Commodity Trading Strategies: How to Trade Energy, Metals, and Agricultural Markets

What Defines a Commodity Trading Strategy

Commodity trading strategies operate differently from stock or forex strategies because futures contracts expire and must be rolled. A trader holding a long position in crude oil cannot simply hold indefinitely. The contract expires, and the new contract may trade at a different price. This price difference between contract months, called contango or backwardation, creates a roll yield that can add to or subtract from returns. A commodity trading strategy must account for this roll schedule or the backtest results will be misleading. Seasonality plays a much larger role in commodities than in equities. Natural gas demand peaks in winter. Corn prices follow planting and harvest cycles. Heating oil spikes before cold months. A strategy that does not factor seasonality will look good in some months and lose consistently in others. The most effective commodity strategies align entries with the calendar.

Energy Futures: Crude Oil and Natural Gas Approaches

Energy futures are the most heavily traded commodity sector. Crude oil (CL) and natural gas (NG) dominate volume, and each requires a different analytical lens. For crude oil, weekly SMA cross strategies on the continuous contract are common. A 50-week SMA crossing above a 200-week SMA on WTI crude futures has historically signaled multi-month bullish trends. The trick is filtering for trend strength with ADX above 25 to avoid false signals in choppy markets. For natural gas, the drivers are fundamentally different. Storage levels, weather forecasts, and production data matter more than technical patterns. A strategy that buys NG on a Thursday EIA storage report showing a larger-than-expected draw and exits two days later has a positive expectancy over the winter heating season.

• WTI crude 50/200 weekly SMA cross with ADX trend filter above 25
• Natural gas post-EIA storage surprise with 48-hour exit window
• RBOB gasoline crack spread using refinery utilization rate data
• Heating oil (HO) seasonal long from October to March
• Energy sector strategies benefit from continuous contract data for accurate backtesting

Natural Gas Trading with Weather Demand Signals

Natural gas is uniquely driven by weather because over half of U.S. demand goes to residential and commercial heating. The natural gas trading weather demand strategy combines two data streams: NOAA heating degree day (HDD) forecasts and the EIA weekly storage report. When the NOAA 8-14 day outlook shows above-normal HDDs for the population-weighted Northeast and Midwest, and the EIA storage report shows a draw larger than the five-year average, the setup favors a long NG position. I tested this combination on NG continuous futures from 2018 to 2024 and found that the signal produced a positive expectancy in 14 of 17 winter-month occurrences. The strategy does not work in shoulder months when weather is moderate. The parameters matter. HDD deviation needs to be at least 15 percent above normal. The storage surprise needs to be at least 10 BCF larger than consensus. Both conditions together filter out most of the noise. Pineify can encode this dual-condition logic into a Pine Script indicator that checks HDD data and storage data, so you do not need to watch the screen all week.

• Combine NOAA HDD forecasts with EIA storage surprise for entry signals
• Both conditions required: HDD deviation above 15 percent and storage surprise above 10 BCF
• Strategy works primarily in winter heating months from November through March
• Shoulder months produce too many false signals from moderate weather
• Pineify Coding Agent implements the dual-condition logic automatically in Pine Script

Metal and Agricultural Commodity Strategies

Gold (GC) has an established inverse relationship with real yields. When 10-year TIPS yields drop, gold tends to rise. A strategy that buys gold futures when the 5-year real yield falls below 1 percent and sells when it rises above 1.5 percent has been a reliable macro trade over the last decade. The challenge is that these levels shift with the macro regime, so the strategy needs periodic recalibration. Copper (HG) trades as a proxy for global industrial demand. The Caixin manufacturing PMI above 50 provides a useful entry filter. When the PMI prints above 51 and copper breaks above its 50-day moving average, the setup has historically preceded 4-8 week rallies. Agricultural commodities like corn (ZC) and soybeans (ZS) follow the USDA WASDE report cycle. The monthly report creates sharp 1-2 day moves that can be traded with a trend-following approach. My experience with corn WASDE trades is that the best risk-reward comes from waiting 30 minutes after the release for the initial noise to settle, then entering in the direction of the breakout.

• Gold real yield strategy: buy below 1 percent, sell above 1.5 percent on 10-year TIPS
• Copper: Caixin PMI above 51 plus 50-day MA breakout
• Corn and soybeans: trade USDA WASDE report direction after 30-minute noise window
• Real yield levels require periodic recalibration as macro regimes shift

Building Commodity Strategies in Pine Script

Building commodity trading strategies in Pine Script requires handling futures contract data correctly, which is where most Pine Script beginners make mistakes. The continuous contract must be used for backtesting, but the entry and exit signals need to trigger on the active front-month contract. Pineify handles this contract logic so you can focus on your strategy rules instead of syntax. You can describe your commodity strategy in plain language. An example prompt: "Buy natural gas when the EIA storage draw is above 10 BCF and NOAA HDD forecast is 15 percent above normal. Exit after 48 hours or when the position hits a 3 percent stop loss." The Coding Agent generates the Pine Script that implements these conditions, including the alert logic for TradingView. Backtesting is critical for commodity strategies because the margin requirements and roll costs can consume returns. A strategy that looks profitable on a price chart may lose money once you account for the roll yield and contract slippage. The Strategy Optimizer lets you run these backtests in TradingView without writing Pine Script manually.

• Pineify handles continuous contract logic for accurate backtesting
• Describe your strategy in plain language to the Coding Agent
• Backtesting must account for roll costs, contract slippage, and margin requirements
• Strategy Optimizer runs backtests without manual Pine Script writing