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Journal of Industrial and Systems Engineering، جلد ۱۶، شماره ۲، صفحات ۱۳۰-۱۵۳
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| عنوان فارسی |
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| چکیده فارسی مقاله |
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| کلیدواژه‌های فارسی مقاله |
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| عنوان انگلیسی |
Chance-constrained programming for Cryptocurrency portfolio optimization using Conditional Drawdown at Risk |
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| چکیده انگلیسی مقاله |
Portfolio optimization is a widely studied problem in financial engineering literature. Its objective is to effectively distribute capital among different assets to maximize returns and minimize the risk of losing capital. Although portfolio optimization has been extensively investigated, there has been limited focus on optimizing portfolios consisting of cryptocurrencies, which are rapidly growing and emerging markets. The cryptocurrency market has demonstrated significant growth over the past two decades, offering potential profits but also presenting heightened risks compared to traditional financial markets. This situation creates challenges in constructing portfolios, necessitating the development of new and improved risk management models for cryptocurrency funds. This paper utilizes a new risk measurement approach called Conditional Drawdown at Risk (CDaR) in constructing portfolios within high-risk financial markets. Traditionally, portfolio optimization has been approached under certain conditions, considering risk and profit as decision criteria. However, recent approaches have addressed uncertainty in the decision-making process. To contribute to the advancement of scientific knowledge in this field, this paper proposes a new mathematical formulation of CDaR based on a chance-constrained programming (CCP) approach for portfolio optimization. To demonstrate the effectiveness of the proposed model, a practical empirical case study is conducted using real-world market data from 10 months focused on cryptocurrencies. The results obtained from this model can provide valuable guidance in making investment decisions in high-risk financial markets. |
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| کلیدواژه‌های انگلیسی مقاله |
Portfolio selection,Conditional drawdown at risk,Stochastic programming,Chance constrained programming,Cryptocurrency |
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| نویسندگان مقاله |
Roghaye Zarezade |
MSc Student in Industrial Engineering, Faculty of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran
Rouzbeh Ghousi |
Iran University of Science and Technology
Emran Mohammadi |
iran university of science and technology
Hossein Ghanbari |
Department of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran
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| نشانی اینترنتی |
https://www.jise.ir/article_206753_1110612f76a2d536f0084cbf0260e826.pdf |
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| زبان مقاله منتشر شده |
en |
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