Alpha Report
Dow Jones
Composite Signal
September 2026

Market SectorEquity IndexModelPythia-v0.12.0SignalComposite
Date FromSep 01 2026Date ToSep 30 2026
Published Oct 15, 2026

1. Executive Summary

YM Macro Review for September 2026

September's rate shock weighed on the value-heavy Dow: the Federal Reserve raised rates to 3.75–4.00% on 16 September, its first hike since 2023, and the 10-year Treasury yield rose from about 4.75% to 5.29%, with Financials among the weakest sectors. Market gains were concentrated in a handful of technology mega-caps, leaving the broader and more traditional parts of the market lower for the month.

Signal Performance Overview for September 2026

Trailing 12-month Sharpe 1.706 and return 5.467% (Table 3), up from Sharpe 1.482 and return 4.611% for the 12 months ending August.

During the report month the rebased Dow futures series in Figure 1 fell about 2.8%; the strategy returned +0.67% with a Sharpe of 2.43 and a win rate of 51.45%, and a maximum intra-month drawdown of −0.53%. Short positions contributed most (+0.47 points) and longs added +0.19 points, so the strategy profited despite the index's decline.

Risk Posture: The trailing 12-month maximum drawdown was unchanged at −1.79%, and the win rate improved by about 0.8 percentage points to 55.04%, strengthening an already low-drawdown profile.

Signal Coverage: Dow Jones Industrial Average

Asset ClassTrading SymbolName
FuturesYME-mini Dow
FuturesMYMMicro E-mini Dow
ETFDIASPDR Dow Jones Industrial Average ETF

2. Trading Strategy

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

  • Entry positions: every 5 minutes between 09:45 and 15:25 ET (69 possible openings per day) we take a long, short or no position. Each position is split into 5 parts, executed on each minute of the 5 minutes after the decision. No sizing adjustment.
  • Exit positions: each decision's position is closed between 15:55 and 16:00 ET, its five parts over the five minutes.
  • Costs: 0.75 bp per side, 1.5 bp round trip (YM). Extra exchange/clearing fees not included.
  • Contract series & roll: Front month quarterly contract (Mar, Jun, Sep, Dec). Switch at the open 5 trading days before expiration (the third Friday of the contract month): 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-v0.12.0: committee of models voting per decision
VersionDOW30_DTC v16
ExchangeCME Globex
DataLevel II Limit Order Book (10 levels)
Trained Time PeriodQ1 2020 to Q4 2025
Final Validation PeriodJan 2026 to Aug 2026

4. Performance Metrics

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

MonthReturn (%)Win Rate (%)
2026 YTD5.52255.196
2026 Sep0.66551.452
2026 Aug0.61581.337
2026 Jul0.57854.477
2026 Jun2.49468.256
2026 May-1.29126.291
2026 Apr0.59747.661
2026 Mar1.04962.384
2026 Feb0.10854.330
2026 Jan0.70755.930
2025 Dec0.33856.825
2025 Nov0.11852.349
2025 Oct-0.51153.524

Table 2: Year over Year Performance Comparison

MonthReturn (%)Win Rate (%)
Sep 20260.66551.452
Sep 2025-0.19140.377
Sep 20240.16357.830

Table 3: 12-Months Ending Performance

Metric12 months ending Sep 202612 months ending Aug 2026Change
Sharpe1.7061.4820.224
Return (%)5.4674.6110.857
Win Rate (%)55.03654.2430.793
Max DD (%)-1.790-1.7930.003
Volatility3.2263.1220.104
Calmar2.9702.5000.470

Table 4: Quarterly Performance

QuarterSharpeReturn (%)Win Rate (%)Max DD (%)VolatilityCalmar
Q3 20263.0741.85860.074-0.7842.4609.289
Q2 20261.8161.80049.904-1.7114.1574.254
Q1 20262.0281.86457.573-1.4923.8585.056

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

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