Catalogs API

Overview

The Catalogs API provides access to organized groupings of financial assets. These catalogs allow you to work with pre-defined collections such as ETFs, index components, leveraged pairs, sector groupings, and other asset categories. Using catalogs simplifies analysis across related financial instruments and enables sector or theme-based trading strategies.

Available Objects

Available Functions

Catalog Types

The Catalogs API supports various types of asset groupings:

1. ETFs - Exchange-Traded Funds and their component securities
2. Indices - Market indices (e.g., S&P 500, Nasdaq 100) and their constituent stocks
3. Leveraged Pairs - Related leveraged/inverse ETF combinations
4. Sectors - Industry sector groupings
5. Themes - Thematic collections (e.g., clean energy, cybersecurity)
6. Custom - User-defined groupings for specialized analysis

Getting Started

To begin working with asset catalogs:

1. Import the GoldenGoose library
2. Use list() to discover available catalogs
3. Use get() to retrieve data for specific catalogs
4. Access component assets and perform analytics on the catalog

Example

import goldengoose
 
# Get all available catalogs
available_catalogs = goldengoose.catalogs.list()
print(f"Available catalogs: {len(available_catalogs)}")
 
# Retrieve a specific catalog (e.g., S&P 500)
sp500 = goldengoose.catalogs.get("SPX")
 
# Print catalog information
print(f"Catalog: {sp500.name}")
print(f"Description: {sp500.description}")
print(f"Number of components: {len(sp500.components)}")
 
# Access component assets
for symbol in sp500.components[:5]:  # First 5 components
    print(f"Symbol: {symbol}")
    
    # Get detailed data for a component stock
    stock_data = goldengoose.stocks.get(symbol)
    current_epoch = goldengoose.get_current_epoch()
    current_price = stock_data[current_epoch].oneMinute.close
    
    print(f"  Current price: ${current_price}")

Use Cases

Sector Analysis

Compare performance metrics across industry sectors to identify relative strength and weakness.

ETF Component Analysis

Analyze the underlying holdings of ETFs to understand exposures and correlations.

Basket Trading

Execute orders across a group of related securities based on a catalog definition.

Thematic Research

Study market trends across themed groupings of assets.

Notes

• Catalogs are updated regularly to reflect changes in component securities
• Historical data shows the evolution of catalog compositions over time
• Custom catalogs can be created for specialized analysis needs
• Component weights are included for weighted-average calculations
• Each catalog includes metadata such as description, creation date, and update frequency