Evidence Coverage Scorecard
Review evidence coverage across historical, OOS, stress, forward and parameter-stability testing.
- Five-layer weighting
- Evidence-gate warnings
- Release-readiness posture
Research tools / Validation infrastructure
A growing suite of deterministic calculators and validation utilities designed to make strategy analysis more explicit, comparable and reproducible. The tools are not signals, forecasts or portfolio advice. They are decision-support utilities for systematic trading research.
Professional calculators
Each calculator runs locally, explains its inputs and keeps the output within a defined decision-support role. It does not predict future performance.
Review evidence coverage across historical, OOS, stress, forward and parameter-stability testing.
Calculate the nonlinear return required to recover from a drawdown and test a constant-rate recovery scenario.
Estimate net expectancy from win rate, average outcome and recurring transaction costs.
Generate seeded trade sequences to inspect equity dispersion, drawdown percentiles and risk-of-ruin scenarios.
Build rolling or anchored IS/OOS schedules and inspect coverage, overlap, gaps and window boundaries.
Compare two local scenario snapshots to document changed inputs and key outputs before a research decision.
Combine selected local snapshots with a documented research decision and exportable review record.
Import a tester summary locally, normalize detected metrics and expose missing evidence before a review.
Record a test question, controlled change, evidence boundary, decision and next action in one exportable local entry.
Stress spread, commission, slippage and adverse-fill assumptions against a separately declared gross expectancy.
Recommended workflow
The site should guide users through a disciplined sequence: risk feasibility, expectancy, validation coverage, simulation and report review.
Check drawdown recovery and capital-buffer pressure before reading return metrics.
Include spread, commission, slippage and execution cost in the model.
Separate historical, OOS, stress and forward records before drawing conclusions.
Use Monte Carlo to inspect drawdown dispersion and unfavorable trade order.
Normalize MT5 tester reports into comparable metrics and distributions.
Document the test context, evidence boundary, decision and next research action.
Next modules / Current releases
MT5 Report Analyzer and Execution Cost Stress Analyzer have moved into the professional library. The remaining modules stay visible with their current development status and methodology boundaries.
Import MetaTrader 5 reports and normalize performance, risk, execution and trade-distribution metrics into one structured review.
Measure how spread, commission, slippage, entry/exit degradation and broker variation can erode expectancy.
Visualize parameter neighborhoods, plateaus, cliffs and isolated optima across performance, drawdown and trade-count surfaces.
Detect low sample size, result concentration, outlier dependence, directional asymmetry and unstable rolling performance.
Compare systems under one validation schema across historical, recent, OOS, stress and forward evidence.
Estimate position size, cash risk, margin context and aggregate exposure across multiple or correlated positions.
Full library / 25 calculators
The catalogue is a product direction, not a release promise. Ten calculators are available today; the other fifteen remain clearly marked as coming soon.
Capital pressure, drawdown recovery and position-level limits.
Trade-level expectancy, outcome distribution and edge quality.
Evidence coverage, stability checks and adverse sequencing.
Execution cost, reports and broker-environment variance.
Comparable evidence and aggregate exposure across systems.
Repeatable testing records, review gates and publication structure.
Operating principles
Inputs, formulas and scenario constraints are documented alongside each output.
Current tools process inputs in the browser and do not transmit or retain user-entered values.
Outputs describe mathematical relationships or validation coverage. They do not predict future performance.
All modules should use consistent labels, risk language and evidence classes across the site.