Alpha Report
Nasdaq-100 | July 2026

Market SectorEquity IndexModelPythia-v0.5.1
Date FromJul 01 2026Date ToJul 31 2026
Published Aug 4, 2026

1. Executive Summary

NQ Macro Review for July 2026

The Nasdaq-100 benchmark declined approximately 5.57% in July 2026, as risk assets came under broad pressure from a combination of renewed geopolitical tensions and a Federal Reserve that signaled it was in no hurry to ease, effectively keeping policy on hold and pushing back market expectations for near-term rate cuts. Sentiment deteriorated further into month-end, with a late-July sell-off amplifying losses as investors reduced exposure ahead of key earnings releases and reassessed stretched valuations in mega-cap technology names. Against this backdrop, the strategy navigated the drawdown with considerably more resilience, returning -0.96% over the same period, outperforming the benchmark by approximately 461 basis points.

Signal Performance Overview for July 2026

Trailing 12-month Sharpe 0.538 and return 2.672% (through the period in Table 3 below). During the report month, the Nasdaq-100 benchmark (rebased series, see Figure 1) declined approximately 5.57%; the strategy returned -0.96% over the same window. Risk Posture & Period Comparison: The current window shows a modest deterioration in drawdown depth (−6.95% vs. −6.43%) alongside a slight softening in win rate (53.47% vs. 53.88%), suggesting marginally less favorable conditions for capital preservation than the prior period. Both metrics remain within a disciplined range, indicating the strategy has absorbed increased volatility without meaningful structural breakdown.

Signal Coverage — Nasdaq-100

Asset ClassTrading SymbolName
FuturesNQNasdaq 100 E-mini
FuturesMNQMicro E-mini Nasdaq 100
ETFQQQInvesco QQQ Trust

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
Versionv0.5.1
ExchangeCME Globex
DataLevel II Limit Order Book (10 levels)
Retrained Time Period21Q1 to 25Q2
Final Validation Period25Q2 to 26Q2

4. Performance Metrics

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

MonthReturn (%)Win Rate (%)
2026 YTD-2.93651.090
2026 Jul-0.84949.949
2026 Jun-3.36149.556
2026 May-0.00750.706
2026 Apr0.00246.921
2026 Mar0.45850.401
2026 Feb-0.72549.038
2026 Jan1.60059.569
2025 Dec0.44456.146
2025 Nov1.04048.970
2025 Oct0.69549.452
2025 Sep2.69872.733
2025 Aug0.78956.575

Table 2: Year over Year Performance Comparison

MonthReturn (%)Win Rate (%)
Jul 2026-0.84949.949
Jul 20250.77053.983
Jul 20242.51559.513

Table 3: 12-Months Ending Performance

Metric12 months ending Jul 202612 months ending Jun 2026Change
Sharpe0.5380.876-0.338
Ann Return (%)2.6724.339-1.667
Win Rate (%)53.47153.875-0.404
Max DD (%)-6.951-6.428-0.523
Volatility4.9954.914+0.081
Calmar0.3870.670-0.283

Figure 1: Cumulative equity curve showing the trading strategy net long/short performance compared with the NQ 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