bradfield (2003) states that over long period such as 20 years would be unreliable to current analysis due to the significant variations, which happens in firm’s not only internal circumstance but also external environment. In order to acquire more relevant and reliable information, the latest ten years should be chosen as the length of the estimation period. Hence, in our study, we treat a ten-year period from 2005 to 2015 as the most suitable selection for data collection.        

In our analysis, monthly data has been chosen as the sampling interval. Moon and Waggle (2006) assert that daily and weekly data are more fluctuant due to some significant changes in a specific day. In addition, short period data are more easily overestimate the risk of investment (Moon and Waggle, 2006) Moreover, under the consideration of Howe and Xing (2003), they insist that in data analysis, the most frequently applied intervals are weekly and monthly. At the same time, Bradfield’s argument (2003) claims monthly intervals could offer the optimal predictive data. Consider all elements, our analysis select monthly data for the purpose to get more accurate and precise calculation results.