EPMS方法對選擇權價格估計之漸近分佈 = Asymptotic Dis...
凃雅婷

 

  • EPMS方法對選擇權價格估計之漸近分佈 = Asymptotic Distribution of the EPMS Estimator for Option Pricing
  • 紀錄類型: 書目-語言資料,印刷品 : 單行本
    並列題名: Asymptotic Distribution of the EPMS Estimator for Option Pricing
    作者: 凃雅婷,
    其他團體作者: 國立高雄大學
    出版地: [高雄市]
    出版者: 撰者;
    出版年: 2012[民101]
    面頁冊數: 28面圖,表格 : 30公分;
    標題: P 測度下的平睹過程配適模擬法
    標題: empirical P-martingale simulation
    電子資源: http://handle.ncl.edu.tw/11296/ndltd/28217167562533389845
    附註: 106年10月31日公開
    附註: 參考書目:面23
    摘要註: 本文推導出 Empirical P-martingale Simulation (EPMS) 方法對金融衍生性產品價格估計量的漸近常態分佈。當風險中立測度模型不容易得到時, EPMS是一個容易執行且有效率的方法。文中考慮在 Black-Scholes 和 GARCH 模型假設下,蒙地卡羅法, Empirical Martingale Simulation (EMS) 以及 EPMS 在計算歐式買權的有效性。模擬結果顯示本文所推導之漸近分布在樣本路徑達到500時,即可給出令人滿意的逼近。 The asymptotic normality of the empirical P-martingale simulation (EPMS)estimator for nancial derivative pricing is established in this study. The EPMS is an easily implemented and e cient method to compute derivative prices if a risk-neutral model is not convenient to be obtained. The e ciency of the Monte Carlo, empirical martingale simulation (EMS) and EPMS estimators for European call option pricing are compared under the Black-Scholes and GARCH models. Simulation results indicate that the asymptotic distribution serves as a persuasive approximation for samples consisting of as few as 500 simulation paths.
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