資產不對稱性波動參數的誤差估計與探討; The Error Estimation and Discussion of Asymmetrical Volatility's Parameters of Asset

Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/7731

Title:	資產不對稱性波動參數的誤差估計與探討;The Error Estimation and Discussion of Asymmetrical Volatility's Parameters of Asset
Authors:	江亮青;Liang-qing Jiang
Contributors:	統計研究所
Keywords:	最大概似估計法;蒙地卡羅模擬法;Black-Scholes 選擇權定價模型;TGARCH模型;不對稱性波動;Maximum Likelihood Estimation;Monte Carlo Simulation;TGARCH model;Black-Scholes option pricing model;Asymmetrical volatility
Date:	2009-06-01
Issue Date:	2009-09-22 11:03:24 (UTC+8)
Publisher:	國立中央大學圖書館
Abstract:	由於標的資產很容易受到外來資訊的影響，因而有時標的資產的價格在短期間內會呈現大幅上升或下跌的情形，並導致標的資產的不對稱性波動(Volatility)。本文的主旨便在於先將實際資料裡的參數代入 TGARCH (1,1) 波動參數模型來模擬並獲得其標的資產在不對稱性波動之下的價格和報酬率資料。之後，利用 Black-Scholes 選擇權定價模型來獲得在該條件底下的選擇權價格資料。藉由蒙地卡羅模擬法 (Monte Carlo simulation)、最大概似估計法(Maximum Likelihood Estimation) 與本研究主要的三種做法分別求出 TGARCH(1,1) 模型的估計參數與實際參數之間誤差絕對值的平均、標準差和均方誤差 (MSE，meansquare error)。最後再根據選擇權當中常見的三種情形 ─ 價平、價內和價外來進行上述參數的誤差推估與討論。 Because a financial asset is affected by outside information easily, sometimes the price of a financial asset has ascent or descent largely in short period. And it results in asymmetrical volatility of a financial asset. The purpose of this thesis is to simulate stock price and return rate of this financial asset in asymmetrical volatility by the method which is that parameters of real data substitute for TGARCH (1,1) model first. And then we predict value of option in the same situation by Black-Scholes option pricing model. Then, we estimate the absolute value of error, standard deviation, and mean square error between true and estimated parameters of TGARCH (1,1) model by Monte Carlo Simulation, Maximum Likelihood Estimation and three methods which is mentioned by this thesis. Finally, we estimate and discuss the error of foregoing parameters with three types of options ─ at-the-money, in-the-money and out-the-money.
Appears in Collections:	[Graduate Institute of Statistics] Electronic Thesis & Dissertation

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