Market Data Dashboard

This project visualizes market data using candlestick charts and order book depth information. It is built using Highcharts and JavaScript, and it processes CSV datasets to display financial data interactively.

Features

1. Candlestick Chart:

   • Displays open, high, low, and close prices for each minute.
   • Includes a range selector for 15 minutes, 1 hour, or the full dataset.

2. Volume Chart:

   • Shows the trading volume for each minute below the candlestick chart.

3. Order Book Depth Tooltip:

   • Displays buy and sell order book depth data for the hovered candlestick.
   • Data is shown in a tabular format with price levels and quantities.

File Structure

• index.html: The main HTML file that sets up the structure of the dashboard.
• styles.css: Contains styles for the dashboard layout and appearance.
• script.js: Handles data processing, chart rendering, and interactivity.
• data/: Contains CSV files with market data.

How to Use

1. Setup:

   • Ensure you have a web server to serve the files (e.g., using VS Code Live Server or Python's http.server).

2. Load the Dashboard:

   • Open index.html in a browser.

3. Select Dataset:

   • Use the dropdown menu to select a dataset from the data/ folder.

4. Interact with the Charts:

   • Hover over candlesticks to view order book depth data in the tooltip.
   • Use the range selector to adjust the visible time range.

Dataset Format

The CSV files should have the following columns:

• _id: Unique identifier for the row.
• tradingSymbol: The trading symbol of the instrument.
• openPrice, highPrice, lowPrice, closePrice: OHLC data for the minute.
• bidDepth.<price>: Buy order quantities at specific price levels.
• askDepth.<price>: Sell order quantities at specific price levels.
• timeStamp: Timestamp for the minute (e.g., 2025-02-24 09:48:00).
• volume: Total trading volume for the minute.

Dependencies

• Highcharts: Used for rendering the charts.

Notes

• The project assumes the dataset contains data for a single trading day.
• Invalid timestamps in the dataset are skipped, and a warning is logged in the console.

Future Improvements

• Add support for multiple trading days.
• Enhance the tooltip to include more detailed analytics.
• Optimize performance for larger datasets.