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    題名: 風險值方法實證研究─以一壽險公司為例
    An Empirical Test on the Value-at-Risk Estimation of a Life Insurance Company
    作者: 蕭國緯
    Hsiao, Justin K.W.
    貢獻者: 蔡政憲
    Tsai, Jason C.H.
    蕭國緯
    Hsiao, Justin K.W.
    關鍵詞: 市場風險
    簡化型模型
    單變數模型
    風險值
    Market Risk
    Reduced-formed
    Univariate Method
    Value-at-Risk (VaR)
    日期: 2013
    上傳時間: 2014-07-01 12:07:24 (UTC+8)
    摘要: 風險值(VaR)目前是金融機構計算市場風險最常使用的方法。雖然這個方法這麼頻繁地被使用，它仍然有一些缺陷。近年來，金融機構的投資活動成長相當快速，其投資的商品也越來越多元和複雜，在這樣的情況下，公司內部複雜的結構型模型無法在99%信賴水準下，比簡單的單變數模型有更好的準確性和預測能力。因此，單變數模型對於公司內部的結構性模型至少是一個相當有用的參考和輔助。本篇論文是第一篇使用單變數模型並採用一家台灣壽險公司歷史資料的實證論文，且有比較單變數模型和公司內部多變數結構模型的表現。
    Value-at-Risk (VaR), nowadays, is the most widely adopted risk management method for measuring market risk in financial institutions, like banks, securities companies, and insurance companies etc. Although this measure is so widespread, it has some setbacks. In recent year, trading activities in financial institutions have grown substantially and became progressively more diverse and complex. In this situation, the complicate structural models were not able to outperform a simple univariate model in terms of accuracy and forecasting ability in 99th percentile. Univariate models, therefore, are at least a useful complement to large structural models and might even be sufficient for forecasting VaR. This paper is the first article adopts univariate methods with historical data from a life insurance company in Taiwan and provides a comparison of the performance between the univariate one and the models actually in use within firm.
    參考文獻: English Literature
    Artzner, P., Delbaen, F., Eber, J. M., & Heath, D. (1999). Coherent measures of risk. Mathematical finance, 9(3), 203-228.
    Berkowitz, J., & O’Brien, J. (2002). How Accurate Are Value‐at‐Risk Models at Commercial Banks? The Journal of Finance, 57(3), 1093-1111.
    Bollerslev, T. (1986). Generalized autoregressive conditional heteroskedasticity. Journal of econometrics, 31(3), 307-327.
    Christoffersen, P. F. (1998). Evaluating interval forecasts. International economic review, 841-862.
    Christoffersen, P. F., & Diebold, F. X. (2000). How relevant is volatility forecasting for financial risk management? Review of Economics and Statistics, 82(1), 12-22.
    Duffie, D., & Pan, J. (1997). An overview of value at risk. The Journal of derivatives, 4(3), 7-49.
    Enders, W. (2008). Applied econometric time series. John Wiley & Sons.
    Engle, R. F., & Manganelli, S. (2004). CAViaR: Conditional autoregressive value at risk by regression quantiles. Journal of Business & Economic Statistics, 22(4), 367-381.
    Hendricks, D. (1996). Evaluation of value-at-risk models using historical data. Federal Reserve Bank of New York Economic Policy Review, 2(1), 39-69.
    Holton, G. A. (2002). History of Value-at-Risk: Working paper. Contingency Analysis, Boston.
    Ian Farr, H. M., Mark Scanlon, Simon Stronkhorst. (February 2008). Economic Capital for Life Insurance Companies: Towers Perrin.
    Jorion, P. (1997). Value at risk: the new benchmark for controlling market risk (Vol. 2): McGraw-Hill New York.
    Jorion, P. (2002). How informative are value-at-risk disclosures? The Accounting Review, 77(4), 911-931.
    Kupiec, P. H. (1995). Techniques for verifying the accuracy of risk measurement models. THE J. OF DERIVATIVES, 3(2).
    Lopez, J. A., & Walter, C. A. (2000). Evaluating covariance matrix forecasts in a value-at-risk framework.
    Marshall, C., & Siegel, M. (1997). Value at risk: Implementing a risk measurement standard. The Journal of derivatives, 4(3), 91-111.
    Zangari, P. (1997). Streamlining the market risk measurement process. RiskMetrics Monitor, 1, 29-35.

    Chinese Literature
    楊奕農, & 經濟. (2009). 時間序列分析: 經濟與財務上之應用. 雙葉書廊.
    描述: 碩士
    國立政治大學
    風險管理與保險研究所
    101358001
    102
    資料來源: http://thesis.lib.nccu.edu.tw/record/#G0101358001
    資料類型: thesis
    顯示於類別:[風險管理與保險學系] 學位論文

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