Dataset Description:
This dataset provides historical stock price data for selected ticker symbols ['AAPL', 'MSFT', 'JPM', 'GS', 'AMZN', 'PG', 'KO', 'JNJ', 'XOM', 'CAT'] from January 1, 2014, to December 31, 2023. It contains the daily opening, highest, lowest, closing, adjusted closing prices, and trading volume for each trading day. These tickers represent a diverse range of sectors to allow comprehensive financial analysis.
Purpose and Use Case:
This dataset is ideal for financial analysis, market trend assessments, and investment decision-making. Analysts and researchers can use this dataset to:
- Analyze price and market trends.
- Evaluate volatility by analyzing price fluctuations and trading volume.
- Use historical price movements to forecast and predict future trends.
- Assess investment opportunities and portfolio performance.
Acknowledgments:
Data was collected using Python and Yahoo Finance. This dataset supports visualization, exploratory data analysis (EDA), and in-depth analysis to develop a predictive model for forecasting stock prices, aiming to gain insights, identify patterns, and improve prediction accuracy.
Potential Research Questions and Inspiration:
- What is the correlation between stock prices and trading volume over time?
- How do corporate actions and adjustments affect adjusted closing prices?
- How does volatility vary across different stocks and sectors?
- What key factors influence stock price dynamics, such as earnings reports, industry news, regulatory changes, or global economic trends?