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dc.contributor.author문미주-
dc.creator문미주-
dc.date.accessioned2016-08-25T06:08:54Z-
dc.date.available2016-08-25T06:08:54Z-
dc.date.issued2002-
dc.identifier.otherOAK-000000029854-
dc.identifier.urihttps://dspace.ewha.ac.kr/handle/2015.oak/181837-
dc.identifier.urihttp://dcollection.ewha.ac.kr/jsp/common/DcLoOrgPer.jsp?sItemId=000000029854-
dc.description.abstractFinancial market volatility 는 투자, 옵션 가격 그리고 financial market regulation에서 중요한 값이다. 이 논문에서는 이런 중요한 값인 volatility을 estimating 하는 여러 가지 방법들에 대해 살펴보고, 이런 방법 중 EWMA와 GARCH을 이용해서 volatility를 구하는 예를 들었다.;Financial market, volatility is an important input for investment, option pric- ing and financial market regulation. In this paper, we compare the volatility forecasting findings in 16 papers published and written in the last decade. We find consists of research papers that formulate volatility forecasts based on historical price information. Provided in this paper as well are volatility definitions, insights into problematic issues of forecast evaluation, comparing two methods of volatility forecasting on Microsoft's earning.-
dc.description.tableofcontentsChapter 1. Introduction = 2 Chapter 2. Overview of Volatility = 5 2.1 Black-Scholes model = 5 2.2 Two basic kinds of Volatility = 8 2.2.1 Historical volatility = 10 2.2.2 Implied volatility = 12 Chapter 3. Methods of estimating historical volatility = 14 3.1 Moving Average processes = 17 3.2 EWMA Model = 18 3.3 ARCH Model = 20 3.4 GARCH(p,q) Model = 24 3.4.1 EGARCH = 26 3.4.2 GJR = 27 3.4.3 APARCH = 28 3.5 Stochastic volatility = 29 Chapter 4. A case study of : Forecasting volatility = 33-
dc.formatapplication/pdf-
dc.format.extent1279815 bytes-
dc.languageeng-
dc.publisherThe Graduate school of Ewha women university-
dc.subjectEstimationg-
dc.subjecthistorical volatility-
dc.subjectstock price-
dc.titleEstimationg historical volatility of stock price-
dc.typeMaster's Thesis-
dc.format.page41 p.-
dc.identifier.thesisdegreeMaster-
dc.identifier.major대학원 수학과-
dc.date.awarded2003. 2-
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일반대학원 > 수학과 > Theses_Master
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