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NSE-TATAGLOBAL Daily Stock Data
Stock & Market Data
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About
Historical stock market data for NSE-TATAGLOBAL over a five-year period. It contains essential financial metrics, offering a clear view into the company's daily stock performance. The information is suitable for analysing market trends and understanding price movements.
Columns
- Date: The specific calendar date of the trading activity.
- Open: The opening price of the share at the start of the trading day.
- High: The highest price at which the share traded during the day.
- Low: The lowest price at which the share traded during the day.
- Last: The final price recorded for the share at the very end of the trading day.
- Close: The closing price of the share when the market concluded for the day.
- Total Trade Quantity: The total volume of shares, indicating the number bought or sold on that particular day.
- Turnover (Lacs): The total turnover of the company on the given date, measured in Lacs.
Distribution
The dataset is presented in a CSV file format and consists of 1235 records across 8 distinct columns. The file size is approximately 75.1 KB. Each column is fully populated with no missing values.
Usage
This data is ideal for various applications, including financial modelling, time-series analysis, and back-testing trading strategies. It can be used for market trend identification, developing predictive stock price models, and exploring the application of machine learning techniques in finance. Data visualisation professionals will also find it valuable for creating insightful charts and graphs.
Coverage
The data covers the NSE-TATAGLOBAL stock performance for a five-year duration, specifically from 8 October 2013 to 8 October 2018. The scope is centred on the National Stock Exchange (NSE) in India, providing a focused view of a single company's equity.
License
CC0: Public Domain
Who Can Use It
- Financial Analysts: To track historical performance, identify patterns, and support investment decisions.
- Data Scientists: For building and testing machine learning models for stock price prediction and market anomaly detection.
- Academic Researchers: To study market efficiency, volatility, and other economic phenomena.
- Students: For educational projects related to finance, data analysis, and programming with financial data.
- Developers: To integrate historical stock data into financial applications or dashboards.
Dataset Name Suggestions
- NSE-TATAGLOBAL Daily Stock Data (2013-2018)
- TATAGLOBAL 5-Year Equity Performance (NSE)
- Indian Stock Market: TATAGLOBAL Historical Prices
- Financial Metrics: NSE-TATAGLOBAL Stock Analysis
Attributes
Original Data Source: NSE-TATAGLOBAL Daily Stock Data
QUALITY