U.S. Economic and Financial Dataset

Dataset Description

This dataset combines historical U.S. economic and financial indicators, spanning the last 50 years, to facilitate time series analysis and uncover patterns in macroeconomic trends. It is designed for exploring relationships between interest rates, inflation, economic growth, stock market performance, and industrial production.

Key Features

• Frequency: Monthly
• Time Period: Last 50 years from Nov-24
• Sources:
  • Federal Reserve Economic Data (FRED)
  • Yahoo Finance

Dataset Feature Description

1. Interest Rate (Interest_Rate):

   • The effective federal funds rate, representing the interest rate at which depository institutions trade federal funds overnight.

2. Inflation (Inflation):

   • The Consumer Price Index for All Urban Consumers, an indicator of inflation trends.

3. GDP (GDP):

   • Real GDP measures the inflation-adjusted value of goods and services produced in the U.S.

4. Unemployment Rate (Unemployment):

   • The percentage of the labor force that is unemployed and actively seeking work.

5. Stock Market Performance (S&P500):

   • Monthly average of the adjusted close price, representing stock market trends.

6. Industrial Production (Ind_Prod):

   • A measure of real output in the industrial sector, including manufacturing, mining, and utilities.

Dataset Statistics

1. Total Entries: 599
2. Columns: 6
3. Memory usage: 37.54 kB
4. Data types: float64

Feature Overview

• Columns:
  • Interest_Rate: Monthly Federal Funds Rate (%)
  • Inflation: CPI (All Urban Consumers, Index)
  • GDP: Real GDP (Billions of Chained 2012 Dollars)
  • Unemployment: Unemployment Rate (%)
  • Ind_Prod: Industrial Production Index (2017=100)
  • S&P500: Monthly Average of S&P 500 Adjusted Close Prices

Executive Summary

This project explores the interconnected dynamics of key macroeconomic indicators and financial market trends over the past 50 years, leveraging data from the Federal Reserve Economic Data (FRED) and Yahoo Finance. The dataset integrates critical variables such as the Federal Funds Rate, Inflation (CPI), Real GDP, Unemployment Rate, Industrial Production, and the S&P 500 Index, providing a holistic view of the U.S. economy and financial markets.

The analysis focuses on uncovering relationships between these variables through time-series visualization, correlation analysis, and trend decomposition. Key findings are included in the Insights section. This project serves as a robust resource for understanding long-term economic trends, policy impacts, and market behavior. It is particularly valuable for students, researchers, policymakers, and financial analysts seeking to connect macroeconomic theory with real-world data.

Potential Use Cases

• Economic Analysis: Examine relationships between interest rates, inflation, GDP, and unemployment.
• Stock Market Prediction: Study how macroeconomic indicators influence stock market trends.
• Time Series Modeling: Perform ARIMA, VAR, or other models to forecast economic trends.
• Cyclic Pattern Analysis: Identify how economic shocks and recoveries impact key indicators.

Snap of Power Analysis

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To ensure sufficient power, the dataset covers last 50 years of monthly data i.e., around 600 entries.

Key Insights derived through EDA, time-series visualization, correlation analysis, and trend decomposition

• Interest Rate and Inflation Dynamics: The interest Rate and inflation exhibit an inverse relationship, especially during periods of aggressive monetary tightening by the Federal Reserve.
• Economic Growth and Market Performance: GDP growth and the S&P 500 Index show a positive correlation, reflecting how market performance often aligns with overall economic health.
• Labor Market and Industrial Output: Unemployment and industrial production demonstrate a strong inverse relationship. Higher industrial output is typically associated with lower unemployment
• Market Behavior During Economic Shocks: The S&P 500 experienced sharp declines during significant crises, such as the 2008 financial crash and the COVID-19 pandemic in 2020. These events also triggered increased unemployment and contractions in GDP, highlighting the interplay between markets and the broader economy.
• Correlation Highlights: S&P 500 and GDP have a strong positive correlation. Interest rates negatively correlate with GDP and inflation, reflecting monetary policy impacts. Unemployment is negatively correlated with industrial production but positively correlated with interest rates.

