Research on the Prediction of Shenzhen Growth Enterprise Market Price Index Based on EMD-ARIMA Model

Tianhua, Li; Qu, Shaowei; Huang, Gaoping

doi:10.1007/978-981-33-4359-7_54

Cited by 2 publications

(1 citation statement)

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“…Liu used the time series ARIMA model to conduct quantitative analysis of Shenzhen Stock Exchange index [10]. Taking the closing price of Shenzhen Stock Exchange Index from July 1, 2009 to June 30, 2010 as the original data, ARIMA (6,1,6) is finally established after the data is processed by stationary and zero-averaging, model identification and model ordering, and parameters are estimated by the least square method, and after the model test proved effective, short-term prediction of future data was carried out.…”

Section: Introductionmentioning

confidence: 99%

An Empirical Study of Shanghai Composite Index Forecasts and Trend Trading Strategies Based on ARIMA Model

Zhang

2023

AEMPS

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ARIMA model is often used to forecast time series, and stock price prediction has always been a concern of investors. Accurate stock price prediction helps to make reasonable decisions in the unpredictable financial market. By modeling historical data, this paper uses ARIMA model to fit the change law of time series data, and then predict future stock changes. This paper selects the closing price data of Shanghai Composite Index on all trading days from August 19, 2019, to August 18, 2023, conducts stationarity test on it, completes the identification and sequencing of ARIMA model, conducts model test, analyzes and forecasts stock prices based on this model. The results show that the ARIMA model has a good forecasting effect on the short-term change rule of stock price time series, and has a certain reference significance for investors to make stock investment. The results show that the selected test data fits the ARIMA model well.

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Section: Introductionmentioning

confidence: 99%