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JCR 2016
جستجوی مقالات
پنجشنبه 20 آذر 1404
Iranian Economic Review
، جلد ۲۹، شماره ۳، صفحات ۷۹۴-۸۱۸
عنوان فارسی
چکیده فارسی مقاله
کلیدواژههای فارسی مقاله
عنوان انگلیسی
Upper Bounds of Stock Portfolio Investment Risk Using Value at Risk (Case Study: Indonesian Blue-Chip Stocks in 2022)
چکیده انگلیسی مقاله
In recent years, stocks become the most preferred asset by Indonesian investors. Besides offering large profits, stock investment also has a risk factor that can occur at any time. One way to minimize risk is to form a stock portfolio. This paper aims to measure the upper bounds of the portfolio loss risk formed by several single assets that are mutually dependent. The upper bound value is chosen because the exact value of portfolio loss risk is difficult to obtained by Convolution or Panjer Recursion methods. The main analysis of this research is formed the upper bounds of stock portfolio investment risk using VaR with Cornish Fisher Expansion aproach by utilized comonotonicity and convex order properties. The portofolio contains of 3 single asset (ARTO.JK, ITMG.JK, and MIKA.JK) which collected from IDX Indonesia from 10/25/21 to 10/21/22. The novelty of this research is combined comonotonicity and convex order properties with VaR-CFE to get upper bounds of portolio risk predicition. The result show that at 95% significance level and 1-day holding period, the upper bounds of VaR-CFE prediction for the portfolio is -0.1394. The social impact of this research can be a benchmark to get accurate risk prediction of their portfolio asset.
کلیدواژههای انگلیسی مقاله
Comonotonicity,Convex Order,Portfolio,risk,Value at Risk-Cornis Fisher Expansion
نویسندگان مقاله
Hersugondo Hersugondo |
Department of Management, Faculty of Economics and Busniness, Diponegoro University, Semarang, Indonesia
Imam Ghozali |
Department of Accounting, Faculty of Economics and Business, Diponegoro University, Semarang, Indonesia
Mohamad Nasir |
Department of Accounting, Faculty of Economic and Business, Diponegoro University, Semarang, Indonesia.
Trimono Trimono |
Data Science Study Program, Faculty of Computer Science, Pembangunan Nasional Veteran Jawa Timur University, Surabaya, Indonesia.
Idris Idris |
Department of Management, Faculty of Economics and Business, Diponegoro University, Semarang, Indonesia
نشانی اینترنتی
https://ier.ut.ac.ir/article_103893_80c0470df89a191a50929751d9a26621.pdf
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