| dc.contributor.advisor | 謝明華<br>陳松男 | zh_TW |
| dc.contributor.advisor | Hsieh,Ming-Hua<br>Chen,Son-Nan | en_US |
| dc.contributor.author (作者) | 陳育偉 | zh_TW |
| dc.contributor.author (作者) | Chen,Yu-Wei | en_US |
| dc.creator (作者) | 陳育偉 | zh_TW |
| dc.creator (作者) | Chen,Yu-Wei | en_US |
| dc.date (日期) | 2006 | en_US |
| dc.date.accessioned | 18-九月-2009 14:32:07 (UTC+8) | - |
| dc.date.available | 18-九月-2009 14:32:07 (UTC+8) | - |
| dc.date.issued (上傳時間) | 18-九月-2009 14:32:07 (UTC+8) | - |
| dc.identifier (其他 識別碼) | G0094356021 | en_US |
| dc.identifier.uri (URI) | https://nccur.lib.nccu.edu.tw/handle/140.119/35244 | - |
| dc.description (描述) | 碩士 | zh_TW |
| dc.description (描述) | 國立政治大學 | zh_TW |
| dc.description (描述) | 資訊管理研究所 | zh_TW |
| dc.description (描述) | 94356021 | zh_TW |
| dc.description (描述) | 95 | zh_TW |
| dc.description.abstract (摘要) | 由於金融事件層出不窮，控管風險已成為銀行、證券、保險各種金融產業的重要課題。其中Value-at-Risk(VaR)模型為銀行與證券業最常用來衡量其市場風險的模型。VaR模型中的蒙地卡羅模擬法是將投資組合持有部位以適當的市場風險因子來表示，接著產生市場風險因子的各種情境，再結合評價公式以求得投資組合在某一段持有期間內、某一信心水準之下的最低價值，再將最低價值減去原來之價值，便為可能的最大損失(Jorion, 2007)。
使用蒙地卡羅模擬法產生市場風險因子的各種情境，必須先估計市場風險因子的共變異數矩陣，再藉此模擬出數千種市場風險因子情境。本研究便是將蒙地卡羅模擬法加入隨著時間改變之共變異數矩陣(time-varying covariance matrix)的概念並減少市場風險因子個數，利用蒙地卡羅模擬法配合Constant模型、UWMA模型、EWMA模型、Orthogonal EWMA模型、Orthogonal GARCH模型、PCA EWMA模型、PCA GARCH模型來產生市場風險因子未來的情境並比較各方法對長天期與短天期風險衡量之優劣。結果顯示PCA EWMA模型的效果最好，因此建議各大金融機構可採用PCA EWMA模型來控管其投資組合短天期與長天期的市場風險。 | zh_TW |
| dc.description.tableofcontents | 第一章 緒論 - 2 - 第一節 研究背景 - 2 - 第二節 研究動機與目的 - 3 -第二章 文獻探討 - 5 - 第一節 變異數估計方法 - 5 - 第二節 共變異數矩陣估計方法 - 9 - 第三節 模型評估方法 - 13 -第三章 研究方法 - 14 -第四章 實證分析 - 17 - 第一節 資料選取 - 17 - 第二節 分析結果 - 18 -第五章 結論與建議 - 23 - 第一節 結論 - 23 - 第二節 建議 - 24 -參考文獻 - 25 -附錄 - 26 - | zh_TW |
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| dc.format.mimetype | application/pdf | - |
| dc.language.iso | en_US | - |
| dc.source.uri (資料來源) | http://thesis.lib.nccu.edu.tw/record/#G0094356021 | en_US |
| dc.subject (關鍵詞) | 市場風險 | zh_TW |
| dc.subject (關鍵詞) | 蒙地卡羅 | zh_TW |
| dc.subject (關鍵詞) | 共變異數矩陣 | zh_TW |
| dc.subject (關鍵詞) | 主成分分析 | zh_TW |
| dc.subject (關鍵詞) | Market Risk | en_US |
| dc.subject (關鍵詞) | Monte Carlo | en_US |
| dc.subject (關鍵詞) | Covariance Matrix | en_US |
| dc.subject (關鍵詞) | Principal Component Analysis | en_US |
| dc.title (題名) | 市場風險因子情境產生方法之研究 | zh_TW |
| dc.title (題名) | Methodology for Risk Factors Scenario Generation | en_US |
| dc.type (資料類型) | thesis | en |
| dc.relation.reference (參考文獻) | Alexander, C.O. (2004), Market Model: A Guide to Financial Data Analysis, John Wiley & Sons Ltd | zh_TW |
| dc.relation.reference (參考文獻) | Alexander, C.O. (2000), `Orthogonal methods for generating large positive semi-definite covariance matrices`, ISMA Centre Discussion Papers in Finance 2000-06 | zh_TW |
| dc.relation.reference (參考文獻) | Alexander, C.O. & Leigh, C. (1997), `On the covariance matrices used in VAR models`, Journal of derivative 4(3), 50-62 | zh_TW |
| dc.relation.reference (參考文獻) | Bank for International Settlements (1996) `Amendment to the Capital Accord to Incorporate Market Risks` | zh_TW |
| dc.relation.reference (參考文獻) | Bollerslev, T. (1986), `Generalised autoregressive conditional heteroskedasticy`, Journal of Econometrics 31, 307-327 | zh_TW |
| dc.relation.reference (參考文獻) | Engle, R.F. (1982), `Autoregressive conditional heteroscedasticity with estimates of the variance of UK inflation`, Econometric 50, 987-1007 | zh_TW |
| dc.relation.reference (參考文獻) | Golub, B. & Tilman, L. (2000), Risk Management: Approaches for Fixed Income Markets, John Wiley & Sons Ltd | zh_TW |
| dc.relation.reference (參考文獻) | Jorion, P. (2007), Value at Risk: The New Benchmark for Managing Financial Risk, McGraw-Hill | zh_TW |
| dc.relation.reference (參考文獻) | Morgan, J.P. & Reuters (1996),`RiskMetrics Technical Document, 4th edition`, Technical report, Morgan Guaranty and Reuters | zh_TW |
| dc.relation.reference (參考文獻) | Singh, M. (1997), `Value at Risk Using Principal Components Analysis`, Journal of Portfolio Management 24, 101-113 | zh_TW |
