Articles

Backtested evidence, not polished chart examples, should determine whether an indicator earns a place in a real-money trading process.

Seasonality becomes directly comparable across seven BTS Heatmaps built with shared metrics, Zone rules and standardized backtests.

Reliable backtests preserve strategy fidelity, use consistent environments, model frictions, choose fair benchmarks and disclose limits.

Backtested Strategies matters more than ever in the age of AI because BTS turns AI-aggregated trading rules into backtests under a common methodology.

Backtests fail in live trading when data, timing, costs, liquidity, accounting, benchmarks or overfitting are ignored in the simulation.

Backtest headlines strip away methodology, structure and evidence—the exact context serious investors need before trusting a result.

Proxy backtests can answer useful questions when original markets, data, or rules cannot be replicated directly—if substitutes and limits are disclosed.

A signal can point to a pattern, but a strategy needs rules, timing, sizing, costs, accounting, benchmarks, and failure-mode review before it deserves trust.

A credible backtest is a proving ground for signals, costs, execution, accounting, benchmarks, failure modes and uncertainty under pressure.

A standardized methodology makes backtest assumptions visible and results easier to inspect, compare, challenge and trust across strategies.

Benchmark choice directly determines the question a backtest answers: opportunity set, control portfolio, active overlay and trade-offs.

The January Barometer and January Confirmation Indicator split in 2026 as weak breadth and higher volatility blocked a clear risk-on signal.