id	author	title	date	pages	extension	mime	words	sentence	flesch	summary	cache	txt
fcis-11268	Xu, Tianyu; He, Xiaoling	EMD-BiLSTM Stock Price Trend Forecasting Model based on Investor Sentiment	2023	5	.pdf	application/pdf	4377	162	47	5. Conclusion Aiming at the problem of large prediction error caused by nonlinearity, non-stationarity and chaos of stock time series, this paper proposes a BiLSTM stock price rise and fall model based on empirical mode decomposition and investor sentiment. In order to improve the prediction accuracy, according to the temporal characteristics of stock price data, it is proposed to use a combination of empirical mode decomposition (EMD), investor sentiment and two-way long short-term memory neural network to predict the rise and fall of stock prices.	cache/fcis-11268.pdf	txt/fcis-11268.txt