مدیریت پرتفوی متشکل از انواع دارایی ریسکی و درآمد ثابت با مدل‌های مبتنی بر ارزش درمعرض ریسک در بازار ایران

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشجوی کارشناسی ارشد سیستم‌های مالی، گروه مهندسی صنایع، دانشکده فنی مهندسی، دانشگاه میبد، میبد، ایران

2 استادیار، گروه مهندسی صنایع، دانشکده فنی مهندسی، دانشگاه میبد، میبد، ایران

3 استادیار، دانشکده مهندسی صنایع و سیستم‌های مدیریت، دانشگاه صنعتی امیرکبیر، تهران، ایران

چکیده

در این پژوهش با هدف ارائه بهترین رویکرد جهت بهینه ­سازی سبد متشکل از پنج کلاس دارایی شامل؛ ارزهای دیجیتال، ارزهای خارجی، طلا، سهام و صندوق­های سرمایه ­گذاری مشترک و در سه گروه؛ صندوق­های سرمایه­گذاری با درآمدثابت، صندوق­های سرمایه­ گذاری سهام و صندوق­های سرمایه­ گذاری مختلط، به توسعه مدل­های میانگین-ارزش در معرض ریسک و میانگین-ارزش در معرض ریسک شرطی و حل آن­ها با الگوریتم کلونی مصنوعی زنبور عسل پرداخته شده­ است. عملکرد مدل­های توسعه‌یافته مبتنی بر ارزش در معرض ریسک، با مدل­های میانگین-واریانس، میانگین-نیم­واریانس و میانگین-قدرمطلق انحرافات مقایسه شده ­است. همچنین، کارایی مدل­ها در حضور محدودیت‌های حد بالا و پایین دارایی، حداقل و حداکثر وزن گروه دارایی و ترکیب دو محدودیت ارزیابی شده ­است. بازه زمانی مورد بررسی این پژوهش از ابتدای مردادماه سال1394 تا انتهای آذر1400 است. نتایج بدست­ آمده از این مدل­ها در بخش درون‌نمونه و برون‌نمونه حاکی از آن است که سنجه ارزش در معرض ریسک شرطی چه در حضور محدودیت­ها و چه بدون حضور آن­ها، نسبت به سایر سنجه ­های ریسک عملکرد بهتری در مدیریت پرتفوی متشکل از انواع دارایی دارد. همچنین، در بهینه ­سازی سبد چندنوع دارایی، کارایی و برتری الگوریتم کلونی مصنوعی زنبور عسل در مقایسه با دو الگوریتم رقابت استعماری و ازدحام ذرات براساس نسبت­های شارپ، شارپ شرطی و بازده به ریسک تأیید شد.

کلیدواژه‌ها


عنوان مقاله [English]

Multi-Asset Portfolio Management Including Fixed Income Securities by Value at Risk based Models in Iran Market

نویسندگان [English]

  • Marzieh Kazemi-Rashnani 1
  • Somayeh Mousavi 2
  • Ehsan Hajizadeh 3
1 Department of Industrial Engineering, Faculty of Engineering, Meybod University, Meybod, Iran.
2 Department of Industrial Engineering, Faculty of Engineering, Meybod University, Meybod, Iran.
3 Assistant Professor, Faculty of Industrial Engineering and Management Systems, Amirkabir University of Technology, Tehran, Iran
چکیده [English]

This paper aims to provide the best approach to optimize the multi-asset portfolio of five asset classes including cryptocurrencies, foreign currencies, gold, stock and investment funds in three groups of fixed income investment funds, stock investment funds and Mutual investment funds. Purposely, the mean-value at risk and mean-conditional value at risk models have been developed and solved using the artificial bee colony algorithm. The performance of the value at risk based models is compared with the mean-variance, mean-semi variance and mean–absolute deviation models. Also, the profitability of the models is evaluated in the presence of three real world constrains, i.e. quantity constrains, class constrains and the both. Our investigation time period is from August 2015 to December 2020. The in-sample and out-of-sample results showed that the conditional value at risk model outperforms the other models, whether in the presence of constraints or not. Also, the artificial bee colony algorithm was superior to the imperialist competitive and particle swarm optimization algorithms in multi asset portfolio management, based on Sharpe, conditional Sharpe and return on risk ratios.

کلیدواژه‌ها [English]

  • Multi-Asset Portfolio
  • Conditional Value at Risk
  • Cryptocurrencies
  • Fixed Income Securities
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