Alpha Report
S&P 500 | July 2026

Market SectorEquity IndexModelPythia-v0.4.4
Date FromJul 01 2026Date ToJul 31 2026
Published Aug 4, 2026

1. Executive Summary

ES Macro Review for July 2026

U.S. equity markets edged lower in July 2026, with the S&P 500 benchmark (rebased series) declining approximately 0.28% over the month, as investors navigated a Federal Reserve that remained firmly on hold amid still-sticky services inflation, tempering expectations for any near-term easing pivot. Geopolitical tensions, including renewed uncertainty in the Middle East and continued friction around Taiwan Strait trade routes, periodically weighed on risk sentiment, contributing to a choppy, range-bound tape through much of the month before a modest late-month sell-off pressured equities into the final sessions of July. Against this backdrop, the strategy outperformed, returning +0.18% over the same window, preserving capital during the month's softer close.

Signal Performance Overview for July 2026

Trailing 12-month Sharpe 0.397 and return 1.642% (through the period in Table 3 below). During the report month, the S&P 500 benchmark (rebased series, see Figure 1) declined approximately 0.28%; the strategy returned +0.18% over the same window. Risk Posture: The strategy held its drawdown profile nearly flat, with max drawdown edging marginally deeper to -7.15% from -7.11%, suggesting contained tail risk despite any shift in market conditions. Win rate slipped modestly to 52.57% from 52.99%, a negligible deterioration that keeps the edge intact and signals the current window is broadly consistent with, though fractionally softer than, the prior period.

Signal Coverage — S&P 500

Asset ClassTrading SymbolName
FuturesESE-mini S&P 500
FuturesMESMicro E-mini S&P 500
ETFSPYSPDR S&P 500 ETF

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 15:30 ET) we decide to take a long, short or no position using 1/69 of our starting portfolio for the day (there are 69 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: 1 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
Versionv0.4.4
ExchangeCME Globex
DataLevel II Limit Order Book (10 levels)
Retrained Time Period21Q1 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 YTD-2.67150.182
2026 Jul-0.04151.475
2026 Jun-3.28541.333
2026 May0.15448.416
2026 Apr-1.00240.946
2026 Mar-0.37950.875
2026 Feb-0.54847.124
2026 Jan2.51370.539
2025 Dec0.58056.876
2025 Nov0.26147.283
2025 Oct0.70252.089
2025 Sep1.52762.937
2025 Aug1.29860.865

Table 2: Year over Year Performance Comparison

MonthReturn (%)Win Rate (%)
Jul 2026-0.04151.475
Jul 20250.89455.729
Jul 20241.69254.840

Table 3: 12-Months Ending Performance

Metric12 months ending Jul 202612 months ending Jun 2026Change
Sharpe0.3970.610-0.213
Ann Return (%)1.6422.586-0.945
Win Rate (%)52.56952.986-0.417
Max DD (%)-7.153-7.114-0.039
Volatility4.0804.113-0.033
Calmar0.2270.353-0.126

Figure 1: Cumulative equity curve showing the trading strategy net long/short performance compared with the ES price (100 = July 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