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Portfolio Management Investing Wisely Assignment Sample

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Intoduction : Portfolio Management Investing-Wisely

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Task 1: Recommendation for portfolio selection 

The measurement of portfolio performance is one of the major challenges for investors who intended to invest in a specific stock. In this situation, they need to evaluate the different investment variables based on which one can measure the return of the portfolio successfully. Hence, by measuring the return of the portfolio one can understand the market performance of the portfolios easily. The study consists of five different portfolios that show five different values of variables in the pre and post-covid situation, which is depicted below:

The above figure depicts that portfolio 1 and 2 has the highest mean and risk premium which are 0.0005 and 0.0005 and the lowest SD which is 0.0090 and 0.0089 in the pre-covid period. However, in the post-covid-period, the mean value of portfolio 2 was higher i.e., 0.0003 and the SD was also higher i.e0.01649. Further, irrespective of the above figures, it can be said that portfolio 3 has the higher performance in pre and post covid situations and it has the mean value of 0.0005 and 0.0003 in pre and post-covid situations (Platanakis and Urquhart, 2019, p. 7). However, portfolio 3 has a lower SD in both the periods such as 0.0089 and 0.1644, which means the variation in the portfolio has been low. Due to this reason, it has been recommended that the investors should choose portfolio 3 as their first preference out of the five portfolios. This is because portfolio 3 is associated with a lower variation in the market which means the risk is lower in the stock and the return is higher as well.

Task 2: Preparation of research report 

A. Classification of Reuters report 

Systematic risk can be defined as the risk specific to a broader market whereas, systematic risk is the risk specific to a company. Hence, the above graph depicts the closing prices of the S&P 500 index and AstraZeneca for measuring systematic and unsystematic risks. The above graph showed a continuous increase in the closing prices of the share of the S&P 500, which might create an unsystematic risk in the vaccine trial (Liang et al. 2018, p. 4). However, the closing price of AstraZeneca was inconsistent, which might not harm their vaccine trial on 7th May 2021. Hence, it can be said that unsystematic risk could be incurred due to higher closing prices of the S&P 500 in comparison to AstraZeneca.

B. Construction of index model 

Systematic Risk Exposure (Index Model)

Ri (t)

0.2822

ai

0.0121

Rm (t)

0.00217

ei (t)

0.26881

Bi

0.5719

Table 1: Index Model

(Source: Self-made) 

The above table shows the systematic risk exposure of AstraZeneca by considering the daily return, beta, and return of the S&P 500 index. The standard value for measuring the systematic risk exposure is 0.50 and increases with the value considered as higher risk and decreases with the value considered as lower risk. Therefore, the index model of AstraZeneca is 0.2822, which is lower than 0.50 and it is one of the positive indications for the company as they possessed lower systematic risk in their business.

C. Comment on risk exposure 

Total Risk Exposure (Index Model)

Ri (t)

0.3410

ai

0.0121

Rm (t)

0.00217

ei (t)

0.328947

Bi

0.0004

Table 2: Index Model

(Source: Self-made) 

The above table depicts the total risk exposure of AstraZeneca Plc by using the daily returns and beta of the index model. It has been stated in the above discussion that the standard value for measuring the performance and risk of the index model is 0.50. Therefore, AstraZeneca has attained a total risk exposure of 0.3410, which is lower than 0.50, which means the risk exposure is lower for the company and the return is higher as well. 

Task 3: Comment on the alpha of five stocks 

The alpha of a stock can be defined as the excess return generated by the stocks after the adjustments of volatility and fluctuation of the market (Gao et al. 2020, p. 20). Therefore, five stocks and their return have been provided in the study. The stocks include “APA.AX, BSL.AX, CBA.AX, RIO.AX, and WOW.AX”. Moreover, the alpha value of all the stocks has been estimated below for measuring the performance of the five stocks: 

Calculation of Alpha

Particulars

APA.AX

BSL.AX

CBA.AX

RIO.AX

WOW.AX

R

0.4323

0.5595

0.8132

0.5757

0.5054

Rf

0.1869

0.3131

0.6613

0.3314

0.2554

beta

0.6489

1.38

0.023

0.9424

0.6314

(Rm-Rf)

0.9054

0.4004

0.5471

0.2118

0.3089

Alpha

-34.21%

-30.62%

13.93%

4.47%

5.50%

 Table 3: Alpha

(Source: Self-made) 

The above table shows the alpha values of the five stocks some are positive and some are negative. Based on the estimation, it can be said that having positive and higher alpha depicts a higher yield for the investors and this is the selection of CBA.AX (13.93%) should be selected to gain a higher return from the stock.

Task 4: Evaluation of performance 

Calculation of Performance ratios

Particulars

Portfolio 1

Portfolio 2

Portfolio 3

Portfolio 4

Sharpe ratio

0.0296

0.0299

0.0360

0.0278

Treynor measure

0.0126

0.0126

0.0140

0.0221

Jensen's measure

0.0130

0.0129

0.0133

0.0105

Information ratio

0.75

0.75

1.00

0.67

Table 4: Performance ratios

(Source: Self-made) 

The above table associated the performance ratios of four different portfolios for the measurement of the performance of the portfolios in the market. The main reason behind conducting the above ratios is it shows the actual performance of the company in the market by considering all the internal and external variables of the market (Danesh et al. 2018, p. 3). From the above table, it can be said that the returns of portfolio 3 are much higher in comparison to the other portfolios since it has higher ratios. The Sharpe ratio, Treynor measure, Jensen’s measure, and Information ratio of portfolio 3 is 0.0360, 0.0140, 0.0133, and 100. This has shown that the performance of portfolio three is much more impressive in comparison to other stocks, which is the best performing manager for portfolio 3

References

Danesh, D., Ryan, M.J. and Abbasi, A., 2018. Multi-criteria decision-making methods for project portfolio management: a literature review. International Journal of Management and Decision Making17(1), pp.75-94.

Liang, Z., Chen, H., Zhu, J., Jiang, K. and Li, Y., 2018. Adversarial deep reinforcement learning in portfolio management. arXiv preprint arXiv:1808.09940.

Platanakis, E. and Urquhart, A., 2019. Portfolio management with cryptocurrencies: The role of estimation risk. Economics Letters177, pp.76-80.

Ye, Y., Pei, H., Wang, B., Chen, P.Y., Zhu, Y., Xiao, J. and Li, B., 2020, April. Reinforcement-learning based portfolio management with augmented asset movement prediction states. In Proceedings of the AAAI Conference on Artificial Intelligence (Vol. 34, No. 01, pp. 1112-1119).

Gao, Z., Gao, Y., Hu, Y., Jiang, Z. and Su, J., 2020, May. Application of deep q-network in portfolio management. In 2020 5th International Conference on Big Data Analytics (ICBDA) (pp. 268-275).

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