estimation of parameter

基本解释

But the methods of estimation of parameter of the GARCH models, BHHH and GMM, may become invalid because they usually meet the situation that the middle data fluctuate greatly.
而GARCH模型参数估计的主要方法BHHH算法和广义矩方法在实际运算中常遇到中间数据震荡从而导致算法整体失效等。
So firstly to get a better estimation of parameter using iterate inversion on wide scale , then using this estimation as initial value on mini scale till to get global optimum of original problem.
因此可先在粗尺度上迭代反演，得到一个较好的参数估计，再将这个估计作为较精细尺度的初值进行反演，直至原问题的全局最优解。
Finally, we present a demonstration of Chinese stock which shows obvious bivariate GARCH effect and apply MAA to the estimation, which solve the estimation of parameter of bivariate GARCH model well.
最后，我们对中国股市统计数据进行了应用研究，结果表明中国股市存在着显著的二元GARCH效应，并利用多智能体退火算法较好地解决了二元GARCH模型的参数估计应用。