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    題名: 退休與保險基金之策略性資產配置---預測學習效果下之動態避險(I)
    其他題名: Strategic Asset Allocation for Pension and Insurance Fund---Dynamic Hedging through Learning Predictability
    作者: 張士傑
    貢獻者: 國立政治大學風險管理與保險學系
    行政院國家科學委員會
    關鍵詞: 退休;保險基金資產配置;預測學習效果;動態避險
    日期: 2007
    上傳時間: 2012-10-22 15:44:23 (UTC+8)
    摘要: 本研究探討長期投資人(諸如保險基金、退休金基金、高淨值自然人等) 面臨通貨膨脹風險之最適投資決策。就長期基金投資決策者而言，通貨膨脹是無可避免卻又不易量化之風險，因為各國僅公布與之相關消費者物價指數而無實值通貨膨脹相關數值，本研究延伸Brennan和Xia (2002)模型，以消費者物價指數修正通貨膨脹動態過程。利用貝式過濾方法(Bayesian Filtering Method)，將含有雜訊之消費者物價指數資訊，透過驗後分配估計通貨膨脹動態過程。於學習效果下完備化交易市場，以Cox and Huang (1989, 1991)依平賭過程描述資產成長過程，求解資產公平價格，針對滿足定值相對風險趨避(Constant Relative Risk Aversion，CRRA)效用之決策者，分析最適投資組合特性。
    This study examines the optimal portfolio selection problem of a long-term investor who possesses learning capability about predictability in inflation rate and can invest only in nominal assets. Assuming that inflation rate process is not directly observable, we first employ the optimal linear filtering equations to estimate the latent process and then use the Bayesian approach to project inflation rates. This learning about predictability in inflation rates extends the studies of Campbell and Viceira (2001) and Brennan and Xia (2002). Contrasting to Barberis (2000) and Xia (2001) that consider the uncertainty regarding the relation between stock returns and state variables, we analyze how the learning about inflation rate predictability affects the composition of the optimal portfolio. We construct the optimal portfolio strategy through a Martingale formulation based on wealth constraints. Our results are given in closed-form solutions as well as numerical illustrations that demonstrate the importance of learning about inflation rate predictability in the portfolio selection proble
    關聯: 應用研究
    學術補助
    研究期間:9608~ 9707
    研究經費:990仟元
    資料類型: report
    顯示於類別:[風險管理與保險學系] 國科會研究計畫

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    96-2416-H004-025-MY3(I).PDF116KbAdobe PDF2526檢視/開啟


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