Determining the optimal weight of the portfolio of bank assets using value at risk (case study of Bank D)
Subject Areas :
shahahram kordi
1
,
فرزانه خلیلی
2
,
مهدی صادقی
3
1 - no
2 -
3 - دانشیار دانشگاه امام صادق
Keywords: Value at Risk (VaR), asset portfolio optimization, Ruiker Markowitz, Bank Day,
Abstract :
In this research, Bank D's asset portfolio was optimized using Ruiker-Marquitzo's value at risk and the results were compared by calculating the variance as a deviation from the average. Three shares of Damavand Electricity Company, Bo Ali and Day Insurance Company were selected as the three companies with the largest share in Bank Day's investment portfolio and prices in the Tehran Stock Exchange Hall, and the data of the period from April 1401 to the end of March 1402 was selected as a sample. . The results of this study showed that at different levels of risk and return, the optimal portfolio of Bank D will be different, and depending on which level of risk and return Bank D accepts, it will have a different optimal portfolio. On the other hand, based on the chosen portfolio for Bank D, this company is not on the efficient frontier, and therefore it can change its portfolio in two ways, increasing the yield with the same level of risk and decreasing the risk with the same level of yield, and move towards the optimal portfolio. Slow
1) Asgharpour, Hossein; Rezazadeh, Ali. (2014). Determining the optimal stock portfolio using the value-at-risk method. Applied Economics Theories, 2(4), 118-93.( Persian)
2) Taftani Eskoui, Seyyed Ali; Hadipour, Hassan; Abaghri, Hassan. (2018). Optimal stock portfolio using the value-at-risk criterion: Evidence from Tehran Stock Exchange. Empirical Studies of Financial Accounting, 16 (61), 157-178. ( Persian)
3) Khodamoradi, Saeed; Turabi Guderzi, Mohammad; Rai Ezzabadi, Mohammad Ibrahim. (2012). Mathematical two-stage approach in stock portfolio optimization. Financial Engineering and Securities Management (Portfolio Management), 4 (14), 0-0. SID. https://sid.ir/paper/405916/fa. ( Persian)
4) Kandahari, Mehsa, Shamshiri, Azima, and Fathi, Saeed. (2016). Stock portfolio optimization based on non-parametric estimation methods. Production and Operations Management, 8(1 (serial 14)), 175-184. SID. https://sid.ir/paper/217582/fa. ( Persian)
5) Ahmadi-Javid, A., & Fallah-Tafti, M. (2019). Portfolio optimization with entropic value-at-risk. European Journal of Operational Research, 279(1), 225-241.
6) Elton E., Gruber. M. (1997). Modern portfolio theory, 1950 to date. Journal of Banking & Finance, 21 (11-12), 1743-1759.
7) Enkhsaikhan, B., & Jo, O. (2024). Risk-averse reinforcement learning for portfolio optimization. ICT Express.
4) Ghahtarani, A., & Najafi, A. A. (2018). ROBUST OPTIMIZATION IN PORTFOLIO SELECTION BY 5) m-MAD MODEL APPROACH. Economic Computation & Economic Cybernetics Studies & Research, 52(1).
5) Lim, A. E., Shanthikumar, J. G., & Vahn, G. Y. (2011). Conditional value-at-risk in portfolio optimization: Coherent but fragile. Operations Research Letters, 39(3), 163-171.
6) Mendonça, G. H., Ferreira, F. G., Cardoso, R. T., & Martins, F. V. (2020). Multi-attribute decision making applied to financial portfolio optimization problem. Expert Systems with Applications, 158, 113527.
7) Narang, M., Joshi, M. C., Bisht, K., & Pal, A. (2022). Stock portfolio selection using a new decision-making approach based on the integration of fuzzy CoCoSo with Heronian mean operator. Decision Making: Applications in Management and Engineering, 5(1), 90-112.
8) Nasini, S., Labbé, M., & Brotcorne, L. (2022). Multi-market portfolio optimization with conditional value at ris\k. European Journal of Operational Research, 300(1), 350-365.
9) Qian, Y., & Wang, J. (2024). Multi-period portfolio optimization: A parallel NSGA-III algorithm with real-world constraints. Finance Research Letters, 60, 104868.
