Deakin University MAF707: Investment Analysis and Portfolio Management

This report provides a comprehensive analysis of Exchange Traded Funds (ETFs) and index funds, evaluating their impact on the asset management industry. The analysis includes a detailed examination of nine specific ETFs, utilizing Bloomberg data to assess their fund structure, objectives, sectoral diversification, performance, and risk analytics. The report delves into the performance metrics of an equally weighted portfolio, calculating Sharpe and Treynor ratios, and assessing risk and return. Furthermore, it explores the creation of portfolios with varied target returns, examining the efficient frontier and investment strategies. The report utilizes data from the appendix to determine the appropriate level of income that could be generated from an investment. The findings highlight the importance of diversification and risk assessment in portfolio construction, providing valuable insights for investors seeking to optimize their investment strategies and maximize returns.

Running head: INVESTMENT ANALYSIS AND PORTFOLIO MANAGEMENT
Investment Analysis and Portfolio Management
Student Name:
Student Number:
Authors Note:

INVESTMENT ANALYSIS AND PORTFOLIO MANAGEMENT
Executive Summary:
The assessment has been conducted relevant evaluation regarding the investment scope that is
presented to the investor who are utilizing the ETF and index funds for their investments. The
analysis mainly helps in determining the appropriate level of investment that could be
conducted on certain portfolios to generate higher level of income in the process. The
calculations process that is used for detecting different type of investment scope are also
depicted in the assessment. Thus, the calculation would eventually help in determining the
sanguinarine of Sharpe and Treynor ratio, which is used by the investors, while making
relevant investment decisions.

INVESTMENT ANALYSIS AND PORTFOLIO MANAGEMENT
Table of Contents
Introduction:...............................................................................................................................3
Part I:..........................................................................................................................................3
Discussing the evaluation of index fund and exchange traded funds, which has disrupted the
asset management industry in General:......................................................................................3
Discussing the nine ETFs in details with the help of the Bloomberg data:...............................4
Part II:.........................................................................................................................................8
a) Commenting on the performance by using the return, risk, Sharpe ratio and Treynor ratio: 8
b) Creating the relevant portfolios with different types of target returns:.................................9
Conclusion:..............................................................................................................................12
References and Bibliography:..................................................................................................13
Appendix:.................................................................................................................................16

INVESTMENT ANALYSIS AND PORTFOLIO MANAGEMENT
Introduction:
The assessment evaluates the implication of exchanges traded funds and index funds
that allow the investors to improve their investment scope in the capital market. The further
analysis has been conducted for the preparation of the portfolios with different levels of
returns that detects the overall efficient frontier of the combined portfolios that can help in
generating high level of income in the process. The scrutiny has indicated the use for
detecting the significance of the portfolios, which states about the level of income that might
be generated from an investment. Thus, relevant description has been conducted on the
selected funds and the returns it can generate from an investment.
Part I:
Discussing the evaluation of index fund and exchange traded funds, which has disrupted
the asset management industry in General:
Index fund and the exchange traded funds have adequate history that unfolds the
polled investing, which is been conducted by investors throughout history since 1774. After
the pooled investing the first open ended mutual funds was created after 1.5 years, which
allowed the investors to buy and sell shares on the daily basis. Thus, index funds and ETFs
have been in demand since the creation of such funds, as they provide access to the investors
for increasing their diversification and create satisfactory level of returns in the process.
However, the alterations amongst the exchange traded fund and index fund mainly permits
the investors to surge their investment exposure in accordance with their investment scope.
Chandra (2017) stated that ETFs have been the center point of investment, as investors with
the help of the funds are able to bet on the underlying index, which was not possible
previously.

INVESTMENT ANALYSIS AND PORTFOLIO MANAGEMENT
The information provided in the above figure mainly indicates about the increment in
the ETFs investment value over the years after its incorporation. The figure has indicated
about the level of demand from investors regarding the ETFs, which is skyrocketing the total
value of investments that is been conducted in the investment opportunity. The evolution of
both index fund and ETFs have been enormous, as both investment option allowed the
investors to increase tier exposure into new type of investments, which was not possible
previously. The funds are popular due to its distinct feature, where it allows the investors to
reduce the level of cost, increase tax efficiency and provide stock like features. Therefore, it
has been detected that investors utilizing the ETFs are able to secure their investments and
generate high level of revenues from their exposure in the long run.
Discussing the nine ETFs in details with the help of the Bloomberg data:
AUST AU Equity (BetaShares Managed Risk Australian Share Fund):

