Stock forecasting based on LSTM model in the context of COVID-19 epidemic
DOI:
https://doi.org/10.54691/bcpbm.v38i.3724Keywords:
LSTM model; COVID-19 pandemic; Stock price forecasting.Abstract
The COVID-19 pandemic has exploded at the beginning of 2020, which lead to great impacts on a wide range of areas. In addition to the change of mankind’s daily behaviors, the global economy is also hit severely by the pandemic. In this context, it is of great significance for the stock market and the investors to conduct in-depth research on quantitative investment considering COVID-19 factor. This study selected 5 representative stocks in the market as the research objects and construct the LSTM model to forecast the stock price as well as analyze the correlation between stock price and COVID-19 pandemic. According to the analysis, it can be obviously seen that the pandemic has had a big impact on the stock market and the price of different stocks fluctuated during the whole period. Moreover, the model was successfully built and output desirable predictions about the stock. These results shed light on guiding further exploration of stock market forecasting and the investment during the pandemic time.
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References
Li R and Xiong Z. Forecasting stock market with fuzzy neural networks, 2005 International Conference on Machine Learning and Cybernetics, 2005, pp. 3475-3479 Vol. 6.
Gholamreza J, et al. Application of Fuzzy-neural networks in multi-ahead forecast of stock price. African Journal of Business Management, 2010, 4(6): 903-914.
Pradeepkumar D, Ravi V. Forecasting financial time series volatility using particle swarm optimization trained quantile regression neural network. Applied Soft Computing, 2017, 58: 35-52.
Samarawickrama A. J. P. and Fernando T. G. I. A recurrent neural network approach in predicting daily stock prices an application to the Sri Lankan stock market. 2017 IEEE International Conference on Industrial and Information Systems (ICIIS), 2017, pp. 1-6.
Yu Wang, et al. Stock forecasting based on Cart Decision tree and Boosting. Journal of Harbin University of Science and Technology, 2019,24(06):98-103.
Zeren F, Hizarci A. The impact of COVID-19 coronavirus on stock markets: evidence from selected countries. Muhasebe ve Finans İncelemeleri Dergisi, 2020, 3(1): 78-84.
Nakat Z, Bou-Mitri C. COVID-19 and the food industry: Readiness assessment. Food control, 2021, 121: 107661.
Yeh S S. Tourism recovery strategy against COVID-19 pandemic. Tourism Recreation Research, 2021, 46(2): 188-194.
Shuai Li, Qiang Zhang. An empirical study on the impact of COVID-19 on the returns of the US stock healthcare industry. China's prices, 2021(09):83-86.
Singh A. COVID-19 and safer investment bets. Finance research letters, 2020, 36: 101729.






