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Investment Database Schema

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Here’s an HTML outline of an investment database schema, focusing on core entities and relationships. “`html

Investment Database Schema

A well-designed database schema is crucial for efficiently managing and analyzing investment data. This outline details a common schema, focusing on key entities and their relationships.

Entities

  • Investor

    Represents individuals or institutions who invest. Attributes include:

    • investor_id (INT, PRIMARY KEY): Unique identifier for the investor.
    • name (VARCHAR): Name of the investor.
    • investor_type (ENUM: ‘Individual’, ‘Institutional’): Type of investor.
    • address (VARCHAR): Physical address of the investor.
    • contact_email (VARCHAR): Email address for communication.
  • Security

    Represents a financial instrument traded on the market. Attributes include:

    • security_id (INT, PRIMARY KEY): Unique identifier for the security.
    • ticker_symbol (VARCHAR): Stock ticker symbol (e.g., AAPL).
    • security_name (VARCHAR): Full name of the security (e.g., Apple Inc.).
    • security_type (ENUM: ‘Stock’, ‘Bond’, ‘Mutual Fund’, ‘ETF’): Type of the security.
    • isin (VARCHAR): International Securities Identification Number.
    • cusip (VARCHAR): Committee on Uniform Securities Identification Procedures number.
  • Transaction

    Represents a buy or sell order placed by an investor. Attributes include:

    • transaction_id (INT, PRIMARY KEY): Unique identifier for the transaction.
    • investor_id (INT, FOREIGN KEY referencing Investor.investor_id): Investor making the transaction.
    • security_id (INT, FOREIGN KEY referencing Security.security_id): Security being traded.
    • transaction_date (DATE): Date of the transaction.
    • transaction_type (ENUM: ‘Buy’, ‘Sell’): Type of transaction.
    • quantity (INT): Number of shares/units traded.
    • price (DECIMAL): Price per share/unit at the time of the transaction.
    • commission (DECIMAL): Commission paid for the transaction.
  • MarketData

    Represents historical pricing data for a security. Attributes include:

    • market_data_id (INT, PRIMARY KEY): Unique identifier.
    • security_id (INT, FOREIGN KEY referencing Security.security_id): Security the data pertains to.
    • date (DATE): Date of the market data.
    • open_price (DECIMAL): Opening price for the day.
    • high_price (DECIMAL): Highest price for the day.
    • low_price (DECIMAL): Lowest price for the day.
    • close_price (DECIMAL): Closing price for the day.
    • volume (BIGINT): Volume of shares traded.
  • Portfolio

    Represents a collection of securities held by an investor. Attributes include:

    • portfolio_id (INT, PRIMARY KEY): Unique identifier.
    • investor_id (INT, FOREIGN KEY referencing Investor.investor_id): Investor owning the portfolio.
    • portfolio_name (VARCHAR): Name of the portfolio (e.g., “Retirement Fund”).
    • creation_date (DATE): Date the portfolio was created.
  • PortfolioHolding

    Links portfolios to securities and their quantities.

    • portfolio_id (INT, FOREIGN KEY referencing Portfolio.portfolio_id): The Portfolio ID.
    • security_id (INT, FOREIGN KEY referencing Security.security_id): The Security ID.
    • quantity (INT): Number of shares/units held in the portfolio.
    • average_cost (DECIMAL): Average cost basis for the holding.
    • PRIMARY KEY (portfolio_id, security_id): Composite key for uniqueness.

Relationships

  • One-to-many relationship between Investor and Transaction (one investor can have multiple transactions).
  • One-to-many relationship between Security and Transaction (one security can be involved in multiple transactions).
  • One-to-many relationship between Security and MarketData (one security has multiple market data points).
  • One-to-many relationship between Investor and Portfolio (one investor can have multiple portfolios).
  • Many-to-many relationship between Portfolio and Security, resolved through the PortfolioHolding entity.

Considerations

This schema is a starting point and can be expanded to include other relevant data, such as company financials, analyst ratings, and economic indicators. Indexing strategies are critical for performance. Data validation and integrity constraints should be implemented to ensure data quality.

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