خط مشی دسترسیدرباره ما
ثبت نامثبت نام
راهنماراهنما
فارسی
ورودورود
صفحه اصلیصفحه اصلی
جستجوی مدارک
تمام متن
منابع دیجیتالی
رکورد قبلیرکورد بعدی
Record identifier : 564947
Personal Name - Primary Intelectual Responsibility : Samadi,Malihe
Title and statement of responsibility : The application of VaR in Insurance Market with Monte Carlo simulation: the case of Collision Insurance Claims in Iran [Thesis]/ملیحه صمدی;supervisor: Ghadir Mahdavi;advisor: Kamran Nadri
Publication, Distribution,Etc. : , 2011
Language of the Item : eng
Internal Bibliographies/Indexes Note : Bibliography
Dissertation of thesis details and type of degree : Master of Arts
Discipline of degree : , Actuarial Science
Body granting the degree : , Allameh Tabatabai University, ECO College of Insurance
Summary or Abstract : هدف تحقیق:بررسی کارمحاسبه سرمایه مورد نیاز در پوشش مطالبات بیمه بدنه می باشد. یافته ها نشان می دهد که برآورد ارزش در معرض خطر با استفاده از فرایند بهینه سازی دارای کارایی بهتری می باشد.ارزش در معرض خطر بهینه مقدار سرمایه مورد نیاز جهت ژوشش مطالبات بیمه با احتمال ۹۹ درصد درست تخمین می زند در حالیکه ارزش در معرض خطر اولیه سرمایه مورد نیاز جهت پوشش مطالبات بیسمه را کمتر از مقدار واقعی آن برآورد می کند
: One of the most common and recent tools in risk measurement is the "Value-at-Risk", (VaR). VaR is the expected loss of a portfolio over a specified period of time, for a level of probability. There are some methods for calculating VaR and in this thesis; we apply Monte Carlo simulation method to estimate the simple Value-at-Risk (VaR-MC) as well as the optimal or adjusted Value-at-Risk (VaR-OP) in daily collision insurance claims in Iran.In this study, we provide random numbers with using random process based on the latest daily data of collision insurance claims in Iran. Monte Carlo simulation is obtained through an iterative procedure with considering the adjusted process to accommodate shocks. Adjusting is a process for reducing the potential bias of VaR estimates. Adjusting coefficient is obtained from the simple VaR. It affects Monte Carlo estimation and provides the adjusted VaR. Depending on the times that loss exceeds over the calculated VaR, the coefficient may increase or decrease the variance of claims and consequently, it causes VaR-OP to become smaller or larger than the simple VaR. Finally, the result obtained by the simple Monte Carlo method (VaR-MC) is compared with the result obtained by the adjusted VaR and the model is validated by using back testing method on the basis of unconditional covering in order to examine the accuracy of the model.Empirical validation shows that VaR estimation via the adjusted process is relatively reliable and appropriate. The results obtained by the simple VaR, underestimate the risk, it shows that the adjusting coefficient is more useful for reaching to a better estimation of VaR within 99 confidence level..
Uncontrolled Subject Terms : VaR-OP
: VaR-MC
: Monte Carlo simulation
: adjusting
: ارزش در معرض خطر
: شبیه سازی مونت کارلو
Information of biblio record : TL
 
 
 
(در صورت عدم وضوح تصویر اینجا را کلیک نمایید)