Analysis Of Stock Markets In Australia
Part A: Risk And Return
|
^AORD (Rt) |
RIO(Rt) |
BHP(Rt) |
ANZ(Rt) |
WES(Rt) |
|
4.38% |
-5.14% |
-1.10% |
7.74% |
8.73% |
|
-2.78% |
-13.04% |
-12.36% |
-0.66% |
-0.16% |
|
3.72% |
-0.40% |
1.44% |
10.98% |
7.59% |
|
-5.05% |
-7.53% |
6.45% |
-14.51% |
-10.01% |
|
-2.86% |
-3.91% |
-10.61% |
6.05% |
0.91% |
|
5.31% |
9.09% |
9.92% |
4.05% |
2.40% |
|
1.76% |
0.27% |
3.15% |
-0.24% |
0.25% |
|
1.79% |
9.47% |
-0.03% |
3.61% |
3.62% |
|
3.81% |
3.90% |
7.18% |
9.48% |
4.38% |
|
-1.97% |
4.53% |
-0.72% |
-5.90% |
-1.36% |
|
0.73% |
6.18% |
1.59% |
3.76% |
2.58% |
|
-2.80% |
-5.99% |
-3.81% |
-6.74% |
-4.74% |
|
3.96% |
7.52% |
4.83% |
6.46% |
2.24% |
|
-0.23% |
-2.60% |
-5.10% |
2.82% |
-2.26% |
|
1.25% |
-0.83% |
5.27% |
4.18% |
3.62% |
|
0.05% |
-5.51% |
-1.98% |
-2.88% |
1.51% |
|
-1.69% |
5.49% |
-3.04% |
2.04% |
-3.57% |
|
4.38% |
5.40% |
7.46% |
1.87% |
5.08% |
|
0.03% |
-6.40% |
-5.34% |
-1.60% |
-1.63% |
|
-6.00% |
-7.28% |
-7.94% |
-7.81% |
-0.36% |
|
3.86% |
-2.49% |
2.20% |
8.01% |
4.59% |
|
-3.83% |
-2.90% |
-9.38% |
-4.83% |
-8.11% |
|
1.69% |
-1.17% |
-5.14% |
3.40% |
1.31% |
|
2.98% |
-4.28% |
-0.37% |
2.80% |
4.38% |
|
6.06% |
11.14% |
13.98% |
6.85% |
6.23% |
|
-0.62% |
-17.53% |
-8.11% |
3.61% |
-3.46% |
|
-1.52% |
10.30% |
5.73% |
-7.51% |
-0.57% |
|
0.02% |
-2.30% |
-0.96% |
-2.38% |
-0.11% |
|
-5.77% |
-6.03% |
-8.97% |
-0.39% |
-11.21% |
|
4.14% |
-6.49% |
-2.24% |
1.48% |
8.40% |
|
-8.44% |
-5.48% |
-3.70% |
-15.71% |
-4.31% |
|
-3.18% |
-0.23% |
-13.73% |
-3.09% |
-0.80% |
|
4.45% |
2.75% |
7.16% |
0.48% |
0.48% |
|
-1.34% |
-9.87% |
-24.10% |
-0.22% |
-3.41% |
|
2.39% |
-12.75% |
-1.28% |
6.46% |
8.84% |
|
-5.54% |
-16.66% |
-15.14% |
-14.42% |
1.34% |
|
-2.17% |
5.72% |
1.42% |
-7.65% |
-7.58% |
|
4.04% |
11.87% |
7.96% |
4.62% |
8.14% |
|
3.14% |
17.45% |
21.63% |
3.39% |
3.13% |
|
2.45% |
-18.27% |
-8.05% |
4.87% |
-5.13% |
|
-2.55% |
11.00% |
-2.28% |
-2.25% |
-1.31% |
|
6.09% |
4.74% |
4.56% |
6.89% |
6.82% |
|
-2.05% |
-8.42% |
4.56% |
4.02% |
-1.15% |
|
-0.08% |
11.54% |
9.12% |
2.68% |
6.00% |
|
-2.25% |
4.25% |
3.95% |
0.79% |
-7.26% |
|
1.83% |
8.42% |
5.65% |
1.99% |
1.86% |
|
3.86% |
1.44% |
2.63% |
9.70% |
0.86% |
|
-0.77% |
15.24% |
6.11% |
-3.79% |
-4.56% |
|
1.50% |
-7.58% |
-6.35% |
5.35% |
5.93% |
|
2.45% |
0.72% |
-3.92% |
2.93% |
7.77% |
|
0.74% |
-2.14% |
0.79% |
2.91% |
-4.70% |
|
-3.18% |
1.22% |
0.76% |
-15.66% |
-0.70% |
|
0.05% |
4.84% |
-2.63% |
5.15% |
-6.23% |
|
0.17% |
11.32% |
10.47% |
3.12% |
1.51% |
|
0.04% |
3.53% |
5.75% |
-0.78% |
4.54% |
|
-0.55% |
-1.57% |
