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.

石油公司是世界上最大的公司之一，其经济指标在全球股票市场对世界经济和市场产生了很大影响，由于与黄金，原油和美元的关系。为了量化这些关系，我们使用相关特征和美元之间的关系，原油，黄金和主要石油公司库存指标，我们创建数据集，并比较预测的结果与真实数据。为了预测不同公司的股票，我们使用经常性的神经网络（RNN）和LSTM，因为这些股票在时间序列中变化。我们继续进行实证实验，并在库存指数上执行数据集，以评估几个常见的误差度量（如均方误差（MSE），平均绝对误差（MAE），根均方误差（RMSE）和均值的预测性能绝对百分比错误（MAPE）。所接受的结果是有前途的，并在不久的将来对石油公司股票价格相当准确的预测。结果表明，RNN没有可解释性，并且我们无法通过添加任何相关数据来改进模型。