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Public demo mode: research software only, no financial advice, no live order execution, no live trading. Data is either real market data or explicitly labeled fallback/demo data.
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breakout · SPY

Quality Momentum Breakout

Identifies symbols near recent highs where volatility compression and healthy participation create a higher-quality breakout setup.

real dataadjusted pricesYahoo Finance chart API·Real daily OHLCV data loaded and adjusted for corporate actions·updated Jul 11, 2026, 9:12 AM
Selection-bias notice. Headline metrics default to CAT — the symbol where this rule scored highest across the 28-name watchlist. That is a deliberate showcase pick, not a survivorship-bias-free result, so the default numbers are optimistic by construction. Switch symbols below to see how the same rule behaves elsewhere.Currently viewing SPY (rank 8 of 28).
Methodology / Assumptions
  • Signals are produced from completed daily bars; entries fill at the next open with modeled costs.
  • Headline view defaults to the strongest symbol for this strategy, and the selection-bias notice documents that assumption.
  • No intraday fills, live order execution, shorts, options, or margin are modeled.
  • AI memo prose is generated from the deterministic backtest payload or a template fallback; metrics are engine-derived.

Quality Momentum Breakout

breakout thesis: treat SPY as research evidence only when factor evidence, trend structure, and risk-adjusted backtest behavior align. The current model reads the setup as medium-confidence research evidence, not a live trading instruction.

Model Reasoning Summary

The ranking model weighs annualized return, Sharpe, drawdown containment, trade sample size, data quality, and cost-aware execution. This strategy is strongest when its signal frequency is sufficient and drawdown remains inside the radar threshold.

54
medium confidence

Deterministic template memo. Set DEEPSEEK_API_KEY to enable LLM-written narrative.

+0.8%
+0.3%
+100.5%
Excess
-99.7%
-1.9%
0.18
71.4%
Trades
7
Profit factor
1.41
Avg holding
40d

Benchmark and excess are measured against a passive hold of SPY over the same window. A long-only, risk-managed rule that trades infrequently is expected to trail a strong benchmark tape — the goal here is risk-adjusted behavior (Sharpe, drawdown), not beating the index.

Deterministic synthesis from the backtest, stress diagnostics, and live regime.

Needs one more validation

Promising but not yet clear of the gates; run one more research test before observation.

Base score53/100
Stress-adjusted53/100
Regime fit77/100
Confidence49/100

Behavioral tilt from the strategy rules and realized statistics.

Momentum
high
Trend
high
Low volatility
moderate
Mean reversion
low

Last ~63 sessions · strategy return split into market vs selection.

Strategy
+0.6%
Benchmark
+19.0%
Market component
+19.0%
Selection / timing
-18.4%
Regime sensitivity
Relatively regime-stable — less dispersion across conditions.
low
Catalyst sensitivity
Moderately catalyst-sensitive
54/100
Downside-risk priority
Contained
5/100
Benchmark behavior
Symmetric participation
0.07↑ / 0.09↓
Current risk
Watch
Model freshness
Fresh
as of 2026-07-10
Data quality
Adjusted real data95/100

Suggested next research test. Extend the backtest window or universe to grow the trade sample before any observation admission.

Equity curve
StrategyBenchmark
Loading chart
Ends below benchmark
Latest signal
OBSERVE · 2026-07-10

near 60d high + volatility contraction + healthy volume breakout; observed after completed bar

AI Research Memo

Quality Momentum Breakout on SPY produced a adjusted real-data backtest annualized return of +0.3%, Sharpe 0.18, and max drawdown -1.9%.

The strategy currently behaves more like an observation rule with limited return elasticity, useful as a pre-radar baseline.

Risk-adjusted return is weak

Keep it on the radar and expand the evidence set across more symbols and market regimes.

Watch under a risk-on tape

Suitability for paper observation during selloff conditions: suitable.

Watch
Base score
53
Composite radar score
Stress-adjusted score
53
Penalizes drawdown / downside vol, rewards resilience
Risk flags
1
1 stop-loss exit on record
Drawdown sensitivity5/100
Volatility sensitivity0/100
Drawdown-focused views
Max drawdown
-1.9%
Current drawdown
-0.4%
Downside volatility
2.9%
Worst 5-day
-1.2%
Benchmark-rel. DD
-53.0%
Recent vs benchmark
-4.2%
Days underwater
26d
Stop-loss triggers
1

Stress status tightens automatically when the broad regime is risk-off. Drawdown metrics are deterministic from the backtest equity curve; historical backtests do not represent future returns. Research only — not investment advice.

Drawdown
Trough -1.9%
Loading chart
Real market data or explicit fallback labelpassed
At least 5 completed tradespassed
Sharpe > 1watch
Max drawdown better than -25%passed
No same-bar fills: signals execute at next openpassed
Costs included: slippage and fees are modeledpassed
Walk-Forward Evaluation
robust

Calendar split at 2025-08-15 (70% in-sample). Backtest is unchanged — the engine simply re-derives metrics for each window from the same equity curve. Numbers are not refit; this is an honesty check.

