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.
翻译:每场金融危机都对全球经济造成双重冲击。 市场流动性的短缺(如债务和债券违约)导致了破产的蔓延,如2008年雷曼兄弟公司(Lehman Brothers)的破产。 这项研究利用从雅虎金融公司收集的S & P 500、Nasdaq 100和Dow Jones工业平均指数数据,运用了深入学习、Neuro网络和时间序列来分析后COVID-19时期美国股票市场的趋势。 内罗网络的LSTM模型来预测未来趋势,这表明美国股票市场在后COVID-19时期持续下跌。 这项研究揭示了有确凿证据的长期短期记忆的合理分配方法。