Qunhui Zhang1, Mengzhe Lu3,4, Liang Dai2,*
Computer Systems Science and Engineering, Vol.41, No.2, pp. 795-809, 2022, DOI:10.32604/csse.2022.019987
Abstract Stock market trading is an activity in which investors need fast and accurate information to make effective decisions. But the fact is that forecasting stock prices by using various models has been suffering from low accuracy, slow convergence, and complex parameters. This study aims to employ a mixed model to improve the accuracy of stock price prediction. We present how to use a random walk based on jump-diffusion, to obtain stock predictions with a good-fitting degree by adjusting different parameters. Aimed at getting better parameters and then using the time series model to predict the data, we employed the time… More >
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