Key-Features.txt

##Key Features for Stock Price Prediction:
    To build a robust stock price prediction model, We need to gather and engineer relevant features.  
    some common and useful features:

1. Historical Price Data
       -: Open, High, Low, Close Prices: Historical data on stock prices at different times of the day.
       -: Volume: Number of shares traded.

2. Technical Indicators
        -:Moving Averages: Simple Moving Average (SMA), Exponential Moving Average (EMA).
        -:Relative Strength Index (RSI): Indicates overbought or oversold conditions.
        -:Moving Average Convergence Divergence (MACD): Shows the relationship between two moving averages.
        -:Bollinger Bands: Indicates volatility and potential price reversals.
        -:Stochastic Oscillator: Compares a particular closing price of a security to a range of its prices over a certain period.
3. Fundamental Data
        -:Earnings per Share (EPS)
        -:Price-to-Earnings (P/E) Ratio
        -:Dividend Yield
        -:Book Value
4. Market Sentiment
        -:News Sentiment: Positive or negative sentiment from financial news.
        -:Social Media Sentiment: Sentiment analysis from platforms like Twitter, Reddit.
5. Macroeconomic Indicators
        -:Interest Rates
        -:GDP Growth Rate
        -:Inflation Rate
        -:Unemployment Rate
6. Other Features
        -:Sector Performance: Performance of the sector the stock belongs to.
        -:Company Events: Announcements, earnings reports, mergers and acquisitions.