INVESTMENT ANALYSIS AND PORTFOLIO MANAGEMENT
The fund structure mainly comprises of Equity class assets from Australia, which is
mainly focused in large-cap investments. The fund mainly comprises of 200 of the largest
equities that are present on the ASX, as it aims to reduce the level of volatility from the
exposure and increase the level of returns in the process. The fund has a relevant sectorial
diversification, where it invests in Banks, mining, food, REITS, Biotechnology, Insurance,
Commercial Services, Oil&Gas, Telecommunications, and diversified Finan Serv.
Furthermore, the risk analytics have mainly indicated that the fund has a tracking error of
4.580, while the NAV tracking error is at 4.253 and Information ratio is at -1.172. this mainly
indicated that the risk attributes of the fund are limited and the portfolio manager is activily
altering the investment to support the underlying benchmark.
CBDAX GR Equity (ComStage ETF DAX):
The main structure of the fund is related to the equity investments with large Cap
organizations. The portfolio manager mainly aims in tracking the performance of DAX
Index, while reinvesting the dividend income and increasing the performance of the ETF. The
fund mainly comprises of Stocks from Chemical, Insurance, Software, Auto Manufacturing,
Miscellaneous Manufacture, Pharmaceuticals, Apparel, Telecommunications, Electric and
Healthcare-services industry. The tracking error is at 3.232, while the Nav tracking error is at
0.179 and Information ratio is at 0.020, which indicates that risk conditions of the fund is
under control, as the portfolio manager is utilizing the investment options to reduce the
negative exposure of the investment. The fund mainly holds around 30 holdings, which help
the management to effectively improve the investment conditions and reduce the total risk
involved in investments.
LYXDAX GR Equity (Lyxor Dax UCITS):

INVESTMENT ANALYSIS AND PORTFOLIO MANAGEMENT
The main aim of the fund is to tracking the performance of DAX index, while being
an open ended UCITS IV compliant exchange traded fund. The fund mainly holds 30
individual stocks, which are mainly from Chemical, Insurance, Software, Auto
Manufacturing, Miscellaneous Manufacture, Pharmaceuticals, Apparel, Telecommunications,
Electric and Healthcare-services industry. In addition, the funds risk is fairly limited with the
Tracking error of 3.113, Nav tracking error of 0.167 and Information ratio of 0.015.
SH US Equity (ProShares Short S&P 500):
The fund has an objective to seek investment results that are inverse of the daily
performance achieved by S&P 500 Index. The fund mainly holds a total of 19 stocks and is
considered highly risky with a tracking error of 33.583, Nav tracking error of 33.586 and an
Information ratio of -0.239. The index fund is considered risky, as it shorts the S&P 500
Index, and performance exactly as the inverse mirror image of the index.
SPXL US Equity (Direxion Daily S&P Bull 3X Shares):
The objective of the fund is to provide 300% of the performance of the S&P 500
Index. The fund comprises of 4 derivatives, which are iShares Core S&P 500 ET, Dreyfus
Government Cash, Goldman Sachs Financial and Goldman Sachs Government. The fund
rebalances its self on daily basis to achieve the required level of returns, as per their
objective. In addition, the tracking error is at the levels of 33.640 with a Nav tracking error of
33.009 and Information ratio of 0.211.
SSO US Equity (ProShare Ultra S&P500 ETF):
The fund mainly aims in seeking daily investment results that is mainly twice the
daily performance of the S&P 500 index. The fund mainly comprises of 507 holdings which
replicates that funds and investment of the index. The fund is relatively considered a high-
risk endeavor with a tracking error of 16.429, Nav tracking error of 16.533 and information

