Curve room
The quiet ride has a cost.
BasketBenchmark
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Screened basketBenchmark
Defensive quality-screen strategy
Workspace-scoped research state and available fixture detail.
Research depth
Long-Term Growth Portfolio · frozen fixture
Evidence map/fixture 01 · complete
Research conclusion
Lower simulated drawdown, with an upside trade-off.
A rules-based basket of high-quality, low-volatility European names would have tracked close to the benchmark with meaningfully smaller drawdowns in simulated stress periods. This is a research finding on historical simulated data — not a prediction or recommendation.
Historical simulation fixtureJan 2016 – Dec 2025 (simulated)
3/5
fresh inputs
Drawdown edge
12.8pt
vs benchmark
Volatility
11.3%
annualised
Evidence
5 inputs
traceable fixture
Evidence map
Know what kind of truth you are holding.
Evidence3 evidence
- 01Across the simulated 10-year window, the screened basket showed a lower maximum drawdown than the benchmark in 8 of 10 calendar years.
- 02Quality factor exposure (return-on-capital) was persistent quarter-over-quarter in the demo fundamentals set.
- 03Realised volatility of the basket was consistently below the benchmark in the demo dataset.
Inference2 inference
- 01The defensiveness likely comes from balance-sheet quality rather than sector tilt alone.
- 02Behaviour in a sharp rate shock is uncertain — the demo window contains only one mild rate-shock analogue.
Assumptions4 assumptions
- 01Rebalanced quarterly with no intra-quarter trading.
- 02Transaction cost of 8 bps and slippage of 5 bps per trade.
- 03Dividends reinvested; no taxes modelled.
- 04Equal-weighted 12-name basket, capped at 1 name per 2% of capital.
Unknowns3 unknowns
- 01No live liquidity or borrow-cost data included.
- 02Survivorship in the demo universe is not fully controlled.
- 03Regime coverage is limited — no severe credit-crisis analogue in the window.
Source rail
Five inputs. One aging edge.
- Demo fundamentals dataset — European large-caps2026-08-14FreshFixture record · no external URLHigh reliabilityVerified data
- Simulated pricing feed (10y daily)2026-08-14FreshFixture record · no external URLHigh reliabilityVerified data
- Benchmark construction note (demo)2026-07-30RecentFixture record · no external URLMedium reliabilityVerified data
- Factor definitions memo (internal demo)2026-06-11AgingFixture record · no external URLMedium reliabilityAssumption
- Rate-regime classification (AI-derived)2026-08-15FreshFixture record · no external URLLow reliabilityAI inference
Kill criteria
What would invalidate this?
- Maximum drawdown advantage disappears once realistic borrow costs are added.
- Quality factor exposure proves unstable out-of-sample.
- A severe credit event reverses the low-volatility relationship (not covered in demo window).
Show the tested hypothesis
Hypothesis: Screening for high return-on-capital, low debt, and low price volatility produces a defensive basket with a shallower maximum drawdown than a broad market benchmark, at the cost of some upside.