In-sample
528 bars
2023-07-112025-08-15
Annualized
+0.3%
vs benchmark
-58.2%
Sharpe
0.20
Max drawdown
-1.9%
Trades
4
Win rate
75.0%
Out-of-sample
226 bars
2025-08-152026-07-10
Annualized
+0.3%
vs benchmark
-26.0%
Sharpe
0.15
Max drawdown
-1.0%
Trades
3
Win rate
66.7%
Degradation (OOS minus In-sample)
Sharpe Δ
-0.05
Annualized Δ
++0.0%
Drawdown Δ
++0.9%
Win-rate Δ
-8.3%
Factor Attribution (OLS)

Strategy daily return regressed on [Market, Momentum, Low-vol]. Alpha is what's left after these known factors are accounted for — the part the simple factors cannot explain.

Annualized alpha
-1.2%
t = -1.46 (not significant)
Market
t-significant
β = 0.06
t = 12.61
SPY daily return (or QQQ fallback).
Momentum
t-significant
β = 0.03
t = 8.64
Top-50% minus bottom-50% of 60-day momentum within the watchlist.
Low-vol
t-significant
β = -0.01
t = -2.58
Bottom-50% minus top-50% of 60-day realized volatility.
0.366
Residual vol (ann.)
1.3%
Observations
691
Sample
2023-10-06 → 2026-07-10

A high R² with small alpha means the factors explain most of the return — be skeptical of “edge”. Significant alpha (|t| ≥ 2) with low R² is more interesting evidence that something beyond Market/Momentum/Low-vol is driving the strategy.

AI Research Memo: Market Selloff Review

Deterministic memo
Market context

Constructive tape: 21/28 names hold their 200-day trend with contained volatility (30% annualized). Risk signals are quiet, but drawdown discipline still applies. Composite stress score is 7/100 (risk-on). Breadth is broad and momentum is leading; short-horizon volatility is running 6% above its 60-day baseline. Conditions support continuation research, but keep stops and position sizing documented in case the regime turns.

Factor behavior

Breadth is broad (21/28 above SMA200), momentum is leading at 2.7% avg 20-day, and volatility is elevated (30% annualized). Factor signals are not flashing broad stress, but drawdown discipline still governs observation admission.

Strategy risk

3 of 5 screened strategies read as resilient and 0 as under stress. Strategies with positive historical returns but high downside sensitivity should be moved from "candidate" to "watch" until volatility normalizes.

Radar impact

Stress-adjusted scoring repriced 0 of 5 strategies versus their base score, penalizing high drawdown and downside volatility while rewarding benchmark-relative resilience and smoother equity. 2 strategies still clear the radar-candidate gate.

Paper observation notes

1 simulated observation remain live. Observation continues under stress so the desk can study how admitted rules behave through the drawdown — no orders are routed.

Suggested next experiments
  • Re-run the radar shortlist with the stress-adjusted score as the primary sort key and compare observation admissions.
  • Measure each candidate's worst 5-day return and benchmark-relative drawdown against the current regime.
  • Stress-test stop placement against overnight gaps rather than intraday fills.
  • Track whether breadth broadens or volatility keeps expanding before changing candidate priorities.

Generated from deterministic engine metrics (regime, breadth, volatility, drawdown, radar scoring). No order instructions. Historical backtests do not represent future returns. Research only — not investment advice.

Rule Logic
  • Generate signals only from completed daily bars.
  • Fill entries at the next bar open with modeled slippage and fees.
  • Exit via stop loss, trailing stop, holding-period expiry, or the strategy's predefined exit rule.
Risk Flags
  • Risk-adjusted return is weak
Suggested Next Experiments
  • Expand the universe beyond the current sector-diversified watchlist and rerun the same rule set.
  • Test a tighter slippage and fee sensitivity range to understand implementation drag.
  • Compare 20%, 10%, and volatility-scaled position sizing across the same signals.
Backtest assumptions
Execution
next open
Position size
+20.0%
Slippage
5 bps
Fee/trade
$1

Entry signals are generated from completed bars and filled at the next bar open. Stop and trailing-stop exits are evaluated on marked daily closes.

Trades
EntryExitHoldReturnP/LFeesReason
2024-06-062024-08-1245d+0.1%$13$2holding period
2024-09-272024-12-0245d+5.0%$992$2holding period
2025-02-202025-03-1012d-8.4%-$1,674$2stop loss
2025-06-042025-08-0845d+6.4%$1,246$2holding period
2025-09-232025-11-2545d+0.2%$35$2holding period
2025-12-242026-03-0345d-2.0%-$393$2holding period
2026-05-012026-07-0845d+3.2%$620$2holding period