针对ARCH模型传统估计方法的不足,提出了利用微粒群算法及其改进的算法快速精确的估计ARCH模型的参数,最后利用微粒群算法实证建立了上证指数收益的ARCH模型,并且对以后的情况进行了预测.
Because of the disadvantages of traditional estimating methods of ARCH model,this paper estimates the parameters in ARCH model accurately with particle swarm optimization and its improved approaches.Finally the ARCH model for stock return is established empirically with algorithm and forecast of the return is given.