Determining the Optimal Portfolio by Systematic Risk Modeling: Selected Food Industry Companies of Tehran Stock Exchange

مجله اقتصاد و توسعه کشاورزی

Article 3, Volume 34, Issue 2 - Serial Number 48, July 2020, Pages 149-161   

Document Type: Research Article

DOI: 10.22067/jead2.v34i2.84194

Authors

F. Mojtahedi; S.M. Mojaverian; S.A. Hosseini Yekani^*

Department of Agricultural Economics, Sari Agricultural Sciences and Natural Resources University, Sari, Iran

Abstract

Introduction: stock market may play a significant role in financing food industries. Nowadays, people select an optimized portfolio with several shares instead of choosing only one in order to cope with the investment risk. For this, the systematic risk could be very important as the market is so fluctuating, especially in Iran. So in this paper, we enter a constraint for systematic risk that helps investors in making decision.
Materials and Methods: As we said, we want to enter systematic risk in the portfolio selection model. We use Extreme Downside Hedge (hereafter EDH) as the measure for the systematic risk of each company in the food industry. This measure relies on the argument that investors are able to hedge against extreme downside risk. The EDH can be estimated by regressing stock returns on a measure of market tail risk. We use Expected Tail Loss (ETL) to measure market tail risk. ETL is defined as the expected value of the loss given that the loss exceeds VaR. Then, the factor models are introduced to capture the systematic risk. In order to actively allocate the systematic risk, we use the definition of the marginal systematic risk introduced by Li et al (2018) to measure the systematic risk contribution of a risk contributor.  First, we choose some variables as factors that affect the return of each company. After that, we calculate the covariance between factors and then make an equation that shows the systematic risk for each company. We apply our methodology to the return time series of 11 companies and the index for the food industry, all listed on the Tehran Stock Exchange (TSE). The data covers the period from 2015 to 2019. Other variables include oil prices, gold prices and exchange rates extracted from the Economic and Financial Databank of Iran.
Results and Discussion: The results show the Behshahr Ind, Glucosan, Kalber, Margarin, Pars Mino, Pegah Fars and Salemin have positive EDH. This means for these companies the stock returns are affected by volatility of the market, in other words as the volatility increases, the stock returns decrease. It should be noted that the higher the EDH is, the greater the impact is. Also, Gorji Biscuit, Mahram Mfg, Minoo Co and Azar Pegah have negative EDH, indicating the reverse impactability of these companies' returns from market volatility. The higher the EDH, the lower the companies' volatility, also the higher the negative EDH, the higher the market volatility. After calculating the factor model and entering it in the portfolio model, we obtained the optimized result. According to the results, Azar Pegah and Pars Mino, with 86% and 12% have the highest percentage of the optimal portfolio, while Kalber, Pegah Fars and Salemin altogether have 2% of the portfolio, respectively. As the results show, the largest share belongs to the Azar Pegah Company, which is also according to the EDH of the company, in fact, the results show the company whose shares have the highest negative impact from the market has entered to the model. The presence of four other companies in the portfolio given the positive EDH is due to their high average return rather than other companies, since we consider the return as a constraint in the model because of its importance in decision making. It is also worth noting that, the two companies, kalber and behshahr Ind, with the highest positive EDH are not in the optimal portfolio. In order to investigate the effect of systematic risk the model was estimated without considering this constraint. The results show, without systematic risk constraint the optimal portfolio has shifted to companies with higher return and lower risk. Thus, the results of this study indicate that with systematic risk, based on expectations, portfolios will shift to companies with lower impactability from market volatility on the one hand and higher returns on the other.
Conclusion: Finally, the results of the study show, the systematic risk in the model shift the portfolio towards the stocks of companies that are less affected by market conditions. Therefore, given today's fluctuating conditions, it may be useful to apply a model that considers this part of the risk.  

Keywords

Factor model; Food industry companies; Stock exchange; Systematic risk

References

1- Abozari A., Shahiki Tash M.N., and Taleblo R. 2014. The Connection between Systematic Risk and Corporate Income Tax (A case study of the Tehran Stock Exchange). Journal of Economic Research 54(3): 101-132. (In Persian with English abstract)

2- Afshari H., and Ebrahimi Hosseinzadeh. 2011. Nanotechnology and Food Industry. Innovative Food Technologies 22: 43-58. (In Persian)

3- Claußen A., Löhr S., Rösch D. and Scheulec H. 2017. Valuation of systematic risk in the cross-section of credit default swap spreads. Journal of the Quarterly Review of Economics and Finance 64: 183-195.   

