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Global Currency-Linked Stock Pricing and Volume Records
Stock & Market Data
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About
Tracking the financial fluctuations of the Euro and US Dollar stock markets offers a detailed perspective on global economic shifts over nearly a decade and a half. This collection provides both raw and preprocessed figures sourced from Yahoo Finance, capturing the daily pricing and trading activity necessary for advanced financial analysis. It serves as a vital foundation for understanding market volatility and the various factors that influence currency-denominated stock performance during significant historical periods. By offering a large volume of training examples, the data helps researchers explore how to create reliable stock indications and predictions in a real-world context.
Columns
- Date: The specific calendar day, month, and year for the recorded stock market activity.
- Open: The starting price of the stock at the commencement of the trading session.
- High: The maximum price reached by the stock during the duration of the trading session.
- Low: The minimum price at which the stock was traded during market hours.
- Close: The final transaction price recorded at the end of the trading day.
- Volume: The total number of shares, futures, or options traded during the session, serving as a key indicator of market liquidity.
Distribution
The information is delivered in two primary CSV files:
Entire.csv, which contains the raw data before any adjustments, and NewDataEntire.csv, which is specifically structured for time series forecasting. The raw file is approximately 51.33 MB in size and consists of roughly 940,000 valid records. The dataset maintains a 100% validity rate with no missing or mismatched entries across its six main columns. This is a static archive with a usability score of 10.00 and no future updates are expected.Usage
This resource is tailor-made for developing and testing sophisticated predictive algorithms, particularly Recurrent Neural Networks (RNN) and Long Short-Term Memory (LSTM) models. Analysts can utilise the training examples to calculate Mean Squared Error (MSE) metrics and refine their forecasting accuracy. It is also suitable for back-testing trading strategies, performing longitudinal studies on market trends, and investigating the correlations between European and American equity markets.
Coverage
The geographic scope is international, focusing on the Euro and US Dollar-denominated stock exchanges. Temporally, the records provide a continuous timeline from 1 January 2007 to 23 January 2021. This fourteen-year span covers major global economic cycles, providing a robust historical backdrop for financial modelling and academic research.
License
CC0: Public Domain
Who Can Use It
Algorithmic traders and quantitative analysts can leverage these figures to build and validate their automated market prediction tools. Data scientists interested in financial time series will find the preprocessed training examples ideal for machine learning applications. Additionally, academic researchers and students in finance or economics can use the structured records to explore market behaviour and the historical performance of major currencies.
Dataset Name Suggestions
- Euro and USD Stock Market Time Series (2007–2021)
- Yahoo Finance: Euro-USD Equities Historical Archive
- Preprocessed Stock Market Training Data for RNN and LSTM
- Global Currency-Linked Stock Pricing and Volume Records
- Fourteen Years of Euro and USD Financial Market Metrics
Attributes
Original Data Source: Global Currency-Linked Stock Pricing and Volume Records
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