Design and optimization of distribution stable stock portfolio based on Kalmar and Rachoff ratios
Subject Areas : Journal of Capital Market Analysismona beyranvand 1 , Sayyed Mohammad Reza Davoodi 2 , Mohammadreza Sharifi-Ghazvini 3
1 - Department of Management, Dehaghan Branch, Islamic Azad University, Dehaghan, Iran
2 - Associate Professor, Department of Management, Dehaghan Branch, Islamic Azad University , Dehaghan, Iran
3 - Department of Industrial Engineering,Dehaghan Branch, Islamic Azad University, Dehaghan, Iran
Keywords: : Kalmar's ratio, Rachev's ratio, distributed stable basket, particle aggregation algorithm.,
Abstract :
The research strategy to stabilize the return distribution parameter is to consider all the returns that are located in a neighborhood of the empirical distribution of the portfolio, which has been used to determine such distributions using Wasserstein's metric criteria and K-L divergence. A sample portfolio of the research consists of 8 indices or industries from the Tehran Stock Exchange with the largest trading volume in the time period from the beginning of 2011 to the end of 2018 and in the weekly time horizon. The test data has been divided into 5 periods, and to evaluate the results of the stable distribution basket compared to the basket without this property, the result of dividing the average ratios of Kalmar and Rachev in the 5 periods by their standard deviation has been used. The results of the optimization with the help of particle aggregation algorithm show that the distribution stable basket of squid improves the mentioned ratio by 1.27 and in addition, the minimum ratio of squid in 5 periods in the distribution stable basket is higher than the basket without this feature. The stable distribution portfolio of Rachof improves this ratio by 1.40, and in addition, the minimum ratio of Rachof in 5 periods in the stable distribution portfolio is higher than the portfolio without this feature.
حمیدیه٬علیرضا؛ کاویانی,میثم؛اخگری٬بهاره. (۱۴۰۲). بهینهسازی استوار پرتفوی تحت معیار ارزش در معرض ریسک شرطی ـ فاصله ای (ICVaR) در بورس تهران. تحقیقات مالی, 25(3), 508-528.
حیدری، محمدسعید؛ ولیدی، جواد؛ ابراهیمی، سیدبابک. (1400). بهینهسازی سبدسهام مبتنی بر مدل برنامه ریزی امکانی استوار با استفاده از الگوریتمهای ژنتیک و جهش قورباغه مخلوط شده، مهندسی مالی و مدیریت اوراق بهادار،12(47)، 564-586.
شیرکوند، سعید؛ فدائی، حمیدرضا. (1401). بهینهسازی سبدسهام استوار با بهکارگیری مدلهای چند متغیره و امگا- ارزش در معرض ریسک شرطی بر پایه ملاک حداقل حداکثر پشیمانی. تحقیقات مالی. 24(1)، 17-1.
Du, N., Liu, Y., & Liu, Y. (2020). A new data-driven distributionally robust portfolio optimization method based on wasserstein ambiguity set. IEEE Access, 9, 3174-3194.
Hosseini-Nodeh, Z., Khanjani-Shiraz, R., & Pardalos, P. M. (2022). Distributionally robust portfolio optimization with second-order stochastic dominance based on wasserstein metric. Information Sciences, 613, 828-852.
Ji, R., Lejeune, M. A., & Fan, Z. (2022). Distributionally robust portfolio optimization with linearized STARR performance measure. Quantitative Finance, 22(1), 113-127.
Kobayashi, K., Takano, Y., & Nakata, K. (2023). Cardinality-constrained distributionally robust portfolio optimization. European Journal of Operational Research, 309(3), 1173-1182.
Li, J. Y. M. (2023). Wasserstein-Kelly Portfolios: A Robust Data-Driven Solution to Optimize Portfolio Growth. arXiv preprint arXiv:2302.13979.
Zhang, X. (2022). Distributional Robust Portfolio Construction based on Investor Aversion. arXiv preprint arXiv:2203.13999.