4- Davarzadeh M. 2007. Prediction of Pricing in Tehran Stock Exchange: An Approach to Technical Analysis. Master thesis, Faculty of Administrative and Economics, Isfahan University. (In Persian)

5- Economic and Financial Databank of Iran, 2019. https://databank.mefa.ir/

6- Fanai S.M. 2009. Knowledge of Exchange and Capital Market: History and Causes of Creation Stock Exchange. Exchange Monthly 86: 74-79. (In Persian)

7- Farahakhsh N., and Norouzi B. 2001. Analysis of Manufacturing and Export Capabilities of Iranian Food Industries. Trade Studies 5(19): 175-195. (In Persian)

8- Ghadiri Moghadam A., and Rafiy H. 2011. Study and Determination of Optimal Portfolio for Stock of Active Food Industrial Company in Tehran Stock. Journal of Economics and Agricultural Development 24(3): 304-309. (In Persian with English abstract)

9- Ghajar M., Hazer M., and Bendari M. 2015. Fundamentals of Investment Management. Hooshmand tadbir, Tehran. (In Persian)

10- Hajiha Z., and Safari F. 2018. The Examination of Relationship between Stock Systematic Risk and Skewness of Returns. Journal of Asset Management and Financing 6(20): 1-10. (In Persian with English abstract)

11- Harris R.D.F., Linh H.N., and Evarist S. 2019. Systematic Extreme Downside Risk. Journal of International Financial Markets, Institutions and Money. Accepted Manuscript.

12- Hosseini Kasgari S.H., Hosseini Yekani S.A., and Abedi S. 2018. Optimal Portfolio Selection of Shares of Food Industry Companies in Tehran Stock Exchange Using Combined Forecasting Method: An Application of Mean-Variance-Skewness Model. Agricultural Economics 4(11): 81-105. (In Persian with English abstract)

13- Kadan, O., Liu F., and Liu S. 2016. Generalized systematic risk. American Economic Journal: Microeconomics 8(2): 86–127.

14- Kavoosi Kalashami M., and Khaligh Khiavi P. 2018. The impact of surplus free cash flow on earnings management in food industry companies listed at the Tehran Stock Exchange: Journal of Agricultural Economics Research 10(40): 227-244. (In Persian with English abstract)

15- Kavoosi Kalashami M., and Khaligh Khiavi P. 2018. The Relationship among the Components of Working Capital Management with Liquidity and Profitability in Food Industry: Journal of Agricultural Economics Research 10(38): 105-120. (In Persian with English abstract)

16- Li Q., Bia Y., Yun X., and Zhang W. 2018. Portfolio selection with the effect of systematic risk diversification: formulation and accelerated gradient algorithm. Journal of Optimization Methods and Software, 34:612-633.

17- Markowitz H. 1952. Portfolio selection. Journal of Finance 7: 77-91.

18- Monjazb M.R. 2002. The relative advantage of Iran's food and garment industries. Journal of Economic Research 2(7): 95-124. (In Persian)

19- Oordt M., and C Zhou. 2016. Systematic Tail Risk. Journal of Financial and Quantitative Analysis 51: 685-705.

20- Piri P., Heidari H., and Rauof S. 2013. The Relationship between Systematic Risk and Economic Value Added in Iran. Journal of Economic Research and Policies 66(21): 169-186. (In Persian with English abstract)

21- Rizvi S.A.R and Arshad Sh. 2018. Understanding time-varying systematic risks in Islamic and conventional sectoral indices. Journal of Economic Modelling 70: 561-570.

22- Saeedi A., and Ramsheh M. 2011. The Systematic Risk Determinants in Tehran Stock Exchange. Journal of Financial Accounting Research 1(7): 125-142. (In Persian with English abstract)

23- Shahrabadi A. 2018. Management of Research, Development and Islamic Studies. Stock Exchange Organization. (In Persian)

24- Statistical Center of Iran, 2018. https://www.amar.org.ir/.

25- Taghian Dinani Z., and Farid D. 2017. The Relationship between Excess Return of the Momentum Strategy and Systematic Risk in Tehran Stock Exchange. Financial Management Perspective 16:9-30. (In Persian with English abstract)

26- Tzang S.W., Wang C.W., and Yu M.T. 2016. Systematic Risk and Volatility Skew. Journal of International Review of Economics & Finance 43: 72-87.     

27- Zahrabi Mazraeshahi A.H. 1999. Investigating the Relationship between the Systematic Risk of Operating Cash Flows and Stock Returns of Companies Listed in Tehran Stock Exchange. Master thesis, Tehran University. (In Persian)

28- Vakilian aghouie M., Salehi M., and Nasserzadeh F. 2017. The impact of product market competition on earnings quality in Agriculture and food industry companies Tehran Stock Exchange. Iranian Association of Agricultural Economics 10(4): 55-79. (In Persian with English abstract)