The stock market is the process of buying and selling stocks between stock buyers and sellers, which represents a claim of ownership in a business, this may include securities listed on public stock exchanges, as well as stocks that are traded privately, such as shares of private companies sold to investors through equity crowdfunding platforms. Investing in the stock market is most commonly done through stock brokers and electronic trading platforms. Investments are usually made with an investment strategy in mind.
Stock prediction is always a challenging issue for statisticians and finance experts. The main reason behind this prediction is to buy stocks that are likely to rise in price and then sell stocks that may fall. Generally, there are two ways to predict the stock market. Fundamental analysis is one of them and depends on company techniques and basic information such as market position, costs, and annual growth rates. The second is the technical analysis method, which focuses on previous stock prices and values.
In the first part of the project, we will try to analyze stock data for Google, Microsoft, Amazon, and IBM in the range from 2006 to 2018. And in the second part, we will create a system to predict the stock market.
The dataset used can be downloaded from this link.
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Data Analysis:
- Visualize the distribution of closing and opening prices.
- Identify the correlation between closing and opening prices.
- Compare attributes such as [Open, High, Low, Close, Volume].
- Detect trends and seasonality in the data.
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Stock Market Prediction:
- Use the GRU model to predict future stock prices.