Link to GitHub Repo

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This stock market dataset is designed for financial analysis and predictive modeling. It includes historical stock prices, technical indicators, macroeconomic factors, and sentiment scores to help in developing and testing machine learning models for stock trend prediction.

Dataset Features: Column Description Stock Random stock ticker (AAPL, GOOG, etc.) Date Random business date Open Open price High High price Low Low price Close Close price Volume Trading volume SMA_10 10-day Simple Moving Average RSI Relative Strength Index (10-90 range) MACD MACD indicator (-5 to 5) Bollinger_Upper Upper Bollinger Band Bollinger_Lower Lower Bollinger Band GDP_Growth Random GDP growth rate (2.5% to 3.5%) Inflation_Rate Inflation rate (1.5% to 3.0%) Interest_Rate Interest rate (0.5% to 5.0%) Sentiment_Score Random sentiment score (-1 to 1) Next_Close Next day's closing price (for regression) Target Binary classification (1: Price Increase, 0: Price Decrease)

Key Features: Stock Prices: Open, High, Low, Close, and Volume data. Technical Indicators: Simple Moving Average (SMA), Relative Strength Index (RSI), MACD, and Bollinger Bands. Macroeconomic Factors: Simulated GDP growth, inflation rate, and interest rates. Sentiment Scores: Randomized sentiment values between -1 and 1 to simulate market sentiment. Target Variables: Next-day close price (for regression) and price movement direction (for classification).

The benchmark interest rate in India was last recorded at 5.50 percent. This dataset provides - India Interest Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Disclaimer

This dataset was compiled from publicly available financial data sourced from Yahoo Finance for research and educational purposes only. Redistribution of raw data may be subject to Yahoo Finance’s terms of service. Users are responsible for complying with all applicable data usage policies and regulations.

Description

This dataset contains two CSV files for companies listed on the London Stock Exchange (next, LSE) * raw_financial_metrics_2025_march.csv - latest available financial data (as of March 2025) including metrics such as revenue, net income, P/E ratio, total debt, market capitalisation and industry classification. * historical_stock_prices_2015_2025.csv - 10 years of daily closing stock prices (2015 April 1st - 2025 March 28) for the same set of companies

The dataset is designed to support: * Financial valuation research * Time-series forecasting (e.g., LSTM ARIMA) * Multi-modal learning (e.g., combining static metrics and price trends) * Exploratory analysis by sector, market capitalisation, etc.

Columns Overview

Financial Metrics:

General Company Information

• Ticker: Unique stock symbol used to identify the company on the stock exchange.
• Name: Full name of the company.
• Website: Official company website.
• Address, City, Postcode, Country: Headquarters location details.
• Exchange: Stock exchange where the company is listed (e.g. LSE for London Stock Exchange).

Market & Share Information

• Market Cap: Total market value of a company’s outstanding shares.
• Shares Outstanding: Total number of shares currently issued and held by shareholders.
• Float Shares: Shares available for public trading (excludes insider holdings).

Stock Performance

• Regular Market Price: Latest trading price during regular market hours.
• Regular Market Change / (%): Absolute and percentage change in price from the previous trading day.
• 50 Day Average / 200 Day Average: Average stock prices over the past 50 and 200 days, respectively.
• 52 Week Change: Percentage change in stock price over the past year.
• 52 Week High / Low: Highest and lowest stock prices over the past year.

Valuation Ratios

• Enterprise to Revenue / EBITDA: Valuation multiples showing how the company is priced relative to its revenue or earnings before interest, taxes, depreciation, and amortization.
• P/E Ratio (Price-to-Earnings): Valuation based on earnings per share.
• P/B Ratio (Price-to-Book): Compares market value to book value.
• Price to Sales (TTM): Market cap divided by total sales over the trailing twelve months.
• PEG Ratio: Price/Earnings ratio adjusted for expected earnings growth.

Financial Strength

• Book Value: Total company equity per share.
• Beta: A Measure of stock volatility relative to the market.
• Debt-to-Equity Ratio: Leverage ratio comparing total debt to shareholder equity.
• Quick Ratio / Current Ratio: Liquidity indicators for meeting short-term obligations.

