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Stock Prices Analysis and Forecasting
  • Elham albaroudi
Elham albaroudi
Elham albaroudi

Corresponding Author:[email protected]

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Abstract

Stock Expectation plays a crucial part in fund and  financial matters. Numerous individuals contribute billions of  monetary standards on the stocks anticipating the benefit after  every single stock is obtained. Depending on the behavior of  advertising there are ups and downs within the benefit, so the  issue of quick and exact estimating of share cost becomes vital.  Such a prediction may be enhanced by using Machine and Deep  Learning, and this dissertation proposes a novel strategy for  predicting stock cost, oil, and gold forecast based on profound  learning and outfit learning strategies. Therefore, this  dissertation assesses and describes the following two types of  frequently used models: Economic Factors in Standard Time  Series based on various approaches and features. Previous  studies attempted to forecast future gold and prices using  previous data and Structural Models which attempt to explain  the links between oil and gold prices about a range of economic  considerations using machine learning models: SVM, Random  Forest, Linear Regression, Random Forest Regression, and  LSTM. These predictions are based on the sliding window  technique and try to implement such a system and apply it for  forecasting using oil and gold time series. By using Machine and  Deep Learning methods, more accurate forecasting in stock  prices may be obtained and this dissertation sought to answer the  following questions about this general premise: What is the effect  of the major oil and company financial results on future price?  What is the effect between oil and price and how that will affect  the gold future price? What is the coloration between US prices  and the stock market? How will natural disasters, disease, and  wars affect oil, and gold prices? The accompanying  macroeconomic variables were utilized which are S&P 500 List,  New York Stock Trade List (NYSE), and US Dollar List and  Consumer Feeling Record (CSI). Findings that NYSE is affected  a positive strong correlation on oil price while oil price affects  positive strong correlation on the gold price. Also, USD affects a  strong negative correlation with the stock market (oil and gold).  Finally, by analyzing the increase and decrease in oil prices from  OPEC, an indirect relationship was discovered.