INVESTMENT ANALYSIS AND PORTFOLIO MANAGEMENT
ratio of 0.159. Moreover, the fund replicates the strategy of derivates, with a beta of 2.019
and an average return from 9.42% to -13.85%.
XDAX GR Equity (Xtrackers DAX UCITIS ETF):
The fund aims in replicating the performance of DAX Index, by conducting the direct
investment in German equities, where the number of holdings is at the levels of 30. In
addition, the fund focuses on Chemical, Insurance, Software, Auto Manufacturing,
Miscellaneous Manufacture, Pharmaceuticals, Apparel, Telecommunications, Electric and
Healthcare-services industry. Moreover, the information ratio value is at 0.017 with the
tracking error of 3.095 and Nav tracking error of 0.178. The risk attributes of the fund is
relevantly low in comparison to fund present in the analysis.
XIC CN Equity (iShare Core S&P/TSX Capped Composite Index ETF):
The main objective of the fund is to conduct relevant long term capital growth, where
the iShares Core S&P/TSX Capped Composite index ETF is mainly used for relevant
investment options. The number of holdings of the fund is mainly at the levels of 272, which
can help in determining the appropriate level of income from investment. However, the risk
analysis has indicated the fund is less volatile, where the tracking error is at 0.820, Nav
tacking error is at 0.038 and Information ratio is at -0.047.
SPY US Equity (SPDR S&P 500 ETF Trust):
The trust is an exchange traded fund that mainly tracks to performance of S&P 500
Index, where the total holding present in the fund is based on the market cap. In addition, the
fund held a total stock of 505, while conducting the relevant trade with a low risk. The
tracking error is at the levels of 0.471 with the Nav tracking error of 0.060 and Information
ratio of -0.146.

INVESTMENT ANALYSIS AND PORTFOLIO MANAGEMENT
Part II:
a) Commenting on the performance by using the return, risk, Sharpe ratio and Treynor
ratio:
Weight Average continuously compounded return Weighted return
11.11% 0.000107234 0.001%
11.11% 0.000194622 0.002%
11.11% 0.000625046 0.007%
11.11% -0.000429619 -0.005%
11.11% 4.92531E-05 0.001%
11.11% 0.000797538 0.009%
11.11% 0.000108887 0.001%
11.11% 9.87153E-05 0.001%
11.11% 0.000350112 0.004%
100.00
%
Mean port. ret.(daily) 0.0211%
Target ret. Annual 5.33%
Port. Variance (daily) 0.0069%
Port. St. dev (daily) 0.8315%
Port. St. dev (Annual) 13.2001%
Risk free rate 1.50%
Sharpe ratio 0.2898
Beta 1.02
Treynor ratio 0.0.375
The information provided in the above table directly states about the overall
performance of the equally weighted portfolio in terms of Sharpe ratio, Treynor ratio, risk
and return. The analysis of the information has mainly indicated that the equally weighted
portfolio will yield a beta level of 1.02 with an annual standard deviation of 13.2001% and an
annual return of 5.33%. Thus, the performance of the equally weighted portfolio is
considered to be appropriate, which can allow the investors to generate high level of income
in the process. The values of the Sharpe ratio are at 0.2898, while he Treynor ratio is at
0.0375, which can be understood that the performance of the portfolio is appropriate and
could create high level of revenues from their exposure in the long run (Chandra 2017).

INVESTMENT ANALYSIS AND PORTFOLIO MANAGEMENT
The summary statistics depicted in the appendix mainly indicates about the level of
returns and risk conditions of each fund, which has been used for preparing the portfolio for
investment. The descriptive analysis has mainly stated about the risk and return capability of
each stock, which indicates that the increment is returns is supported by high level of
standard deviation volatility. The major information that is provided from the descriptive
analysis is the mean and standard deviation of the 9 funds, which can be used while
evaluating the preparing the relevant portfolios (DeFusco et al. 2015).
b) Creating the relevant portfolios with different types of target returns:
The analysis of the appendix has mainly stated about the different types of returns and
risk that is associated with the portfolios formed for speculations. The portfolio analysis is
mainly conducted to determine the level Sharpe ratio and Treynor ratio that is present within
the investment opportunity. The analysis has been conducted for detecting the appropriate
level of income that could be generated from an investment. On the contrary, Damodaran
(2016) argued that investors mainly tend to formulate portfolios with different level of risk
and correlation conditions, as it increase the diversification and reduces the level of
implication from the capital market movement on the portfolio. The appendix analysis has
mainly stated that the overall returns of the portfolio is mainly linked with its risk attributes.
Hence, it is seen that whenever the return requirements of the portfolio increase the risk
attributes also increases. Therefore, investors can choose the portfolio in accordance with
their risk appetite, which can help in generating the required level of returns with certain risk
associated with the investment. Williams and Dobelman (2017) stated that investors utilize
the data of returns and risk to formulate different level of portfolios, which can be used for
creating the efficient frontier that states regarding the investment scope that could be used for
generating high level of revenues in the long run.

