Dark Mode
Google Market Performance Dataset
Stock & Market Data
Tags and Keywords
Trusted By
"No reviews yet"
Free
About
Google stock data from 2010 to 2023 is available in this dataset, crafted for training machine learning and deep learning models. It comprises historical stock price information, provided in two CSV files for distinct training and evaluation purposes. Each row within the dataset details a specific trading day, offering a selection of relevant information pertaining to Google's stock performance on that day. This data is excellent for predicting future stock prices, analysing historical market trends, and developing financial forecasting models.
Columns
- Date: The specific trading day, formatted as "YYYY-MM-DD".
- Open: The initial price of Google's stock at the beginning of the trading day.
- High: The peak price achieved by Google's stock during the trading day.
- Low: The lowest price observed for Google's stock during the trading day.
- Close: The final price of Google's stock at the close of the trading day.
- Adj Close: The adjusted closing price, which takes into account any corporate actions such as stock splits or dividends that could influence the stock's value.
- Volume: The total number of shares traded on that particular trading day.
Distribution
The dataset is provided in CSV (Comma Separated Values) format and includes two separate files: one for training and one for testing. The training dataset encompasses daily stock price information spanning twelve years, from 1st January 2010 to 31st December 2022. The test dataset covers seven months of daily stock price data, from 1st January 2023 to 30th July 2023, for model evaluation. For the test dataset, individual columns like Low, Close, Adj Close, and Volume each contain 143 valid records, with no mismatched or missing values. The 'Google_Stock_Test (2023).csv' file is approximately 10.54 kB in size. Each row uniformly represents a single trading day's data.
Usage
This dataset is ideally suited for a variety of applications, including:
- Predicting future stock prices: Utilise historical data to forecast market movements.
- Analysing historical stock trends: Examine past patterns to understand market behaviour.
- Building machine learning models for financial forecasting: Develop robust models to predict stock performance.
- Time Series Analysis: Explore stock price patterns and identify seasonal variations.
- Financial Modelling: Create predictive models to anticipate stock price changes.
- Algorithmic Trading: Formulate trading strategies based on past stock data.
- Risk Management: Evaluate potential risks and volatilities within the stock market.
Coverage
The dataset focuses on Google's stock performance. The time range for the training dataset extends from 1st January 2010 to 31st December 2022, providing over a decade of daily information. The test dataset covers the period from 1st January 2023 to 30th July 2023. The data was collected from Yahoo Finance (finance.yahoo.com), a widely recognised financial data platform. There are no specific demographic notes as the data pertains to corporate stock performance.
License
Creative Commons CC0 1.0 Universal (CC0 1.0) Public Domain
Who Can Use It
Intended users of this dataset include:
- Machine learning practitioners and data scientists: For developing and assessing machine learning and deep learning models.
- Financial analysts: To predict future stock prices and analyse past market trends.
- Quantitative traders: To design and implement algorithmic trading strategies.
- Researchers and academics: For studies in time series analysis and financial modelling.
- Risk managers: To assess and mitigate financial risks and market volatilities.
Dataset Name Suggestions
- Google Stock Prices 2010-2023
- Historical Google Stock Data for ML
- Alphabet Inc. Daily Stock Prices
- Google Market Performance Dataset
- Stock Price Analysis: Google
Attributes
Original Data Source: Google Market Performance Dataset
QUALITY