خط مشی دسترسیدرباره ما
ثبت نامثبت نام
راهنماراهنما
فارسی
ورودورود
صفحه اصلیصفحه اصلی
جستجوی مدارک
تمام متن
منابع دیجیتالی
رکورد قبلیرکورد بعدی
Record identifier : 564648
Personal Name - Primary Intelectual Responsibility : Abedi Khorasgani, Atefeh
Title and statement of responsibility : APPLYING EXTREME VALUE THEORY IN MEASURING MARKET RISKS [Thesis]/عابدی خوراسگانی، عاطفه;supervisor: Hamid Reza Farhadi;advisor: Hossein Behzadi
Publication, Distribution,Etc. : , 2008
Language of the Item : eng
Internal Bibliographies/Indexes Note : Bibliography
Dissertation of thesis details and type of degree : MAster Of Arts
Body granting the degree : , ECO COLLEGE OF INSURANCE
Summary or Abstract : برای دو سری اغز داده های بازار مالی مورد محاسبه قرار گرفته استExpected shoryfall در این تحقیق مطالعه دقیقی در مورد ادبیات تئوری مقادیر کرانگین انجام شده و تئوری مقادیری کرانگین نیز به عنوان روشی برای محاسبه اندازه ریسک های بازار به کار برده شده است سپس ارزش در معرض خطر
: The theory of extreme values is considered when one is dealing with the events which do not usually happen. Extremes or rare events are of interest when having the most to win or lose by that event. Some examples are: stock market crashes, insurance losses, earthquakes, hurricanes and meteorological changes. The use of Extreme Value Theory in financial market calculations has been received more attention in recent years in such a way that a clear understanding of the probability distribution of extreme events is an important issue in financial and insurance risk management. By definition, an extreme event happens when the risk random variable takes the values of its tail distribution and therefore the Extreme Value Theory (EVT) is a branch of Statistics focusing on the studying the tail behavior of a probability distribution. The aim of this work is to use Extreme Value Theory to compute market risk measures namely, Value-at-Risk (VaR), a widely used risk management tool for portfolios x exposed to market risk, the Expected Shortfall and the Return Level. We consider two general approaches for identifying maximums in the data set. They are the Block Maxima Method (BMM) and the method of Peak Over Threshold (POT). The theoretical results then would be applied for a real dataset of stock market index return. Keywords: Extreme value Theory, Fisher-Tippett Theorem, Maximum Domain of Attraction, Value-at-Risk, Expected Shortfall..
Topical Name Used as Subject : extreme value Theory
: Fisher
: Ippett Theorm
Information of biblio record : TL
 
 
 
(در صورت عدم وضوح تصویر اینجا را کلیک نمایید)