INVESTMENT ANALYSIS AND PORTFOLIO MANAGEMENT
The analysis of the Treynor ratio has been conducted with the help of the returns and
beta of the portfolio, which is then contemplated with the risk-free rate. Therefore, the
information used in the calculations of the Treynor ratio directly helps the investors to detect
the level of security and additional investment that could be generated from a particular
investment. The Treynor ratio directly helps in determining the volatility models, where the
excess returns are mainly evaluated to determine the level of risk to reward ratio. The
portfolio created for evaluation has mainly indicated that the increment in retunes with the
risk has shown high values of Treynor ratio from portfolio 8 to portfolio 19. On the other
hand, other portfolios received a low Treynor ratio in comparison to other portfolios. Thus, it
could be understood that when the specified returns of the portfolio increased from the levels
of 8% to 20% the overall performance of the Treynor ratio was at the highest level. This
indicated that risk to reward ratio was appropriate and could allow the investor to generate
high level of income from the investment. However, the reduction of return from 8% or the
increment of return from 20% would lead to the reduction in the values of the Treynor ratio,
which is mainly not favorable for the investors. Casson and Russell (2017) indicated that
investors by utilizing the Treynor values could adequately detect the level of risk to reward
ratio that might be provided from a particular investment.
The analysis of Sharpe ratio is also conducted in the Appendix, which could allow the
investor to increase the level of income from their investment. Therefore, investor utilize the
Sharpe ratio method for detecting the level of income that might be brought from an
investment in the portfolio with higher Sharpe ratio in comparison to other investments. In
addition, the evaluation has indicated that the investors can use the data from the Sharpe ratio
to conduct relevant investment decisions and generate high level of income in the process.
The values depicted in the Appendix regarding the 19 portfolios directly state that
investments in 12 portfolios would be beneficial for the investor in comparison to the other 7

INVESTMENT ANALYSIS AND PORTFOLIO MANAGEMENT
portfolios. Thus, it has been detected that the overall performance of the Sharpe ratio has
indicated the increment in the performance of the portfolio from the levels of portfolio 9 to
portfolio 17. The calculations have indicated that the performance of the portfolio within the
returns of 9% to 17% has the highest level of Sharpe ratio, which indicates that the
performance of the investment would be higher in comparison to other portfolios. Thus, a
portfolio with high Sharpe ratio is considered superior to other portfolios, as it would help in
generating high level of income from investment. Mauleon and Hamoudi (2017) stated that
investors utilizing the Sharpe ratio mainly uses the standard deviation values to determine the
level of volatility that is present within the stock before conducting any kind of investments.
Thus, the combination of the returns that is provided by each portfolio created for the
evaluation has indicated an adequate pattern that can be used by investors with different risk
and return requirements. The analysis the appendix also helps in detecting the efficient
frontier, which relevantly indicates about the risk to reward conditions of the investments in
the particular portfolios. Thus, investor with high level of risk would be able to generate
higher returns in comparison to other portfolios. Thus, the investors could use different levels
investment weights to support their risk attributes and generate adequate returns in the
process. Krupa (2016) indicated that change in the investor’s perspective is directly reflected
on their portfolio creation process, as investors with conservative stance would mainly have
low risk investment attuites associated with their portfolios.
Thus, the performance of the created portfolios is depended on the risk attributes,
where increment in risk would result in higher returns. However, the valuation of the Treynor
ratios has indicated that the performance of portfolio 8 to 19 is relevantly higher in
comparison to other portfolios. On the other hand, the higher performance of the portfolio in
accordance with the Sharpe ratio is mainly associated with Portfolio 9 to 17, where the values
of the calculation are the highest. Hence, the investment in portfolio 9 to 17 would be

INVESTMENT ANALYSIS AND PORTFOLIO MANAGEMENT
beneficial for the investors, as it would help in raising the risk to reward ratio from
investment.
Conclusion:
The assessment is based on the evaluation of the ETFs and index funds, which can be
used by the investor to improve their return generation capability. In addition, the evaluation
has indicated that ETFs have growth in value over the years, as investors see the benefit that
would be cultivated from such investment scope. Further analysis has been conducted on the
selected 9 funds with whom relevant portfolios have been created for investment purposes.
Thus, the calculations that have been conducted for Sharpe ratio and Treynor ratio has mainly
helped in selecting Portfolio 9 to 17 as the ideal investment options, which can be used by the
investors to generate higher returns in the process.

