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arXiv · 2212.05369

Time Series Analysis in American Stock Market Recovering in Post COVID-19 Pandemic Period

Weilin Fu·Zhuoran Li·Yupeng Zhang·Xingyou Zhou
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Abstract

Every financial crisis has caused a dual shock to the global economy. The shortage of market liquidity, such as default in debt and bonds, has led to the spread of bankruptcies, such as Lehman Brothers in 2008. Using the data for the ETFs of the S&P 500, Nasdaq 100, and Dow Jones Industrial Average collected from Yahoo Finance, this study implemented Deep Learning, Neuro Network, and Time-series to analyze the trend of the American Stock Market in the post-COVID-19 period. LSTM model in Neuro Network to predict the future trend, which suggests the US stock market keeps falling for the post-COVID-19 period. This study reveals a reasonable allocation method of Long Short-Term Memory for which there is strong evidence.

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Weilin Fu, Zhuoran Li, Yupeng Zhang, Xingyou Zhou. 2022-12-10. Time Series Analysis in American Stock Market Recovering in Post COVID-19 Pandemic Period. https://doi.org/10.47191/afmj%2Fv8i2.03

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