Concepts

Market Lab is organized around three layers:

• source: raw market data access
• study: computed market metrics built on top of market data
• strategy: logic that consumes a time series and emits live events or backtest summaries

This separation matters because it keeps the CLI predictable.

Source

source commands expose provider data directly.

Examples:

• source orderbook
• source candles
• source vd

Use source when you want:

• current market state
• raw or lightly-normalized time series
• streaming updates from a provider

Study

study commands compute market structure or execution metrics from source data.

Examples:

• study spread
• study depth
• study imbalance
• study slippage
• study vamp
• study cvd

Use study when you want:

• execution cost estimates
• liquidity shape
• orderbook imbalance
• derived statistics that are more useful than raw provider output

Strategy

strategy commands consume time-series data and evaluate logic over it.

Current example:

• strategy run sma-crossover
• strategy backtest sma-crossover

There are two modes:

• run mode for live evaluation
• backtest mode for historical evaluation

Run mode returns event-oriented output.

Backtest mode returns summary-oriented performance output.

Time Model

Market Lab uses milliseconds at the app boundary.

That means --from, --to, and ts_ms are millisecond-oriented in the CLI and JSON outputs.

Some providers, such as MMT, accept seconds over their API. Market Lab converts to provider-native units only at the adapter boundary.

Output Modes

The CLI is designed for both humans and machines.

• terminal: compact human-readable output
• json: machine-readable output
• jsonl: stream-friendly machine-readable output

For study and strategy, default JSON is compact. Add --verbose if you want expanded context.