INVESTMENT ANALYSIS AND PORTFOLIO MANAGEMENT
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of gas-turbine combined heat and power systems for commercial buildings under different
climatic and market scenarios. Energy conversion and management, 183, pp.35-49.
Casson, P. and Russell, D., 2017. Universities superannuation scheme: implementing
responsible investment. In Responsible Investment (pp. 158-171). Routledge.
Chandra, P., 2017. Investment analysis and portfolio management. McGraw-Hill Education.
Chandra, P., 2017. Investment analysis and portfolio management. McGraw-Hill Education.
Chen, L., Wang, Y., Lai, F. and Feng, F., 2017. An investment analysis for China's
sustainable development based on inverse data envelopment analysis. Journal of cleaner
production, 142, pp.1638-1649.
Chisholm, D., Sweeny, K., Sheehan, P., Rasmussen, B., Smit, F., Cuijpers, P. and Saxena, S.,
2016. Scaling-up treatment of depression and anxiety: a global return on investment
analysis. The Lancet Psychiatry, 3(5), pp.415-424.
Damodaran, A., 2016. Damodaran on valuation: security analysis for investment and
corporate finance (Vol. 324). John Wiley & Sons.
DeFusco, R.A., McLeavey, D.W., Pinto, J.E., Runkle, D.E. and Anson, M.J.,
2015. Quantitative investment analysis. John Wiley & Sons.

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Edwards, R.D., Magee, J. and Bassetti, W.C., 2018. Technical analysis of stock trends. CRC
press.
Gaudard, L., 2015. Pumped-storage project: A short to long term investment analysis
including climate change. Renewable and Sustainable Energy Reviews, 49, pp.91-99.
Guillen, J., Cheilari, A., Damalas, D. and Barbas, T., 2016. Oil for fish: An energy return on
investment analysis of selected European Union fishing fleets. Journal of Industrial
Ecology, 20(1), pp.145-153.
Kock, A., Heising, W. and Gemünden, H.G., 2015. How ideation portfolio management
influences front‐end success. Journal of Product Innovation Management, 32(4), pp.539-555.
Krupa, M.B., 2016. Who's who in the Kenai River Fishery SES: A streamlined method for
stakeholder identification and investment analysis. Marine Policy, 71, pp.194-200.
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Parnell, G.S., Butler III, R.E., Wichmann, S.J., Tedeschi, M. and Merritt, D., 2015. Air Force
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Ruan, T., Xue, L., Wang, H., Hu, F., Zhao, L. and Ding, J., 2016, October. Building and
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p.S98.

INVESTMENT ANALYSIS AND PORTFOLIO MANAGEMENT
Williams, E.E. and Dobelman, J.A., 2017. Financial statement analysis. World Scientific
Book Chapters, pp.109-169.

INVESTMENT ANALYSIS AND PORTFOLIO MANAGEMENT
Appendix:
Portfoli
o Return SD Beta Sharpe ratio Treynor ratio
P1 1% 1.00% 2.80% 0.216851 (0.18) (0.02)
P2 2% 1.98% 4.03% 0.321364 0.12 0.01
P3 3% 2.96% 5.27% 0.424858 0.28 0.03
P4 4% 3.92% 6.50% 0.527351 0.37 0.05
P5 5% 4.88% 7.73% 0.628864 0.44 0.05
P6 6% 5.83% 8.95% 0.729415 0.48 0.06
P7 7% 6.77% 10.16% 0.829022 0.52 0.06
P8 8% 7.70% 11.36% 0.927701 0.55 0.07
P9 9% 8.62% 12.65% 0.990485 0.56 0.07
P10 10% 9.53% 14.25% 1.102993 0.56 0.07
P11 11% 10.44% 15.89% 1.232097 0.56 0.07
P12 12% 11.33% 17.52% 1.360043 0.56 0.07
P13 13% 12.22% 19.15% 1.486852 0.56 0.07
P14 14% 13.10% 20.76% 1.612543 0.56 0.07
P15 15% 13.98% 22.36% 1.737138 0.56 0.07
P16 16% 14.84% 23.94% 1.860653 0.56 0.07
P17 17% 15.70% 25.52% 1.983108 0.56 0.07
P18 18% 16.55% 27.98% 2.174156 0.54 0.07
P19 20% 18.23% 32.96% 2.560169 0.51 0.07
0.00% 5.00% 10.00% 15.00% 20.00% 25.00% 30.00% 35.00%
0.00%
2.00%
4.00%
6.00%
8.00%
10.00%
12.00%
14.00%
16.00%
18.00%
20.00%
Effecient Frontier
XDAX GR Equity
Mean 0.000107234

