论文标题
设计可解释的动态饲料远期机器学习模型，以预测纳斯达克
Design interpretable experience of dynamical feed forward machine learning model for forecasting NASDAQ
论文作者
论文摘要
国家证券交易商协会自动报价（NASDAQ）是美国证券交易所。它是世界上最有价值的经济指数之一，位于纽约市\ cite {pagano2008 Quality}。股票市场的波动以及股票市场中的原油，黄金和美元等经济指标的影响，也受到了影响，并且具有动荡的和混乱的性质\ cite {firouzjaee20222lstm}。在这篇文章中，我们已经检查了油，金额和销售的效果，我们已经检查了油，金额和销售的效果，我们的销售效果是沃尔特的效果，我们的销售效果是沃尔特的效果，我们的销售效果是沃尔特的效果。这些指标在纳斯达克股票上。然后，我们开始分析反馈对纳斯达克股票过去价格的影响及其对当前价格的影响。使用PCA和线性回归算法，我们设计了用于建模这些库存的最佳动态学习经验。从定量分析中获得的结果与经济研究的定性分析的结果一致，并且使用机器学习的最佳动态体验进行的建模证明了纳斯达克股票的当前价格是合理的。
National Association of Securities Dealers Automated Quotations(NASDAQ) is an American stock exchange based. It is one of the most valuable stock economic indices in the world and is located in New York City \cite{pagano2008quality}. The volatility of the stock market and the influence of economic indicators such as crude oil, gold, and the dollar in the stock market, and NASDAQ shares are also affected and have a volatile and chaotic nature \cite{firouzjaee2022lstm}.In this article, we have examined the effect of oil, dollar, gold, and the volatility of the stock market in the economic market, and then we have also examined the effect of these indicators on NASDAQ stocks. Then we started to analyze the impact of the feedback on the past prices of NASDAQ stocks and its impact on the current price. Using PCA and Linear Regression algorithm, we have designed an optimal dynamic learning experience for modeling these stocks. The results obtained from the quantitative analysis are consistent with the results of the qualitative analysis of economic studies, and the modeling done with the optimal dynamic experience of machine learning justifies the current price of NASDAQ shares.
