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).

🇺🇸 Alphabet Inc. (GOOGL) Comprehensive Financial Dataset

📌 Overview

Welcome to the GOOGL Financial Dataset! This dataset provides clear and easy-to-use quarterly financial statements (income statement, balance sheet, and cash flow) along with daily historical stock prices.

As a data engineer double majored with economics, I'll personally analyze and provide constructive feedback on all your work using this dataset. Let's dive in and explore Google's financial journey together!

🗃 Files Included

• googl_daily_prices.csv: Historical daily stock prices.
• googl_income_statement.csv: Quarterly income statements.
• googl_balance_sheet.csv: Quarterly balance sheets.
• googl_cash_flow_statement.csv: Quarterly cash flow statements.

📘 About This Dataset

This dataset offers a unique blend of long-term market performance and detailed financial metrics:

• Time Series of Daily Prices: Track the historical performance of GOOGL stock from its early days up until now.
• Quarterly Financial Statements: Dive into the income statements, balance sheets, and cash flow statements that reflect the company’s financial evolution.
• Integrated Insights: Ideal for comprehensive financial analyses, forecasting, model building, and exploring the dynamic interplay between market performance and underlying business operations.

Whether you're building predictive models, performing deep-dive financial analysis, or exploring the evolution of one of the world's most innovative tech giants, this dataset is your go-to resource for clean, well-organized, and rich financial data.

💡 Tips for Using the Dataset

• Visualize Stock Trends: Plot daily prices to quickly understand stock movements.
• Financial Analysis: Compare income, balance sheet, and cash flow data to spot financial trends and health.
• Predictive Modeling: Use this dataset to build forecasting models and predict future performance.
• Combine Data: Merge price data with financial statements to analyze relationships and uncover deeper insights.

🔗 Works Great with My GOOGL News Dataset!

For a more comprehensive financial analysis, pair this dataset with my other Kaggle dataset:
👉 Google (Alphabet Inc.) Daily News — 2000 to 2025

That dataset includes:

• Daily news articles from Finnhub
• Headlines, summaries, sources, and timestamps
• Covering GOOGL from 2000 to 2025

Combining both datasets unlocks powerful analysis such as:

• Correlating news sentiment with stock price movements
• Studying the impact of earnings reports and product launches
• Developing event-driven forecasting models

Together, they give you everything you need for news + financial signal modeling.

📝 Column Descriptions

📈 googl_daily_prices.csv

• date: Trading date.
• 1. open: Opening stock price on the trading day.
• 2. high: Highest stock price on the trading day.
• 3. low: Lowest stock price on the trading day.
• 4. close: Closing stock price on the trading day.
• 5. volume: Number of shares traded on the day.

📊 googl_income_statement.csv

• fiscalDateEnding: Date marking the end of fiscal quarter.
• reportedCurrency: Currency used in reporting (USD).
• grossProfit: Revenue minus the cost of goods sold.
• totalRevenue: Total income generated from operations.
• costOfRevenue: Direct costs attributable to the production of goods.
• costofGoodsAndServicesSold: Costs directly associated with goods sold.
• operatingIncome: Earnings after operating expenses deducted.
• sellingGeneralAndAdministrative: Administrative and general sales costs.
• researchAndDevelopment: Expenses related to research and innovation.
• operatingExpenses: Total operational costs.
• investmentIncomeNet: Net income from investments.
• netInterestIncome: Income earned from interest after deducting interest paid.
• interestIncome: Income generated from interest-bearing investments.
• interestExpense: Expenses from interest payments.
• nonInterestIncome: Income from non-interest-bearing activities.
• otherNonOperatingIncome: Additional income outside regular operations.
• depreciation: Reduction in value of assets over time.
• depreciationAndAmortization: Combined depreciation and amortization costs.
• incomeBeforeTax: Income before taxation.
• incomeTaxExpense: Taxes paid on earnings.
• interestAndDebtExpense: Interest paid on debts.
• netIncomeFromContinuingOperations: Profit from ongoing operations.
• comprehensiveIncomeNetOfTax: Income after comprehensive expenses.
• ebit: Earnings before interest and taxes.
• ebitda: Earnings before interest, taxes, depreciation, and...

Turkmenistan TM: External Debt: DOD: Stocks: Variable Rate data was reported at 143.055 USD mn in 2016. This records an increase from the previous number of 136.000 USD mn for 2015. Turkmenistan TM: External Debt: DOD: Stocks: Variable Rate data is updated yearly, averaging 110.903 USD mn from Dec 1970 (Median) to 2016, with 47 observations. The data reached an all-time high of 1.758 USD bn in 1999 and a record low of 0.000 USD mn in 1992. Turkmenistan TM: External Debt: DOD: Stocks: Variable Rate data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Turkmenistan – Table TM.World Bank: External Debt: Debt Outstanding, Debt Ratio and Debt Service. Variable interest rate is long-term external debt with interest rates that float with movements in a key market rate; for example, the London interbank offered rate (LIBOR) or the U.S. prime rate. This item conveys information about the borrower's exposure to changes in international interest rates. Long-term external debt is defined as debt that has an original or extended maturity of more than one year and that is owed to nonresidents by residents of an economy and repayable in currency, goods, or services. Data are in current U.S. dollars.; ; World Bank, International Debt Statistics.; Sum;

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.