Understanding the output

TradeJS output is meant for analysis and comparison, not for promises about future behavior.

Backtest Output

A backtest usually produces:

• console progress and summary lines
• statistics for each tested configuration
• order and position records when available
• optional AI or ML dataset chunks
• result indexes that the app can display

The exact shape depends on strategy config, connector, cache mode, and enabled AI/ML flags.

Common Metrics

• orders: number of closed simulated orders.
• wins: orders with positive result.
• losses: orders with negative result.
• winRate: wins divided by closed orders.
• netProfit: historical net result for the run.
• maxDrawdown: largest historical peak-to-trough decline.
• riskRewardRatio: relationship between average reward and risk when available.

Signal Output

A signal describes a strategy decision at a candle timestamp. It commonly includes:

• strategy
• symbol
• interval
• direction
• timestamp
• prices.currentPrice
• prices.takeProfitPrice
• prices.stopLossPrice
• figures for chart inspection
• indicators and additionalIndicators for context

AI/ML Output

When enabled, AI/ML layers may add:

• AI evaluations and explanations
• ML feature rows
• approval or rejection metadata
• quality and threshold values

These are research and order-filtering outputs. Validate them on historical data and monitor their behavior during live evaluation.

How To Read Results

Use results to answer practical questions:

• Did the strategy trade when expected?
• Are entries and exits explainable from the candle data?
• Do metrics remain stable across symbols and periods?
• Are fees, slippage, and fill timing assumptions realistic?
• Does the same logic behave consistently in backtest, replay, and live evaluation?

Next: review the backtesting caveats, then follow the controlled production rollout when the strategy is ready.