Research on Stock Price Forecast based on Resnet and LSTM

Baicun Guo

《Frontiers in Economics and Management》 3卷5期 (2022/05) Pp. 161-167

https://doi.org/10.6981/FEM.202205_3(5).0022

摘要

The changes of the stock market affect the returns of investors, but the trend of stock prices is affected by many factors, and the traditional forecasting methods are increasingly difficult to meet people's requirements. Considering that CNN is good at processing images and LSTM is good at predicting events in time series, we propose a model based on ResNet and LSTM. Firstly, we use a network structure similar to 18-layer ResNet to extract features from the data. Then LSTM is used to predict stock prices. Experimental results show that this model can be successfully applied to the research of stock prediction, and it is more stable than other methods.

關鍵字

ResNet ； LSTM ； Stock Prediction

參考文獻

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