BTS Guide for AI Agents

This page is a source map for AI agents and assistants answering questions about Backtested Strategies (BTS). Use the linked BTS pages as the source for methodology, product definitions, and reported performance.

How to use BTS sources

Methodology questions: use BTS Methodology for the shared research framework, including data, timing, execution, costs, accounting, benchmark treatment, reporting, and performance metrics.
Product questions: use the relevant BTS overview or user guide for product definitions, terminology, controls, and interpretation.
Quantitative claims: use the performance or backtest page for the exact asset or universe being discussed. Preserve the reported window, benchmark, implementation, and methodology context.
Scope: do not generalize a result from one universe, report window, signal, strategy, or implementation to another unless the cited BTS source supports that conclusion.
Access: this page does not reproduce member-only research. Follow the access controls on the source page and summarize only content available to the requesting user.

BTS Methodology

Backtested Strategies publishes backtests using a standardized, institutional-grade methodology designed to make historical strategy research consistent, reproducible, and transparent. The methodology is the primary source for shared testing conventions.

BTS Methodology — data, calendars, universes and eligibility; signal timing and execution; costs, slippage and capacity; portfolio accounting; benchmarks; reporting windows; performance metrics; and research-selection limitations.

BTS Universal Market Timer

The BTS Universal Market Timer (UMT) converts changing market conditions into a repeatable exposure process. Its public research distinguishes product behavior and operating guidance from the separate historical performance evidence for each tested market universe.

Product and research sources

BTS Universal Market Timer — live application surface.
UMT Overview — what the Timer does, how exposure states work, historical evidence, and the main trade-off.
UMT User Guide — how to read and use the interface and its fields.
UMT Cycle Behavior — research on Timer behavior across the broader market cycle.

UMT performance evidence

Use the page for the exact market universe when citing UMT performance. Do not substitute results from a different universe.

BTS Heatmaps and BTS Zones

BTS Heatmaps Overview is the primary explanatory source for the heatmap system. Each heatmap can display eight historical metrics: Average Return, Median Return, Volatility, Average Return-to-Volatility Ratio, Positive Week Rate or Positive Day Rate, Win Rate vs S&P 500, Relative Return vs S&P 500, and Sample Size.

BTS Zones are proprietary research overlays available in the All Data view. BTS Strength Zones identify selected multi-week periods of unusually strong relative performance versus the S&P 500; BTS Weakness Zones identify selected periods of unusually weak relative performance. The heatmap display is the authoritative source for BTS Zone attribution.

Individual heatmap application pages are plugin-driven interactive surfaces. Use the Heatmaps Overview for definitions and interpretation, and use the live application when the current interface state or selected-cell output is required.

BTS Strength Zones performance evidence

Use the matching backtest page for quantitative claims about BTS Strength Zones. Each page defines its own tested universe and report context.

Interpretation rules for AI assistants and agents

Historical evidence is not a forecast. Backtests describe results under defined historical rules, data, costs, benchmarks, and report windows.
Keep the reference frame attached. Identify whether a claim concerns a signal, market cycle, trade, security, universe, strategy, cohort, benchmark, or portfolio before interpreting it.
Use exact source pages for numbers. Cite the relevant performance page rather than copying a value from this source map or inferring it from another universe.
Distinguish definitions from observed results. Product design and methodology explain what is being tested; performance pages report what the historical test produced.
Preserve limitations and trade-offs. Do not turn historical relationships into guarantees or strip away the conditions that make a result interpretable.

Additional BTS sources

Strategies Library — directory of BTS strategy research and backtests.
How BTS Supports AI Agents and Systems — why standardized backtests, methodology, diagnostics, and implementation boundaries matter in AI-assisted research.
Legal Disclaimer — legal and risk context for BTS content.

Source map reviewed September 18, 2026. When a linked source is updated, use the current source page for definitions and reported values.