GARCH模型之參數估計
Parameters Estimation of the GARCH Model
Date Issued
2006
Date
2006
Author(s)
Chang, Yu-Chieh
DOI
en-US
Abstract
GARCH is one of the most popular stochastic variance models. The model successfully captures the serial correlation of asset return volatilities. The model needs five parameters, and some of them do not have intuitively economic meanings. So how to determine the parameters is one of the most challenging problems facing the GARCH model. Applying the maximum likelihood method to the
historical data is the most common approach to obtaining the parameters. As an alternative, this thesis develops efficient numerical algorithms to calibrate the model with option prices.
Subjects
參數估計
隨機變異數模型
GARCH
parameter estimation
Type
thesis
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