Check for warehoused risk.
The first structural test. Step 2 deploys the Structural Integrity toolkit to answer the highest-priority question: is this system storing unrealized losses inside open positions right now?
- Why warehoused risk is the highest-priority structural assessment in the framework.
- The six-check diagnostic sequence: balance vs. equity, position accumulation, max position count, defined max loss, win rate fingerprint, holding time comparison.
- The two-or-more convergence threshold for structural findings.
- What happens after Step 2 — the pass/fail branching logic.
The surface inventory from Step 1 generates a catalog of claims: equity curve shape, win rate figures, drawdown numbers, return percentages. Step 2 subjects those claims to the first structural test by deploying the entire Structural Integrity pillar toolkit. The central question is direct: is this system storing unrealized losses inside open positions right now?
This is the highest-priority structural assessment because warehoused risk is the most common and most dangerous failure mode in the retail algorithmic trading space. A system that warehouses risk manufactures the appearance of consistent profitability by holding losing positions open while closing winners. Every surface metric cataloged in Step 1 — the equity curve, the win rate, the drawdown figure — is distorted by this mechanism.
What Step 2 tests for.
The defining characteristic of warehoused risk is the accumulation of unrealized losses inside open positions to create a smooth equity curve. The balance curve, which records only completed transactions, rises steadily as small winners close. The equity curve, which reflects the account's actual value including open positions, diverges beneath it.
This is not a matter of short-term position management. Systems that warehouse risk structurally depend on holding losing positions for extended periods, often adding to those positions, while counting the closure of each small winning segment as a separate profitable trade.
The diagnostic sequence.
The Institute's framework applies a sequence of checks, each targeting a specific observable behavior associated with warehoused risk. No single check is definitive in isolation. The diagnostic power comes from the pattern that emerges when multiple checks produce consistent findings.
The decision threshold.
The individual checks each have legitimate alternative explanations when considered alone. A high win rate can reflect a genuinely effective entry methodology. Holding multiple positions can reflect portfolio diversification. The diagnostic significance emerges from convergence.
What happens after Step 2.
The pass/fail outcome also determines how the evaluator interprets vendor responses to diagnostic questions. The Credible Answers vs. Deflection framework provides the analytical lens for assessing whether a vendor's explanations for any of these findings are substantive or evasive.
Frequently asked questions.
The Algo Institute's Six-Step System checks for warehoused risk using a diagnostic sequence: verify whether drawdown is measured from balance or equity, examine position holding and accumulation behavior, check for a defined maximum loss, test whether the win rate falls in the 66-78% fingerprint range, and compare holding times of winners versus losers. If the system fails two or more checks, the framework identifies warehoused risk as likely present.
Warehoused risk is the most common and most dangerous structural failure mode. A system that stores unrealized losses invalidates every surface metric — the equity curve, win rate, and drawdown figures are all distorted. The Institute checks for it first because identifying this condition prevents spending analytical effort on metrics that may be structurally unreliable.
If a system reports drawdown from balance only and cannot show equity-based drawdown, the Institute's framework treats this as a significant diagnostic signal. Balance-based drawdown excludes unrealized losses on open positions, which is the defining characteristic of warehoused risk.