INVESTMENT ANALYSIS AND PORTFOLIO MANAGEMENT
Standard Error 0.000333122
Median 0.000312241
Mode 0
Standard Deviation 0.010412402
Sample Variance 0.000108418
Kurtosis 10.49549887
Skewness -1.199507378
Range 0.14769451
Minimum -0.101384085
Maximum 0.046310426
Sum 0.104767557
Count 977
XIC CN Equity
Mean 0.000194622
Standard Error 0.000282023
Median 6.5283E-06
Mode 0
Standard Deviation 0.008815184
Sample Variance 7.77075E-05
Kurtosis 1.954012687
Skewness 0.073229665
Range 0.072854546
Minimum -0.033150458
Maximum 0.039704089
Sum 0.190145912
Count 977
SSO US Equity
Mean 0.000625046
Standard Error 0.000516466
Median 0.000579398
Mode 0
Standard Deviation 0.016143173
Sample Variance 0.000260602
Kurtosis 4.664744598
Skewness -0.647796309
Range 0.17826191
Minimum -0.084742401
Maximum 0.09351951
Sum 0.61066958
Count 977
SH US Equity

INVESTMENT ANALYSIS AND PORTFOLIO MANAGEMENT
Mean -0.000429619
Standard Error 0.000258257
Median -0.000303076
Mode 0
Standard Deviation 0.008072326
Sample Variance 6.51625E-05
Kurtosis 4.869982807
Skewness 0.380769765
Range 0.093056591
Minimum -0.052877099
Maximum 0.040179492
Sum -0.419737995
Count 977
CBDAX GR Equity
Mean 4.92531E-05
Standard Error 0.000338651
Median 0.000408873
Mode 0
Standard Deviation 0.010585225
Sample Variance 0.000112047
Kurtosis 9.917267651
Skewness -1.166113244
Range 0.147346402
Minimum -0.101003999
Maximum 0.046342402
Sum 0.048120236
Count 977
SPXL US Equity
Mean 0.000797538
Standard Error 0.000776662
Median 0.000911439
Mode 0
Standard Deviation 0.02427611
Sample Variance 0.00058933
Kurtosis 4.671575556
Skewness -0.720855113
Range 0.266377964
Minimum -0.131077984
Maximum 0.13529998
Sum 0.779194921
Count 977

INVESTMENT ANALYSIS AND PORTFOLIO MANAGEMENT
LYXDAX GR
Equity
Mean 0.000108887
Standard Error 0.000333585
Median 0.000337318
Mode 0
Standard Deviation 0.010426867
Sample Variance 0.00010872
Kurtosis 8.911548513
Skewness -1.07908782
Range 0.142983547
Minimum -0.096752574
Maximum 0.046230972
Sum 0.106383072
Count 977
AUST AU Equity
Mean 9.87153E-05
Standard Error 0.000265108
Median 0
Mode 0
Standard Deviation 0.00828649
Sample Variance 6.86659E-05
Kurtosis 3.506941048
Skewness -0.337529947
Range 0.095233137
Minimum -0.05286764
Maximum 0.042365497
Sum 0.096444861
Count 977
SPY US Equity
Mean 0.000350112
Standard Error 0.000261606
Median 0.000377003
Mode 0
Standard Deviation 0.00817703
Sample Variance 6.68638E-05
Kurtosis 4.607163155
Skewness -0.553553154
Range 0.092012131
Minimum -0.042722207

INVESTMENT ANALYSIS AND PORTFOLIO MANAGEMENT
Maximum 0.049289923
Sum 0.342059645
Count 977