Time Series Analysis with Apple stock price Forecasting(November 29)

Why don’t we do something more intriguing now that we have a firm understanding of time series? For those who share my curiosity, stocks offer a captivating experience with their charts, graphs, green and red tickers, and numbers. But, let’s review our understanding of stocks before we get started.

• What is a Stock? A stock represents ownership in a company. When you buy a stock, you become a shareholder and own a portion of that company.
• Stock Price and Market Capitalization: The stock price is the current market value of one share. Multiply the stock price by the total number of outstanding shares to get the market capitalization, representing the total value of the company.
• Stock Exchanges: Stocks are bought and sold on stock exchanges, such as the New York Stock Exchange (NYSE) or NASDAQ. Each exchange has its listing requirements and trading hours.
• Ticker Symbol: Each stock is identified by a unique ticker symbol. For example, Apple’s ticker symbol is AAPL.
• Types of Stocks:
  • Common Stocks: Represent ownership with voting rights in a company.
  • Preferred Stocks: Carry priority in receiving dividends but usually lack voting rights.
• Dividends: Some companies pay dividends, which are a portion of their earnings distributed to shareholders.
• Earnings and Financial Reports: Companies release quarterly and annual financial reports, including earnings. Positive earnings often lead to a rise in stock prices.
• Market Index: Market indices, like the S&P 500 or Dow Jones, track the performance of a group of stocks. They give an overall sense of market trends.
• Risk and Volatility: Stocks can be volatile, and prices can fluctuate based on company performance, economic conditions, or global events.
• Stock Analysis: People use various methods for stock analysis, including fundamental analysis (company financials), technical analysis (historical stock prices and trading volume), and sentiment analysis (public perception).
• yfinance: yfinance is a Python library that allows you to access financial data, including historical stock prices, from Yahoo Finance.
• Stock Prediction Models: Machine learning models, time series analysis, and statistical methods are commonly used for stock price prediction. Common models include ARIMA, LSTM, and linear regression.
• Risks and Caution: Stock trading involves risks. It’s essential to diversify your portfolio, stay informed, and consider seeking advice from financial experts.

When working with stock data using the yfinance library in Python, the dataset typically consists of historical stock prices and related information.