Alpha Report
Natural Gas | June 2026

Market SectorEnergyModelPythia-v0.8.0
Date FromJun 01 2026Date ToJun 30 2026
Published Jul 28, 2026

1. Executive Summary

NG Macro Review for June 2026

Natural Gas futures edged higher over June 2026, with the benchmark (rebased series) advancing approximately 2.35% on the month, supported by firmer summer cooling demand expectations and lingering supply-side tightness across key LNG export corridors. The Federal Reserve held rates steady during the month but signaled a cautious easing bias heading into H2 2026, providing a modestly constructive macro backdrop for energy commodities, though geopolitical tensions in the Middle East periodically injected volatility and capped more decisive upside moves. Against this backdrop, the strategy returned +0.04% over the same window, meaningfully lagging the benchmark as positioning did not fully capture the directional move, with late-month price strength into the June close contributing to the bulk of the benchmark's gains at a point where the strategy carried limited net exposure.

Signal Performance Overview for June 2026

Trailing 12-month Sharpe 0.513 and return 9.826% (through the period in Table 3 below). During the report month, the Natural Gas benchmark (rebased series, see Figure 1) rose approximately 2.35%; the strategy returned +0.04% over the same window.

Signal Coverage — Natural Gas

Asset ClassTrading SymbolName
FuturesNGNatural Gas Futures
FuturesQGE-mini Natural Gas Futures
ETFUNGUnited States Natural Gas Fund

2. Trading Strategy

In order to produce the metrics below we use the signal in combination with the trading strategy below:

  • Leverage: No leverage is applied for this strategy and metrics
  • Positions:
    • Entry positions: Every 5 minutes (between 09:45 and 14:00 ET) we decide to take a long, short or no position using 1/51 of our starting portfolio for the day (there are 51 possible openings per day). Each long/short position is then split into 5 parts and executed on each minute for the next 5 minutes following the decision. There is no sizing adjustment.
    • Exit positions: We exit all positions at the end of the day. The exits are split over five minutes (15:55–16:00 ET).
  • Costs: 2.5 bp round-turn assumption. Extra exchange/clearing fees not included.
  • Contract series & roll: Front-month continuous. Switch at the open T–5 trading days before expiration; stop trading the expiring contract and start trading the next.

For detailed examples, flowcharts, and a full walkthrough of the trading strategy, see Benchmark Trading Strategy.

3. Model Training Data and Timeframe

CategoryValue
Model FamilyPythia
Versionv0.8.0
ExchangeCME Globex
DataLevel II Limit Order Book (10 levels)
Retrained Time Period20Q1 to 24Q4
Final Validation Period25Q1 to 26Q2

4. Performance Metrics

Table 1: Monthly Return and Win Rate Metrics (Last 12 Months)

MonthReturn (%)Win Rate (%)
2026 YTD2.80250.792
2026 Jun0.14051.512
2026 May-3.51048.598
2026 Apr-1.68147.472
2026 Mar-1.36247.629
2026 Feb5.29951.224
2026 Jan5.51658.419
2025 Dec-1.89344.074
2025 Nov4.11457.260
2025 Oct0.51346.569
2025 Sep2.03553.987
2025 Aug5.11764.698
2025 Jul-2.96941.354

Table 2: Year over Year Performance Comparison

MonthReturn (%)Win Rate (%)
June 20260.14051.512
June 20250.21948.663
June 2024-4.36744.677

Table 3: 12-Months Ending Performance

Metric12 months ending June 202612 months ending May 2026Change
Sharpe0.5130.512+0.002
Ann Return (%)9.8269.881-0.055
Win Rate (%)51.08550.907+0.178
Max DD (%)-12.128-11.238-0.890
Volatility18.54118.604-0.063
Calmar0.7840.847-0.062

Table 4: Quarterly Performance

QuarterSharpeReturn (%)Win Rate (%)Max DD (%)VolatilityCalmar
Q2 2026-2.415-4.97649.243-7.3437.748-2.548
Q1 20261.2008.22052.455-6.57731.9425.828

Figure 1: Cumulative equity curve showing the trading strategy net long/short performance compared with the NG price (100 = June 01, 2026)

5. Next Steps

Download historical predictions for this month using the Client API and confirm performance in your own test harness.

6. Contact

Please reach out with any questions or comments at: info[at]quantumsignals.ai