Portfolio Optimization
Investment options
Firstly, it is important to choose 12 investment options as per the requirements of the document to complete the exercise here. The table in the next slide contains 12 companies in which investment can be made by the investors. In order to achieve the objective of maximizing the rate of return on investment it is important to select suitable stocks out of the 12 mentioned stocks in the next slide (Nawrocka, 2018).
12 investment options
Continued…
Criterions for selection of above stock
- The stocks have been selected from wide range of sectors.
- Banking, mining and materials, pharmaceuticals, technology and media are the sectors from where the companies have been chosen to fulfill the requirements of the exercise (Chourmouziadis & Chatzoglou, 2016).
- The reason to select companies from diverse sectors is to ensure that the representation is of whole market and not limited to a particular sector.
Data collection
- Data of these stocks have been collected from yahoo finance Australia.
- The data about the stock movement from October 2014 to October 2018 have been collected (Chandra, 2017).
- In order to determine the risk class of these stocks the mean return and standard deviation of these stocks have been calculated.
- The mean and standard deviations have been provided in the next slide (Kumar, 2014).
Mean and standard deviation of return
Continued…
Most risky stocks (R1)
The following two are the most risky companies with most standard deviation suggesting that the expected deviation in the return is highest in these stocks (Golub, Greenberg & Ratcliffe, 2018).
v Apple Inc.: Apple Inc. has a standard deviation of 9.61
vFacebook has a standard deviation of 8.29
Second category of risk (R2)
- In terms of most risky stocks R2 are the stocks with very high risk, i.e. ranked immediately after the most riskiest companies.
R3 stocks
- These are stocks with relatively less risk (Guerard Jr, Markowitz & Xu, 2015).
R3 stocks are mentioned in the table below:
Least risky stocks (R4)
- These are stocks with least risk as these stock have shown very less deviation from mean return (Kevin, 2015).
LP model
Optimum portfolio
Ranking criterions
- On the basis of premium for risk the 12 stocks have been assessed.
- Thus, the mean return has been divided by the standard deviation to calculate the risk premium of different stocks (Liang, Jiang, Chen, Zhu & Li, 2018).
- The stocks which shall provide highest premium for return shall be chosen over other stock in the order of preference for investment (Danesh, Ryan & Abbasi, 2017).
- The next slide shows the calculation of risk premium of 12 stocks (Aouni, Colapinto & La Torre, 2014).
The investment options ranking
ILP model
Portfolio optimization
NLP model
Strategy in NLP model
Return and standard deviation
Conclusion: Portfolio optimization
- On the basis of return and standard deviation the following stocks are recommended:
- Apple Inc.
- Facebook.
- Vanguard Properties.
- Starphramacy (Curci, Mula, Díaz-Madroñero & Dassisti, (2019).
References
- Aouni, B., Colapinto, C., & La Torre, D. (2014). Financial portfolio management through the goal programming model: Current state-of-the-art. European Journal of Operational Research, 234(2), 536-545.
- Chandra, P. (2017). Investment analysis and portfolio management. McGraw-Hill Education.
- Chourmouziadis, K., & Chatzoglou, P. D. (2016). An intelligent short term stock trading fuzzy system for assisting investors in portfolio management. Expert Systems with Applications, 43, 298-311.
- Curci, V., Mula, J., Díaz-Madroñero, M., & Dassisti, M. (2019). An Overview of Supply Chain Planning That Integrates Financial Issues. In Engineering Digital Transformation(pp. 305-313). Springer, Cham.
- Danesh, D., Ryan, M. J., & Abbasi, A. (2017). A systematic comparison of multi-criteria decision making methods for the improvement of project portfolio management in complex organisations. International Journal of Management and Decision Making, 16(3), 280-320.
- Golub, B., Greenberg, D., & Ratcliffe, R. (2018). Market-Driven Scenarios: An Approach for Plausible Scenario Construction. The Journal of Portfolio Management, jpm-2018.
- Continued…
- Guerard Jr, J. B., Markowitz, H., & Xu, G. (2015). Earnings forecasting in a global stock selection model and efficient portfolio construction and management. International Journal of Forecasting, 31(2), 550-560. Guerard Jr, J. B., Markowitz, H., & Xu, G. (2015). Earnings forecasting in a global stock selection model and efficient portfolio construction and management. International Journal of Forecasting, 31(2), 550-560.
- Kevin, S. (2015). Security analysis and portfolio management. PHI Learning Pvt. Ltd..
- Kumar, D. (2014). Return and volatility transmission between gold and stock sectors: Application of portfolio management and hedging effectiveness. IIMB Management Review, 26(1), 5-16.
- Liang, Z., Jiang, K., Chen, H., Zhu, J., & Li, Y. (2018). Deep Reinforcement Learning in Portfolio Management. arXiv preprint arXiv:1808.09940.
- Nawrocka, D. (2018). Machine learning for trading and portfolio management using Python.