Cash Flows & Liquidity

• Operating Cash Flow: Cash generated from core business operations.
• Free Cash Flow: Cash available after capital expenditures.
• Total Cash: The Company’s total cash reserves.
• Total Debt: Total liabilities in the form of debt.
• Current Total Assets: Total assets expected to be converted into cash within a year.
• Total Cash Per Share: Cash reserves divided by the number of outstanding shares.

Earnings & Profitability

• Gross Profits: Revenue minus cost of goods sold.
• EBITDA: Earnings before interest, taxes, depreciation, and amortization.
• Operating Margins / Profit Margins: Efficiency and profitability ratios.
• Forward EPS / Trailing EPS: Projected vs actual earnings per share.
• Earnings Quarterly Growth: Year-over-year change in earnings.
• Revenue Growth: Year-over-year change in revenue.

Dividends

• Dividend Rate: Annual dividend per share.
• Dividend Yield: Dividend as a percentage of the share price.
• Payout Ratio: Proportion of earnings paid out as dividends.

Analyst Sentiment

• Recommendation: Consensus recommendation from financial analysts (e.g., Buy, Hold, Sell).
• Recommendation Mean: Average numerical value of analyst ratings (lower means more favorable).
• Number of Analyst Opinions: Number of analyst reports used to generate recommendation scores.

Stock Prices

• Company Name - the name of the company
• Date (daily) - the dates in the "yyyy-mm-dd" format

Potential Use Cases

• Stock price prediction
• Deep learning models combining tabular and time-series data
• Graham-style intrinsic value estimation
• Sector-wise performance benchmarking
• Feature engineering and data preprocessing experiments

Inspiration

This dataset was created as part of a Data Science research project exploring the use of financial fundamentals and historical price movements to evaluate company value and predict future performance.

Context

Tesla, Inc. is an American company that manufactures and sells electric cars, as well as power storage and photovoltaic systems. The company's goal is to “accelerate the transition to sustainable energy”. The company name is based on the physicist and inventor Nikola Tesla.

Market cap

Market capitalization of Tesla (TSLA)

Market cap: $1.082 Trillion USD

As of February 2025 Tesla has a market cap of $1.082 Trillion USD. This makes Tesla the world's 9th most valuable company by market cap according to our data. The market capitalization, commonly called market cap, is the total market value of a publicly traded company's outstanding shares and is commonly used to measure how much a company is worth.

Revenue

Revenue for Tesla (TSLA)

Revenue in 2024 (TTM): $97.69 Billion USD

According to Tesla's latest financial reports the company's current revenue (TTM ) is $97.69 Billion USD. an increase over the revenue in the year 2023 that were of $96.77 Billion USD. The revenue is the total amount of income that a company generates by the sale of goods or services. Unlike with the earnings no expenses are subtracted.

Earnings

Earnings for Tesla (TSLA)

Earnings in 2024 (TTM): $9.34 Billion USD

According to Tesla's latest financial reports the company's current earnings are $97.69 Billion USD. a decrease over its 2023 earnings that were of $10.12 Billion USD. The earnings displayed on this page are the earnings before interest and taxes or simply EBIT.

End of Day market cap according to different sources

On Feb 12th, 2025 the market cap of Tesla was reported to be:

• $1.082 Trillion USD by Yahoo Finance

• $1.082 Trillion USD by CompaniesMarketCap

• $1.082 Trillion USD by Nasdaq

Content

Geography: USA

Time period: June 2010- February 2025

Unit of analysis: Tesla Stock Data 2025

Variables

Acknowledgements

This dataset belongs to me. I’m sharing it here for free. You may do with it as you wish.

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The benchmark interest rate in Philippines was last recorded at 4.75 percent. This dataset provides the latest reported value for - Philippines Interest Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Gold fell to 4,199.97 USD/t.oz on December 2, 2025, down 0.75% from the previous day. Over the past month, Gold's price has risen 4.93%, and is up 58.92% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Gold - values, historical data, forecasts and news - updated on December of 2025.

Sri Lanka's main stock market index, the ASPI, closed flat at 22022 points on December 2, 2025. Over the past month, the index has declined 3.95%, though it remains 66.30% higher than a year ago, according to trading on a contract for difference (CFD) that tracks this benchmark index from Sri Lanka. Sri Lanka Stock Market (CSE All Share) - values, historical data, forecasts and news - updated on December of 2025.