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	Stock Price Prediction Through the Mixture of Gaussian Processes via the Precise Hard-cut EM Algorithm
	Liu, Shuanglong ; Ma, Jinwen
	2016
关键词	Mixture of Gaussian processes EM algorithm Parameter learning Stock price Times series prediction
英文摘要	In this paper, the mixture of Gaussian processes (MGP) is applied to model and predict the time series of stock prices. Methodically, the precise hard-cut expectation maximization (EM) algorithm for MGPs is utilized to learn the parameters of the MGP model from stock prices data. It is demonstrated by the experiments that the MGP model with the precise hard-cut EM algorithm can be successfully applied to the prediction of stock prices, and outperforms the typical regression models and algorithms.; EI; CPCI-S(ISTP); jwma@math.pku.edu.cn; 282-293; 9773
语种	英语
出处	EI ; SCI
出版者	12th International Conference on Intelligent Computing (ICIC)
内容类型	其他
源URL	[http://hdl.handle.net/20.500.11897/449594]
专题	数学科学学院
推荐引用方式 GB/T 7714	Liu, Shuanglong,Ma, Jinwen. Stock Price Prediction Through the Mixture of Gaussian Processes via the Precise Hard-cut EM Algorithm. 2016-01-01.

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