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TSLA Financial Market Daily Data
Stock & Market Data
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About
The daily historical stock prices for TESLA Inc. over a five-year period. It is designed to provide analysts, investors, and enthusiasts with critical financial metrics necessary for studying market volatility, identifying long-term growth patterns, and developing predictive models related to one of the world's most dynamic companies.
Columns
- Date: The trading date associated with the stock activity.
- Open: The starting price of the Tesla stock for the specified date.
- High: The highest price point the Tesla stock reached during the trading day.
- Low: The lowest price point the Tesla stock reached during the trading day.
- adj Close: The adjusted closing price of the stock, which accounts for corporate actions such as dividends, stock splits, and new stock offerings.
- Volume: The total amount of Tesla stock that was traded hands during the course of the trading day.
Distribution
The historical stock data is provided in a seven-column structure and is typically delivered as a CSV file. While the full five-year dataset size is larger, the provided sample data contains 251 valid daily trading records. The data is time-series in nature, tracking daily price fluctuations.
Usage
Ideal applications include time series analysis and modelling, particularly using methods such as CNNs (Convolutional Neural Networks) and LSTMs (Long Short-Term Memory networks). The data is excellent for deep learning projects focused on financial prediction, back-testing trading strategies, and analysing market behaviour across various economic cycles.
Coverage
The data covers the historical stock performance of Tesla, Inc., spanning the last five years. The sampled period ranges from 22 June 2022 to 21 June 2023. The scope is global financial market activity related to the Nasdaq-listed corporation. The data records daily trading metrics for this entire period.
License
CC0: Public Domain
Who Can Use It
- Investors: To track and analyse past performance for future investment decision-making.
- Financial Researchers: To study market efficiency and stock volatility.
- Data Scientists: To train and test predictive models for stock price forecasting.
- Students: To learn and apply techniques in business intelligence and quantitative finance.
Dataset Name Suggestions
- Tesla Historical Stock Prices (5 Years)
- TSLA Financial Market Daily Data
- Tesla Stock Performance Trends
Attributes
Original Data Source: TSLA Financial Market Daily Data
QUALITY