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DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 吳文方 | |
dc.contributor.author | Chung-Chi Huang | en |
dc.contributor.author | 黃中奇 | zh_TW |
dc.date.accessioned | 2021-06-16T10:30:21Z | - |
dc.date.available | 2018-08-20 | |
dc.date.copyright | 2013-08-20 | |
dc.date.issued | 2013 | |
dc.date.submitted | 2013-08-14 | |
dc.identifier.citation | 1. Artzner, P., Delbaen, F., Eber, J. M., and Heath, D. (1999). Coherent measures of risk. Mathematical finance, 9(3), 203-228.
2. Aumann, Robert J., and Roberto Serrano. (2008). An economic index of riskiness. Journal of Political Economy, 116(5), 810-836. 3. Hull, J. C., and White, A. D. (1998). Value at risk when daily changes in market variables are not normally distributed. The Journal of Derivatives, 5(3), 9-19. 4. Jorion, P. (2007). Value at risk: the new benchmark for managing financial risk(Vol. 3). New York: McGraw-Hill. 5. Markowitz, H. (1952). Portfolio selection. The journal of finance, 7(1), 77-91. 6. Mausser, H., and Rosen, D. (1999). Beyond VaR: From measuring risk to managing risk. In Computational Intelligence for Financial Engineering, 1999.(CIFEr) Proceedings of the IEEE/IAFE 1999 Conference on (pp. 163-178). IEEE. 7. Morgan, J. P. (1997). Creditmetrics-technical document. JP Morgan, New York. 8. Pflug, G. C. (2000). Some remarks on the value-at-risk and the conditional value-at-risk. In Probabilistic constrained optimization (pp. 272-281). Springer US. 9. Roy, A. D. (1952). Safety first and the holding of assets. Econometrica: Journal of the Econometric Society, 431-449. 10. 梁允綺(2010),「Riskiness之應用:以跨國證券市場為例」,國立台灣大學財務金融學研究所碩士論文。 11. 盧錫滿(2009),「以GARCH模型衡量投資組合的波動性風險- 台灣股票市場為例」,國立台灣大學工業工程學研究所碩士論文。 12. 謝明峰(2012),「風險指標之實證研究─以美國上市公司債資料為例」,國立台灣科技大學財務金融學研究所碩士論文。 13. 關淑蕙(2003),「條件風險值—於保險與股票投資上之應用」,國立台灣大學財務金融學研究所碩士論文。 | |
dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/60791 | - |
dc.description.abstract | 近年來,風險管理已成社會重要議題,尤其在金融風暴之後,更是如此。風險管理工作中重要的一環在於風險量化,亦即藉由某種數據指標衡量風險之大小。本研究旨在以Aumann與Serrano於2008年所提出、有別於傳統VaR (Value at Risk)與CVaR (Conditional Value at Risk)一種稱為Riskiness之新風險指標衡量台灣股票市場十九大類股的風險數值,同時也計算各類股的VaR與CVaR風險指標數值,探討此三種指標與各類股平均日報酬率及各類股財務變數的相關性。研究結果發現,Riskiness風險指標與平均日報酬率呈現負相關,而VaR風險指標及CVaR風險指標與平均日報酬率則呈正相關,此三個風險指標都與平均日報酬率的標準差呈正相關。經分別依據三種風險指標針對十九大類股一一排序後,本研究發現依據三種風險指標所為類股的排序並不一致,表示三者對風險的衡量並不全然相同。對財務變數建立迴歸模型研究結果顯示,類股之股東權益報酬率越高,三種風險指標皆會越低,而類股之股價淨值比越高,則Riskiness風險指標則越高。 | zh_TW |
