مقایسه کارایی پرتفوی‌های بهینه متشکل از رمزارزها مبتنی بر سنجه‌های ریسک نامطلوب: تجزیه و تحلیلی بر سنجه‌های ریسک نامطلوب مبتنی بر صدک
محورهای موضوعی : فصلنامه تحلیل بازار سرمایه
مصطفی شبانی
1
(کارشناسی ارشد مهندسی صنایع، دانشکده مهندسی صنایع، دانشگاه علم و صنعت ایران، تهران، ایران)
حسین قنبری
2
(دانشجوی دکتری مهندسی صنایع، دانشکده مهندسی صنایع، دانشگاه علم و صنعت ایران، تهران، ایران)
عمران محمدی
3
(دانشکده مهندسی صنایع، دانشگاه علم و صنعت ایران، تهران، ایران)
سید علی موسوی لولتی
4
(دانشجوی کارشناسی ارشد مهندسی صنایع، گرایش مهندسی مالی، گروه مهندسی صنایع، واحد تهران، دانشگاه علم و صنعت ایران، تهران، ایران.)
کلید واژه: بهینه‌سازی سبد سرمایه‌گذاری, سنجه‌های ریسک نامطلوب, ارزش در معرض خطر مشروط, افت سرمایه در معرض خطر مشروط,
چکیده مقاله :
بازار رمزارزها به‌عنوان یکی از بازارهای نوظهور و در حال رشد تمرکز زیادی را در سال‌های اخیر به دلیل پتانسیل بالای سوددهی به خود کسب نموده است. این بازار شاهد رشد خارق‌العاده‌ای در سال‌های اخیر بوده؛ اما درعین‌حال سرمایه‌گذاری در آن با ریسک بسیار بالایی همراه می‌باشد. به همین منظور، اهمیت انتخاب یک استراتژی و معیار مناسب جهت سرمایه‌گذاری و سنجش ریسک در بازار رمزارزها امری بسیار حیاتی است. در میان سنجه‌های مختلف ریسک، سنجه‌های مبتنی بر صدک به دلیل توانایی بالقوه‌ای که در شناسایی دقیق ریسک‌های نامطلوب دارند، ابزاری بسیار کاربردی می‌باشند. در همین راستا، هم سرمایه‌گذاران و هم پژوهشگران تمایل زیادی به به‌کارگیری این دسته از سنجه‌های ریسک دارند. در همین راستا این پژوهش به بررسی و مقایسه کارایی سبدهای متشکل از رمزارزها مبتنی بر سنجه‌های ارزش در معرض خطر مشروط و افت سرمایه در معرض خطر مشروط به‌عنوان دو تا از مهم‌ترین سنجه‌های ریسک مبتنی بر صدک می‌پردازد. این مقایسه نه‌تنها به سرمایه‌گذاران کمک می‌کند تا با اطلاعات دقیق و تصمیم‌گیری آگاهانه، سبد سرمایه‌گذاری متشکل از رمزارزهای خود را به شیوه‌ای مؤثر مدیریت کنند، بلکه به تعمیق در درک این سنجه‌های ریسک و کاربرد آن‌ها در سایر تصمیم‌گیری‌های سرمایه‌گذاری نیز کمک می‌نماید. در جهت افزایش کاربرد این مدل‌ها در محیط‌های واقعی، محدودیت‌های عملیاتی نیز در طراحی آن‌ها لحاظ شده‌اند. نتایج این تحقیق نشان می‌دهد که مدل ارزش در معرض خطر مشروط، نتایج بهتری ارائه می‌کند و استفاده از آن به‌عنوان معیار ترجیحی، سرمایه‌گذاران را قادر می‌سازد تا تصمیمات آگاهانه‌تر و مستند به شواهد را در
In the realm of burgeoning financial landscapes, the cryptocurrency market has garnered substantial attention owing to its pronounced profit potential. Despite witnessing remarkable expansion in recent years, investing in this market is concurrently entwined with heightened risk levels. Consequently, the imperative of selecting a judicious strategy and criteria for investment and risk assessment within the cryptocurrency market cannot be overstated. Among diverse risk measures, Quantile Based Risk Measures emerge as pivotal tools due to their intrinsic capacity to precisely discern adverse risks. Consequently, both investors and scholars exhibit a keen inclination towards leveraging this category of risk measures. This research delves into the scrutiny and juxtaposition of portfolio efficiency comprising cryptocurrencies, employing Conditional value-at-risk and conditional dropdown value at risk as two paramount risk measures based on percentiles. Such an examination not only facilitates investors in adeptly steering their cryptocurrency investment portfolios through well-informed decision-making but also contributes to an enhanced comprehension of these risk measures and their potential application in diverse investment contexts. To bolster the practical utility of these models in authentic settings, operational constraints have been deliberately incorporated into their design. The research outcomes underscore that the conditional value-at-risk model yields superior performance. Adopting it as a preferred criterion empowers investors to make decisions imbued with greater discernment and evidence-based rationale in managing their investment portfolios. These findings not only deepen the understanding of these risk criteria and their applicability in investment decisions but also furnish investors with insights essential for making judicious and optimal
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