Stress test
The verified track record answers what did happen. This page answers what would happen: a behavioral policy derived from this trader's chain, played day-by-day against market regimes they haven't traded through. One deterministic path per regime, with no Monte Carlo, no distribution, and no fan chart. A single causal story you can audit.
Edge degrades in regimes the strategy didn't train on, slippage widens with vol, and the policy sits out under drawdown. These are the standard failures of real trading reflected back at simulation speed. Behavioral simulation, not investment advice.
Regime
Compare all regimes →Calendar-year 1987 with Black Monday (Oct 19) anchored at day 198. The single -20.4% gap is the stress; the rest of the year is ordinary. Tests whether a strategy survives a single tail event.
Custom regime
Define your own scenario.
Set an annualized drift and volatility, a horizon, and any single-day shocks. The same behavioral policy is replayed against the path you describe, built on the fly, never stored.
Policy under 1987 Black Monday
252 trading days · starting equity $100,000 · cached
Simulated policy
Trader's actual record
Hover for day-by-day detail
Policy return
+8.85%
Actual return
+22.94%
Max drawdown
3.8%
Days in drawdown
122
Recovery
Never
Sit-out days
0
Entries
70
Exits
70
What happened
Composed deterministically from the policy decisions. The same input always yields the same paragraph, with no LLM, cached forever.
Run against the 1987 Black Monday (tail-event regime over 252 trading days). The behavior policy derived from this trader's chain produced a +8.9% total return with a 3.8% peak drawdown; the policy never returned to its prior peak in this window. The policy entered 70 times, exited 70 times, and sat out 0 days under drawdown / vol thresholds. Policy thresholds: 1.4% profit target, -1.1% stop loss, 28% of equity per position, active on ~95% of trading days. This is a single deterministic path — no Monte Carlo aggregation. It shows what the policy would do in this specific scenario, not a distribution. It is not investment advice.
Key decisions
- Day 2Hit stop loss (-1.3% over last 10 days, vol-adjusted threshold -1.1%).
- Day 8Equity trough: $99,195.
- Day 73Realized 10-day vol jumped from 0.75% to 1.22%.
- Day 173Equity peak: $110,710.
- Day 197Oct 16: Friday wobble before the gap
- Day 198Oct 19: BLACK MONDAY (-20.4%)
Adversarial resilience
How much of the edge survives a competitor who knows the playbook and fades the policy's fills, hardest on forced stop exits. A resilience disclosure, not a verdict on the trader.
33/100
edge retained under attack
Baseline return
+8.85%
Under attack
+2.91%
Edge taxed away
5.9%
Fills faded
140 · 48 stops
Against a competitor who knows this playbook, the strategy retains 33% of its edge in the 1987 Black Monday regime: a +8.9% return becomes +2.9% once the adversary withdraws liquidity on its 140 fills, 48 of them forced stop exits. Higher resilience means the edge depends less on cheap, unopposed execution. This is a resilience disclosure, not a verdict on the trader — a deterministic execution-cost stress, not a prediction. Not investment advice.
Your mirrored account
What this regime would have done to your allocation if you had mirrored Volterra Capital (Demo). Pick an amount; the dollar figures scale, the percentage path doesn't.
Allocation
$50,000
Ending (before fee)
$54,425
+$4,425 · +8.85%
Performance fee
−$1,071
24.2% of profit
Net to you (after fee)
$53,354
+$3,354 · +6.71%
Max drawdown
$2,086
3.8% from peak
Lowest balance
$49,598
trough of the path
Your dollars on the same simulated 1987 Black Monday path, a linear scaling of the policy curve, not a separate simulation. Mirroring is exactly proportional, so the percentage path is identical at every allocation; only the dollar figures change. After-fee figures apply this trader's 20% performance fee on a high-watermark basis (you never pay twice for the same gain). Display only; behavioral simulation, not investment advice.
Investor lens
The same result, read through four investor archetypes. Each weights drawdown, return, recovery, and survival differently. The spread itself is the signal. When the panel disagrees, your own tolerance is the tiebreaker.
Deterministic verdicts. Not allocation advice, just a disclosure of how different profiles would read these numbers.
All 4 archetypes read this trader favourably. The reasons differ — capital preservation, growth, risk-adjusted, and stress survival each see it positively from their own angle.
Preservation
The Capital Preserver
Drawdown weighs heaviest here: 3.8% peak drawdown, never recovered in the window. Upside of +8.9% total return doesn't offset the capital-at-risk reading.
Growth
The Growth Seeker
Total return of +8.9% drives the reading; the 3.8% drawdown is acceptable cost-of-capture. Note: the policy stayed engaged with 70 entries.
Risk-Parity
The Risk-Parity Allocator
On a risk-adjusted basis the return/drawdown ratio of +2.35 is the read. +8.9% return came at 3.8% peak DD; weight in proportion to that ratio.
Skeptic
The Regime Skeptic
Survivability is the question, not upside. The 3.8% max drawdown and the policy exited 70 times against 70 entries characterise how the policy responds when the regime turns.
Policy thresholds
The rules-of-thumb derived from this trader's chain. The simulator runs these decisions day-by-day.
Base notional
28%
of equity per position
Active days
95%
of trading days
Hold target
2.6d
median position
Profit target
+1.4%
exit on gain
Stop loss
-1.1%
exit on loss
Market beta
1.05
exposure to regime