dc.description.abstract | Risk management is highly concerned in modern society, especially after the financial storm occurred in 2008. One important issue of risk management is the quantitative risk measurement. In this study, a particular ‘riskiness index’ proposed by Aumann and Serrano is adopted to measure risks of 19 sectors of stock issued in Taiwan. Risk indices based on more traditionally used VaR (Value at Risk) and CVaR (Conditional Value at Risk) of these stocks are also calculated. For each of these three indices, its correlations with the average daily return and other financial variables are investigated. The result indicates that riskiness index is negatively correlated to the average daily return, but both VaR index and CVaR index are positively correlated to the average daily return. All these three indices are positively correlated to the standard deviation of average daily return. The orders of ranking based on different risk indices appear differently. From investigating various financial variables regression model, it is found that higher ROE (Return on equity) of 19 sectors of stocks results in lower risk no matter which of the three indices is employed. It is also found that higher PBR (price-to-book ratio) results in higher riskiness index. | en |
dc.description.provenance | Made available in DSpace on 2021-06-16T10:30:21Z (GMT). No. of bitstreams: 1 ntu-102-R98546030-1.pdf: 1457093 bytes, checksum: 8be43a23a40927e5ef314db15a529f25 (MD5) Previous issue date: 2013 | en |
dc.description.tableofcontents | 論文口試委員審定書 i
謝辭 ii 中文摘要 iii Abstract iv 目錄 v 圖目錄 vii 表目錄 viii 第一章 緒論 1 1.1 研究背景 1 1.3 研究目的 3 1.4 論文架構 4 第二章 文獻回顧 6 2.1 Riskiness風險指標 6 2.1.1 Riskiness的概念 7 2.1.2 Riskiness的性質 8 2.2 VaR(Value-at-Risk)風險指標 10 2.2.1 VaR的定義 10 2.2.2 VaR的源起 12 2.2.3 VaR的估計方法 14 2.3 CVaR(Conditional Value-at-Risk)風險指標 18 2.3.1 CVaR風險指標的定義 18 2.3.2 CVaR風險指標具有凸性(convex) 19 2.3.3 CVaR風險指標是具連貫性的(coherent)風險衡量指標 20 2.3.4 VaR風險指標與CVaR風險指標的比較 23 2.4 風險指標總回顧 24 第三章 研究方法 26 3.1 資料來源 26 3.2 風險指標之計算方法 27 3.2.1 假設報酬率之機率分配為常態分配 27 3.2.2 未假設報酬率之機率分配服從常態分配 28 3.3 標準差之計算方法 29 3.4 研究變數選擇 29 3.5 迴歸模型建立 31 第四章 實證結果 32 4.1 常態分配與原始分配的Riskiness風險指標數值之差異性 32 4.2 Riskiness、VaR與CVaR風險指標之基本敘述統計量 33 4.3 Riskiness風險指標與平均日報酬率及標準差之相關性 35 4.4 VaR風險指標與平均日報酬率及標準差之相關性 35 4.5 CVaR風險指標與平均日報酬率及標準差之相關性 36 4.6 Riskiness風險指標與VaR風險指標及CVaR風險指標之比較 41 4.6.1 Riskiness風險指標與VaR風險指標之比較 41 4.6.2 Riskiness風險指標與CVaR風險指標之比較 41 4.7 Riskiness、VaR、CVaR風險指標與財務變數迴歸分析 45 4.7.1 基本敘述統計量 45 4.7.2 迴歸結果分析 46 第五章 結論與建議 49 5.1 研究結論 49 5.2 研究限制與建議 50 參考文獻 51 | |
dc.language.iso | zh-TW | |
dc.title | 不同風險指標之比較與實證研究-以台灣股票市場為例 | zh_TW |
dc.title | Comparison and Empirical Study of Different Risk Indices with Taiwan Equity Market | en |
dc.type | Thesis | |
dc.date.schoolyear | 101-2 | |
dc.description.degree | 碩士 | |
dc.contributor.oralexamcommittee | 洪一薰,黃奎隆 | |
dc.subject.keyword | 風險,Riskiness,風險值,條件風險值,風險指標, | zh_TW |
dc.subject.keyword | Risk,Riskiness,VaR,CVaR,Risk index, | en |
dc.relation.page | 52 | |
dc.rights.note | 有償授權 | |
dc.date.accepted | 2013-08-15 | |
dc.contributor.author-college | 工學院 | zh_TW |
dc.contributor.author-dept | 工業工程學研究所 | zh_TW |
顯示於系所單位: | 工業工程學研究所 |
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