Commodities API

Overview

The Commodities API provides access to real-time and historical pricing data for a wide range of commodity markets, including energy products, precious metals, agricultural goods, and industrial metals. This documentation outlines the available objects and functions to help you integrate commodity market data into your trading algorithms and analysis workflows.

Available Objects

Available Functions

Commodity Categories

The Commodities API supports various categories of tradable commodities:

1. Energy

   • Crude Oil (WTI, Brent)
   • Natural Gas
   • Heating Oil
   • Gasoline

2. Precious Metals

   • Gold
   • Silver
   • Platinum
   • Palladium

3. Industrial Metals

   • Copper
   • Aluminum
   • Zinc
   • Nickel

4. Agricultural

   • Corn
   • Wheat
   • Soybeans
   • Cotton
   • Coffee
   • Sugar

5. Livestock

   • Live Cattle
   • Feeder Cattle
   • Lean Hogs

Getting Started

To begin working with commodity data:

1. Import the GoldenGoose library
2. Use list() to discover available commodity symbols
3. Use get() to retrieve data for specific commodities
4. Access historical and real-time pricing through the returned ggCommodity object

Example

import goldengoose
 
# Get all available commodity symbols
available_commodities = goldengoose.commodities.list()
print(f"Available commodities: {len(available_commodities)}")
print(f"Examples: {', '.join(available_commodities[:5])}")
 
# Retrieve data for Gold
gold = goldengoose.commodities.get("GC")
 
# Get current epoch
current_epoch = goldengoose.get_current_epoch()
 
# Access the current price data
current_candle = gold[current_epoch]
current_price = current_candle.oneMinute.close
 
# Print basic information
print(f"Gold (GC)")
print(f"Current Price: ${current_price:.2f} per troy ounce")
print(f"Daily Volume: {gold.volume:,.0f} contracts")
 
# Calculate daily range
daily_high = current_candle.oneMinute.high
daily_low = current_candle.oneMinute.low
daily_range = daily_high - daily_low
daily_range_pct = (daily_range / daily_low) * 100
 
print(f"Today's Range: ${daily_low:.2f} - ${daily_high:.2f} (${daily_range:.2f}, {daily_range_pct:.2f}%)")
 
# Access 5-minute data
five_min_data = current_candle.fiveMinute
print(f"5-Minute OHLC: Open=${five_min_data.open:.2f}, High=${five_min_data.high:.2f}, Low=${five_min_data.low:.2f}, Close=${five_min_data.close:.2f}")

Use Cases

Portfolio Diversification

Incorporate commodities into investment portfolios to reduce correlation with equity markets.

Inflation Hedging

Monitor precious metals and other commodities that traditionally serve as inflation hedges.

Sector Analysis

Analyze relationships between commodity prices and related equity sectors (e.g., oil prices and energy stocks).

Seasonal Trading

Identify and exploit seasonal patterns in agricultural and energy commodities.

Supply Chain Risk Management

Monitor industrial metals and energy prices to assess supply chain cost impacts.

Notes

• Commodity data is provided in real-time with minimal latency
• Historical data is available for backtesting and analysis
• Data includes OHLC (Open, High, Low, Close) values and volume
• Prices are displayed in the commodity's standard trading unit (e.g., troy ounces for gold, barrels for oil)
• Contract specifications such as contract size and delivery months are available
• Commodities follow their respective exchange trading hours, which may differ from equity market hours
• All timestamps are in UTC format

For more detailed information on specific objects and functions, please refer to the dedicated documentation pages linked in the tables above.