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    題名: 狀態轉換下利率與跳躍風險股票報酬之歐式選擇權評價與實證分析
    Option Pricing and Empirical Analysis for Interest Rate and Stock Index Return with Regime-Switching Model and Dependent Jump Risks
    作者: 巫柏成
    Wu, Po Cheng
    貢獻者: 陳麗霞
    林士貴

    Chen, Li Shya
    Lin, Shih Kuei

    巫柏成
    Wu, Po Cheng
    關鍵詞: 狀態轉換下利率與跳躍相關風險之股票報酬二維模型
    EM演算法
    Esscher轉換法
    歐式買權定價公式
    敏感度分析
    模型校準
    波動度微笑曲線
    MMJDMSI model
    EM algorithm
    Esscher Transformation
    European call option pricing formula
    sensitivity analysis;model
    model calibration
    volatility smile curve
    日期: 2015
    上傳時間: 2015-09-01 16:09:16 (UTC+8)
    摘要: Chen, Chang, Wen and Lin (2013)提出馬可夫調控跳躍過程模型(MMJDM)描述股價指數報酬率,布朗運動項、跳躍項之頻率與市場狀態有關。然而,利率並非常數,本論文以狀態轉換模型配適零息債劵之動態過程,提出狀態轉換下的利率與具跳躍風險的股票報酬之二維模型(MMJDMSI),並以1999年至2013年的道瓊工業指數與S&P 500指數和同期間之一年期美國國庫劵價格為實證資料,採用EM演算法取得參數估計值。經由概似比檢定結果顯示無論道瓊工業指數還是S&P 500指數,狀態轉換下利率與跳躍風險之股票報酬二維模型更適合描述報酬率。接著,利用Esscher轉換法推導出各模型下的股價指數之歐式買權定價公式,再對MMJDMSI模型進行敏感度分析以評估模型參數發生變動時對於定價公式的影響。最後,以實證資料對各模型進行模型校準及計算隱含波動度,結果顯示MMJDMSI在價內及價外時定價誤差為最小或次小,且此模型亦能呈現出波動度微笑曲線之現象。
    To model asset return, Chen, Chang, Wen and Lin (2013) proposed Markov-Modulated Jump Diffusion Model (MMJDM) assuming that the Brownian motion term and jump frequency are all related to market states. In fact, the interest rate is not constant, Regime-Switching Model is taken to fit the process of the zero-coupon bond price, and a bivariate model for interest rate and stock index return with regime-switching and dependent jump risks (MMJDMSI) is proposed. The empirical data are Dow Jones Industrial Average and S&P 500 Index from 1999 to 2013, together with US 1-Year Treasury Bond over the same period. Model parameters are estimated by the Expectation-Maximization (EM) algorithm. The likelihood ratio test (LRT) is performed to compare nested models, and MMJDMSI is better than the others. Then, European call option pricing formula under each model is derived via Esscher transformation, and sensitivity analysis is conducted to evaluate changes resulted from different parameter values under the MMJDMSI pricing formula. Finally, model calibrations are performed and implied volatilities are computed under each model empirically. In cases of in-the-money and out-the-money, MMJDMSI has either the smallest or the second smallest pricing error. Also, the implied volatilities from MMJDMSI display a volatility smile curve.
    參考文獻: 1.Bailey, W. and Stulz, R. (1989). The pricing of stock index options in a general equilibrium model. Journal of Financial and Quantitative Analysis 24, 1-12.
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    3.Ball, C. and Torous, W. (1983). A simplified jump process for common stock returns. Journal of Financial and Quantitative Analysis 18, 01, 53-65.
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    5.Bo, L., Wang, Y., and Yang, X. (2010). Markov-modulated jump-diffusion for currency option pricing. Insurance: Mathematics and Economics 46, 461-469.
    6.Charles, C., Fuh, C.D., and Lin, S.K. (2013). A tale of two regimes: Theory and empirical evidence for a markov-modulated jump diffusion model of equity returns and derivative pricing implications. Working paper.
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    17.Lin, S.K. Shyu, S.D. and Wang, S.Y. (2013). Option pricing under stock market cycles with jump risks: evidence from Dow Jones industrial average index and S&P 500 index. Working paper.
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    描述: 碩士
    國立政治大學
    統計研究所
    102354017
    資料來源: http://thesis.lib.nccu.edu.tw/record/#G0102354017
    資料類型: thesis
    顯示於類別:[統計學系] 學位論文

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