-6.02% |
0.68% |
-0.22% |
|
3.95% |
1.56% |
4.83% |
1.08% |
1.13% |
|
1.34% |
-0.06% |
2.82% |
-5.00% |
4.95% |
|
1.80% |
9.99% |
7.99% |
3.65% |
1.13% |
|
Particulars |
^AORD (Rt) |
RIO(Rt) |
BHP(Rt) |
ANZ(Rt) |
WES(Rt) |
|
Monthly returns |
0.39% |
0.27% |
0.05% |
0.61% |
0.63% |
|
Annual return |
105% |
103% |
101% |
108% |
108% |
|
Correlation Coefficient |
^AORD (Rt) |
RIO(Rt) |
BHP(Rt) |
ANZ(Rt) |
WES(Rt) |
|
^AORD (Rt) |
1.0000 |
0.3246 |
0.5122 |
0.7490 |
0.6815 |
|
RIO(Rt) |
0.3246 |
1.0000 |
0.7156 |
0.1664 |
0.1821 |
|
BHP(Rt) |
0.5122 |
0.7156 |
1.0000 |
0.2350 |
0.3142 |
|
ANZ(Rt) |
0.7490 |
0.1664 |
0.2350 |
1.0000 |
0.4914 |
|
WES(Rt) |
0.6815 |
0.1821 |
0.3142 |
0.4914 |
1.0000 |
From the evaluation of above table, it can be identified that the highest correlation is between Rio Tinto and BHP Billiton, where the values are at the levels of 0.7156. In addition, the least correlation is between ANZ Bank and Rio Tinto, where the values are at the levels of 0.1664. Further evaluation of the correlation table indicates that ANZ Bank has the highest correlation with the market, while Rio Tinto has the lowest correlation (Fang et al. 2018).
There are certain economic reasons behind the correlation between the high and low correlated organisations. The high correlation between Rio Tinto and BHP Billiton is because of their underlying industry, where both the companies fall under mining industry of Australia. Hence, the changes in values of mining industry directly affect the share price valuation of both Rio Tinto and BHP Billiton. The low correlation is between ANZ Bank and Rio Tinto, as both the companies fall in different sectors. The changes in market conditions of Rio Tinto alter the share price valuation of the organisation, where increment in one will result in slow improvement of other. Therefore, using ANZ Bank and Rio Tinto for diversification could eventually help the portfolio to minimise the risk from investment.
|
Particulars |
^AORD (Rt) |
RIO(Rt) |
BHP(Rt) |
ANZ(Rt) |
WES(Rt) |
|
Standard Deviation |
0.032444732 |
0.08068 |
0.076442 |
0.060728 |
0.047715 |
|
Beta |
1.24 |
2.07 |
3.80 |
4.40 |
|
|
CAPM |
7.08% |
10.79% |
18.61% |
21.31% |
The expected return from CAPM is different from the above calculation, as CAPM uses beta, risk free rate and market returns to analyse the level of return, which should be provided by an investment. The valuation of stocks cannot be determined, as no adequate information is presented for deriving the intrinsic value of stock to valuate it with the current share price (Bao, Diks and Li 2018).
