سنجش ارزش در معرض ریسک شرطی با استفاده از ترکیب مدل FIGARCH و نظریه ارزش فرین

نوع مقاله : مقاله پژوهشی

نویسندگان

1 استادیار دکتری مدیریت مالی، دانشگاه تهران، تهران، ایران

2 استاد دانشگاه تهران، دکتری مدیریت مالی، تهران، ایران

3 استادیار گروه سیستم‌های اقتصادی و اجتماعی دانشگاه علم و صنعت ایران، تهران، ایران

4 دانشجوی دکتری مدیریت مالی دانشگاه تهران، تهران، ایران (نویسنده مسئول)

چکیده

تلاش در جهت شناسایی مدل مناسب و بالا بردن دقت اندازه‏گیری با استفاده از سنجه ارزش در معرض ریسک از اهمیت ویژه ای برخوردار است. ارزش در معرض ریسک شرطی (CVaR) با نداشتن برخی نواقص ارزش در معرض ریسک، سنجه قابل اعتماد‏تری می‏باشد. در این پژوهش با مطالعه در خصوص ویژگی‏های داده‏های شاخص کل بورس اوراق بهادار تهران وکاربرد مدل FIGARCH-EVT در محاسبه ارزش در معرض ریسک شرطی، تصریح دقیق‏تری حاصل شده است. ابتدا مدل ترکیبی GARCH-EVT پیاده‏سازی شد و با توسعه آن، به مدل FIGARCH-EVT رسیدیم که خاصیت خوشه‏ای بودن، پویا بودن و حافظه بلندمدت را در مدل‏سازی لحاظ نموده است. استفاده از مدل FIGARCH برای داده‏های بازده لگاریتمی شاخص کل، موجب لحاظ‏کردن خواص فوق در مدل‏سازی خواهد شد. بعلاوه، خاصیت دنباله پهن بودن داده‏های بازده شاخص با استفاده از تئوری مقدار فرین (EVT) برای پسماندهای مدل FIGARCH بکار برده می‏شود. برای مقایسه نتایج، مدل‏های NORMAL-GARCH و t-Student-GARCH، شبیه‏سازی تاریخی و GARCH-EVT نیز برای داده‏ها بازده شاخص بکار برده شده است. نتایج حاصل از مدل‏‏ها با استفاده از آزمون‏های پس‌آزمون مورد بررسی و مقایسه قرار گرفته‏اند. نتایج حاصل از این پژوهش نشان می‏دهد که توزیع داده‏ها بازدهی شاخص نامتقارن دارای چولگی بوده و از توزیع نرمال تبعیت نمی‏کند. بر اساس چهار آزمون جزء اخلال مازاد استاندارد شده، فرآیند نقض تجمعی، پس آزمایی ریزش مورد انتظار و تابع زیان لوپز مدل FIGARCH-EVT نسبت به سایر مدل‏ها از دقت بالاتری برخوردار می‏باشد.

کلیدواژه‌ها

عنوان مقاله [English]

Modeling volatility and conditional VaR measure using GARCH models and theoretical EVT in Tehran Stock Exchange

نویسندگان [English]

  • Saeed Fallahpoor 1
  • Reza Raee 2
  • Saeed Mirzamohammadi 3
  • seyed mohammad hasheminejad 4
1 professor of Tehran University, financial management Ph.D
2 professor of Tehran University, financial management Ph.D
3 Assistant professor of Iran University of Science and Technology, Economic Ph.D
4 Ph.D student of financial management at University of Tehran kish, International Campus,
چکیده [English]

Trying to identify an appropriate model to enhance measurement accuracy by using value at risk measures is of particular importance. Conditional Value at Risk (CVaR) with having some of the shortcomings of VaR, is a more reliable measure. In this study, the characteristics of the Tehran Stock Exchange index data usage FIGARCH-EVT model to calculate value at risk if states have been more accurate. GARCH-EVT hybrid implementation model and its development, FIGARCH-EVT model, we found that the effect of clustering, dynamic and long-term memory has been included in the modeling. FIGARCH model for log data output index, which will be modeled in terms of the above properties. In addition, the wide trail property index return data using extreme value theory (EVT) is used for residual FIGARCH model. To compare the results, NORMAL-GARCH models and t-Student-GARCH, historical simulation and GARCH-EVT indicator is used for data output. The results of the model using retrospective tests were evaluated. The results of this study indicate that the data distribution is skewed and asymmetrical index returns do not follow a normal distribution. The tests Standardized Exceedance Residuals and The Cumulative Violation Process and  Expected shortfall backtesting and loss function Lopez FIGARCH-EVT model over other models is more accurate.

کلیدواژه‌ها [English]

  • Extreme Value Theory
  • function Lopez losses
  • long-term memory
  • FIGARCH

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دانش سرمایه‌گذاری
دوره 6، شماره 23
آبان 1396
صفحه 259-282

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