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    請使用永久網址來引用或連結此文件: https://ir.lib.ncu.edu.tw/handle/987654321/105838


    題名: Model risk of the implied GARCH-normal model
    作者: 黃士峰;Huang, Shih-Feng;Guo, Meihui
    貢獻者: 理學院統計研究所
    關鍵詞: Conditional leptokurtic model;Dynamic semiparametric approach;Extended Girsanov principle;GARCH model;Hedging;Investment policy;Model risk;Option pricing;Rates of return;Risk management;Securities prices;Stochastic models;Studies
    日期: 2014-12-13
    上傳時間: 2026-04-23 12:56:27 (UTC+8)
    出版者: Taylor and Francis Ltd.;Bristol: Routledge
    摘要: 摘要: Model risk causes significant losses in financial derivative pricing and hedging. Investors may undertake relatively risky investments due to insufficient hedging or overpaying implied by flawed models. The GARCH model with normal innovations (GARCH-normal) has been adopted to depict the dynamics of the returns in many applications. The implied GARCH-normal model is the one minimizing the mean square error between the market option values and the GARCH-normal option prices. In this study, we investigate the model risk of the implied GARCH-normal model fitted to conditional leptokurtic returns, an important feature of financial data. The risk-neutral GARCH model with conditional leptokurtic innovations is derived by the extended Girsanov principle. The option prices and hedging positions of the conditional leptokurtic GARCH models are obtained by extending the dynamic semiparametric approach of Huang and Guo [Statist. Sin., 2009, 19, 1037-1054]. In the simulation study we find significant model risk of the implied GARCH-normal model in pricing and hedging barrier and lookback options when the underlying dynamics follow a GARCH-t model.
    出版者: Bristol: Routledge
    出版日期: 2014-12-02
    出處: Quantitative finance, 2014-12, Vol.14 (12), p.2215-2224
    資源來源: Taylor & Francis Journals
    版權: 2011 Taylor & Francis 2011
    版權: Copyright American Institute of Physics 2014
    識別號: ISSN: 1469-7688
    識別號: EISSN: 1469-7696
    識別號: DOI: 10.1080/14697688.2011.630323
    顯示於類別:[統計研究所] 期刊論文

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