residual-edge-analyzer

Residual Edge Analyzer

Overview

Test whether a strategy's apparent performance survives explicit comparison with predeclared baseline return series. Produce an auditable JSON artifact and a concise Markdown report without fetching data or changing trading exposure.

Treat this as a falsification gate after backtest-expert, not as trade authorization.

Prerequisites

• Use Python 3.9+.
• Prepare one CSV containing an ISO date, strategy return, and every baseline return on the same row.
• Prepare a JSON specification following references/input-contract.md.
• Supply actual period returns. Do not substitute CAGR, Sharpe, cumulative P&L, or other summary metrics.

Workflow

1. Define the question before inspecting results

State the claimed independent edge in one sentence. Select a primary baseline that is a plausible simple copy of the strategy, then select at least one alternate baseline model.

Record these declarations in the config:

• baseline_selection: predeclared
• strategy_return_basis and baseline_return_basis: both gross or both net
• analysis_scope: out_of_sample, live, or in_sample
• universe_data: point_in_time, current_constituents, or not_applicable

Every declaration is mandatory for a decision-grade verdict. Omitting one is treated as undeclared, not as benign, and drops the report to REVIEW_REQUIRED. not_applicable exists so that a baseline with no universe membership can be declared explicitly rather than left blank.

Do not choose a baseline because it gives the preferred residual result.

2. Validate the return-series contract

Require:

• unique ISO dates;
• finite numeric returns greater than -100%;
• identical frequency and cost basis across strategy and baselines;
• point-in-time membership for same-universe equal-weight or momentum baselines;
• regime labels defined independently of the loss periods being explained.

Stop if the input lacks a dated strategy return series. Report summary-only input as insufficient rather than inventing observations.