|
Particulars |
Amount |
|
Building cost |
$ 24,000 |
|
Equipment |
$ 16,000 |
|
Net working capital |
$ 12,000 |
|
Net Initial Investment |
$ 52,000 |
|
Particulars |
Year 1 |
Year 2 |
Year 3 |
Year 4 |
|
Total cost of production |
$ 58,000 |
$ 58,000 |
$ 58,000 |
$ 58,000 |
|
Particulars |
Year 1 |
Year 2 |
Year 3 |
Year 4 |
|
The incremental EBIT |
-12.07% |
12.80% |
1.94% |
|
Particulars |
Year 1 |
Year 2 |
Year 3 |
Year 4 |
|
Incremental operating cash flows after tax |
4.07% |
-3.64% |
67.45% |
|
Particulars |
Market value |
|
Building |
$ 15,000 |
|
Equipment |
$ 4,000 |
|
Particulars |
Value |
|
Building book value |
$ 21,816.00 |
|
Building market value |
$ 15,000.00 |
|
Total loss from sale |
$ (6,816.00) |
|
Tax shield |
$ (2,044.80) |
|
Particulars |
Value |
|
Equipment Book value |
$ 2,720 |
|
Equipment sell price |
$ 4,000 |
|
Total gain from sale |
$ 1,280 |
|
Capital Gain tax |
$ 384 |
|
Particulars |
Value |
|
Building |
$ 15,000 |
|
Equipment |
$ 4,000 |
|
Total cash inflow from non-operating cash flows |
$ 19,000 |
|
Particulars |
Year 1 |
Year 2 |
Year 3 |
Year 4 |
|
Sales |
80,000.00 |
80,000.00 |
80,000.00 |
80,000.00 |
|
Variable manufacturing cost |
48,000.00 |
48,000.00 |
48,000.00 |
48,000.00 |
|
Fixed overhead cost |
10,000.00 |
10,000.00 |
10,000.00 |
10,000.00 |
|
Total cost of production |
58,000.00 |
58,000.00 |
58,000.00 |
58,000.00 |
|
Depreciation |
3,512.00 |
5,744.00 |
3,664.00 |
2,544.00 |
|
Loss of building sale |
(2,044.80) |
|||
|
Profit from equipment sale |
1,280.00 |
|||
|
Income |
18,488.00 |
16,256.00 |
18,336.00 |
18,691.20 |
|
Tax |
5,546.40 |
4,876.80 |
5,500.80 |
5,607.36 |
|
PAT |
12,941.60 |
11,379.20 |
12,835.20 |
13,083.84 |
|
Total Cash flow |
16,453.60 |
17,123.20 |
16,499.20 |
27,627.84 |
|
NPV |
5,643.02 |
The positive value of NPV analysis indicates that Myer Inc should accept the project, as it will increase the firm value in future.
|
Particulars |
NPV Value |
|
Normal |
5,643.02 |
|
Increase in sales by 10% |
12,446.68 |
|
Decrease in sales by 10% |
(1,160.64) |
|
Particulars |
NPV Value |
|
Normal |
5,643.02 |
|
Increase in cost of capital by 10% |
4,097.13 |
|
Decrease in cost of capital by 10% |
7,258.20 |
Reference and Bibliography:
Bao, T., Diks, C. and Li, H., 2018. A generalized CAPM model with asymmetric power distributed errors with an application to portfolio construction. Economic Modelling, 68, pp.611-621.
Baum, A.E. and Crosby, N., 2014. Property investment appraisal. John Wiley & Sons.
Fang, L., Chen, B., Yu, H. and Xiong, C., 2018. The effect of economic policy uncertainty on the long-run correlation between crude oil and the US stock markets. Finance Research Letters, 24, pp.56-63.
Fard, H.V. and Falah, A.B., 2015. A New Modified CAPM Model: The Two Beta CAPM. Jurnal UMP Social Sciences and Technology Management Vol, 3(1).
Li, F.G. and Trutnevyte, E., 2017. Investment appraisal of cost-optimal and near-optimal pathways for the UK electricity sector transition to 2050. Applied energy, 189, pp.89-109.
Lokman, S., Volker, D., Zijlstra-Vlasveld, M.C., Brouwers, E.P., Boon, B., Beekman, A.T., Smit, F. and Van der Feltz-Cornelis, C.M., 2017. Return-to-work intervention versus usual care for sick-listed employees: health-economic investment appraisal alongside a cluster randomised trial. BMJ open, 7(10), p.e016348.
Nasiri, M., Alishah, A.Y., Sayyahmelli, S.A.S. and Karimi, A., 2017. Estimating Expected Return based on Capital Asset Pricing Model compared with Stock Interest Rate at Tehran Stock Exchange. HELIX, 7(2), pp.1406-1415.
Nghiem, L., 2015. Risk-return relationship: An empirical study of different statistical methods for estimating the Capital Asset Pricing Models (CAPM) and the Fama-French model for large cap stocks. arXiv preprint arXiv:1511.07101.
Sattar, M., 2017. CAPM Vs Fama-French three-factor model: an evaluation of effectiveness in explaining excess return in Dhaka stock exchange. International Journal of Business and Management, 12(5), p.119.
Shortall, J., Shalloo, L., Foley, C., Sleator, R.D. and O’Brien, B., 2016. Investment appraisal of automatic milking and conventional milking technologies in a pasture-based dairy system. Journal of dairy science, 99(9), pp.7700-7713.
Upton, J., Murphy, M., De Boer, I.J.M., Koerkamp, P.G., Berentsen, P.B.M. and Shalloo, L., 2015. Investment appraisal of technology innovations on dairy farm electricity consumption. Journal of dairy science, 98(2), pp.898-909.
Warren, L. and Seal, W., 2018. Using investment appraisal models in strategic negotiation: the cultural political economy of electricity generation. Accounting, Organizations and Society.