Author(s)

Yunzhe Liu ¹

Affiliation(s)

¹ School of Economics and Management, Qinghai Minzu University, Xining, Qinghai, 810007, China

Corresponding Author

Yunzhe Liu

ABSTRACT

With the continuous development of the economy, people have gradually started to enjoy playing with stocks. Although stock trading comes with certain risks, it often comes with returns. Therefore, how to effectively predict stock prices, avoid risks, and increase returns has become the focus of current research. This article studied the prediction of stock trading prices based on big data, aiming to improve the accuracy of stock trading price model prediction through big data technology. This article tested the accuracy of using big data to predict stock trading prices through experiments, with a maximum of 88% and a minimum of 80%. The accuracy of traditional stock trading price prediction models was highest at 72% and lowest at 60%. From this experimental result, it can be seen that big data can indeed improve the effectiveness of stock trading price prediction models, proving the high degree of compatibility between big data and stock trading price prediction.

KEYWORDS

Big Data, Stock Trading, Trading Prices, Forecasting Research

CITE THIS PAPER

Yunzhe Liu, Prediction of Stock Trading Prices Based on Big Data. Financial Engineering and Risk Management (2023) Vol. 6: 64-71. DOI: http://dx.doi.org/10.23977/ferm.2023.060409.

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