NASDAQ Stock Data with Economic Indicators
Overview
This dataset comprises historical stock price data for NASDAQ-listed companies, combined with a selection of key economic indicators. It is designed to provide a comprehensive view of market behavior, facilitating financial analysis and predictive modeling. Users can explore relationships between stock performance and various economic factors.
Features
The dataset includes the following features:
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Date: The date of the recorded stock prices (formatted as YYYY-MM-DD).
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Open: The price at which the stock opened for trading on a given day.
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High: The highest price reached by the stock during the trading day.
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Low: The lowest price recorded during the trading day.
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Close: The price at which the stock closed at the end of the trading day.
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Volume: The total number of shares traded during the day.
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Interest Rate: The prevailing interest rate, which influences economic activity and stock performance.
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Exchange Rate: The exchange rate for the USD against other currencies, reflecting international market influences.
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VIX: The Volatility Index, a measure of market risk and investor sentiment, often referred to as the "fear index."
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Gold: The price of gold per ounce, which serves as a traditional safe-haven asset and is often inversely correlated with stock prices.
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Oil: The price of crude oil, an essential commodity that influences various sectors, especially transportation and manufacturing.
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TED Spread: The difference between the interest rates on interbank loans and short-term U.S. government debt, which indicates credit risk in the banking system.
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EFFR (Effective Federal Funds Rate): The interest rate at which depository institutions lend reserve balances to other depository institutions overnight, influencing overall economic activity.
Use Cases
This dataset is suitable for a variety of applications, including:
- Financial Analysis: Evaluate historical trends in stock prices relative to economic indicators.
- Predictive Modeling: Develop machine learning models to forecast stock price movements based on historical data and economic variables.
- Time Series Analysis: Conduct analyses over different time frames (daily, weekly, monthly, yearly) to identify patterns and anomalies.
Data Source
The data is sourced from reputable financial APIs and databases:
- Yahoo Finance: Historical stock prices.
- Federal Reserve Economic Data (FRED): Economic indicators such as interest rates and VIX.
- Alpha Vantage / Quandl: Commodity prices for gold and oil.
Conclusion
This dataset provides a rich foundation for analysts, researchers, and data scientists interested in the intersection of stock market performance and macroeconomic conditions. Its structured features and comprehensive nature make it a valuable resource for both academic and practical financial inquiries.