Current-composition maximum-drawdown model
Author: Arhan Canli
Affiliation: Canli Capital / AlphaC Algorithms
Version: 1.0, 2026
Capital boundary: research simulation over a paper-trading specification
Abstract
This study estimates the two-year maximum-drawdown distribution of the current ALPHAC
composition: four constituent sleeves at equal-quarter weights plus a separately disclosed 10%
50/50 BTC/SPY strategic overlay. It corrects a category error in the earlier frontier study. The
15% volatility target belongs to constituent BlendStrategy instances; the ALPHAC composite
applies no second book-level volatility target or drawdown ladder.
Two zero-drift models were frozen before execution. A 10,000-path circular moving-block bootstrap uses a 63-calendar-day primary block, with 21- and 126-day sensitivity arms. A separate 10,000-path regime model preserves observed component volatility and calm dependence while moving all five weighted contributions to 0.50 stress correlation for a predeclared 12% stress share and 40-day mean stress run.
The conservative expected maximum drawdown is 9.32%, inside the governing 11% design objective. The conservative p95 maximum drawdown is 16.45%, outside 11%. The expected result is therefore encouraging; the tail result is not. Neither establishes live expected drawdown.
1. Exact specification mapped
The source builder reconstructs the same research book used by the public state:
- AlphaMax, AlphaForge, AlphaTrend and AlphaVintage at 25% each;
- fixed-weight aggregation;
- no ALPHAC-level volatility target;
- no ALPHAC-level drawdown ladder;
- missing daily constituent marks contribute zero; and
- a fixed +10% strategic overlay, 50% BTC and 50% SPY, outside constituent sizing.
The component contributions reconstruct the daily book return with zero numerical residual. The study binds the live fingerprint, contracts, protocol, book implementation, market-factor implementation, four sleeve-equity inputs and the market-factor source corpus by SHA-256.
2. Calibration boundary
The exact common window contains 1,061 calendar days from 2023-07-07 through 2026-06-01. In that window the research book has 5.21% annualized volatility and a 4.51% realized maximum drawdown. Its 1.78 Sharpe is labelled simulation, not forward evidence, and is not used as model drift: every arm removes the sample mean before estimating drawdown.
This window begins after both COVID and 2022. That is a binding limitation. A block bootstrap cannot generate a crisis absent from its source window.
3. Frozen models
3.1 Circular moving-block bootstrap
The primary 63-day arm produces:
| statistic | maximum drawdown |
|---|---|
| expected | 7.83% |
| median | 7.35% |
| p95 | 13.35% |
| Monte Carlo standard error of expected | 0.029 percentage points |
The 21-day sensitivity arm gives 7.96% expected / 14.11% p95. The 126-day arm gives 7.41% expected / 12.15% p95. All three expected values are inside 11%; all three tails exceed it.
3.2 Correlation-regime model
The regime arm produces:
| statistic | maximum drawdown |
|---|---|
| expected | 9.32% |
| median | 8.59% |
| p95 | 16.45% |
| Monte Carlo standard error of expected | 0.038 percentage points |
The model's simulated stress-day share is published in the machine artifact. It changes dependence but deliberately does not invent a stress-volatility multiplier.
4. Decision
The protocol defines the conservative expected value as the larger of the primary bootstrap and regime expectations. That value is 9.32%, so the current-composition modeled expectation is within the 11% design objective. The mandatory p95 is 16.45% and is not within 11%.
Status:
CURRENT_COMPOSITION_EXPECTED_WITHIN_OBJECTIVE_HISTORICAL_TAIL_COVERAGE_INCOMPLETE.
This is not statistical establishment. The live record is still short, the common calibration window omits major crises, the regime arm has no stress-volatility multiplier, and neither model replays constituent instruments, execution gaps, liquidity feedback or dynamic ladder state. Those limitations are machine-readable failed establishment dimensions, not prose footnotes.
5. Reproduction
uv run python scripts/analyze_current_book_drawdown.py
uv run python scripts/seal_forward_drawdown_evidence.py
uv run pytest -q tests/unit/test_current_book_drawdown.py tests/unit/test_forward_drawdown_evidence.py
Canonical machine result: /glassbox/current_book_drawdown.json
Sealed claim boundary: /glassbox/forward_drawdown_evidence.json