Choosing Backtest Data and Matching Venue Book Types
Summary
This guide explains how historical data drives a backtest and how venue book configuration affects simulated matching. It ranks inputs by detail: market-by-order depth, market-by-price depth, top-of-book quotes, trade ticks, and interval bars. More detailed records reveal more of the observed queue and depth, while bars are often easier and cheaper to obtain for early signal research.
The venue’s book type must suit the data used for execution. Level 1 books can update from quotes or bars, while Level 2 and Level 3 books require order book data for book updates; mismatched inputs may be ignored even as the backtest clock and strategy data callbacks continue. Trade ticks can trigger matching across the listed book types. The guide cautions that recorded data cannot show the market impact of simulated orders, and bars cannot establish spread, queue position, or intrabar price order. It recommends validating execution-sensitive strategies with more granular data; it provides configuration behavior rather than performance evidence.
Key ideas
- Order book data provides more recorded execution detail than quotes, trades, or bars.
- Bars can support early signal development but cannot reveal spread, queue position, or intrabar price order.
- The venue book type determines which data updates book state for simulated matching.
- Level 2 and Level 3 books ignore quote and bar updates, so suitable order book data is needed.
- More detailed historical records still cannot show how simulated orders would alter the market.
Tags
Full text
# Backtest Data and Venues
# Backtest Data and Venues
## Data
Historical data advances the backtest clock, updates simulated market state, and drives strategy
callbacks. The venue's `book_type` determines which data can update the matching book, so the
configuration must match the available data.
Order book data exposes more execution detail than quotes, trades, or bars, but even a recorded
book cannot show how a simulated order would have changed the market. NautilusTrader supports the
following data in descending order of detail:
```mermaid
flowchart LR
L3["L3 Order Book<br/>(market-by-order)"]
L2["L2 Order Book<br/>(market-by-price)"]
L1["L1 Quotes<br/>(top of book)"]
T["Trades"]
B["Bars"]
L3 --> L2 --> L1 --> T --> B
style L3 fill:#2d5a3d,color:#fff
style L2 fill:#3d6a4d,color:#fff
style L1 fill:#4d7a5d,color:#fff
style T fill:#5d8a6d,color:#fff
style B fill:#6d9a7d,color:#fff
```
More granular data exposes more of the recorded queue and depth, while less granular data requires
more simulation assumptions.
- **L3 order book data (market-by-order)**: Individual orders at each recorded price level.
- **L2 order book data (market-by-price)**: Aggregate size at each recorded price level.
- **L1 quote ticks (market-by-price)**: Best bid and ask prices and sizes.
- **Trade ticks**: Recorded executions.
- **Bars**: Aggregated price and volume over fixed intervals.
### Choosing data: cost vs. accuracy
Bar data can be sufficient for early strategy development and is often cheaper and easier to
obtain than tick or order book data. It cannot establish intrabar price order, spread, depth, or
queue position, so execution-sensitive strategies need more granular validation.
:::tip
Start with bars to test the core signal when appropriate. Move to quotes, trades, or depth data
before relying on results that depend on spread, exact intrabar order, tight exits, or queue
position.
:::
## Venues
When initializing a venue for backtesting, you must specify its internal order `book_type` for
execution processing from the following options:
- `L1_MBP`: Level 1 market-by-price (default). Only the top level of the order book is maintained.
- `L2_MBP`: Level 2 market-by-price. Order book depth is maintained, with a single order aggregated
per price level.
- `L3_MBO`: Level 3 market-by-order. Order book depth is maintained, with all individual orders
tracked as provided by the data.
The `book_type` determines which data updates book state and drives matching. Data that does not
apply to the selected book is ignored for book and price updates, but the outer backtest clock still
advances. Strategies continue to receive subscribed data through the data engine. Precision
validation depends on the matching path; for example, a bar ignored by an L2 or L3 venue returns
before executable-bar precision checks.
| Data type | L1_MBP | L2_MBP | L3_MBO |
| ----------------- | ----------------- | ----------------- | ----------------- |
| `QuoteTick` | Updates book | *Ignored* | *Ignored* |
| `TradeTick` | Triggers matching | Triggers matching | Triggers matching |
| `Bar` | Updates book | *Ignored* | *Ignored* |
| `OrderBookDelta` | *Ignored* | Updates book | Updates book |
| `OrderBookDeltas` | *Ignored* | Updates book | Updates book |
| `OrderBookDepth` | Updates book | Updates book | Updates book |
The granularity of the data must match the specified order `book_type`. Nautilus cannot generate
higher granularity data (L2 or L3) from lower-level data such as quotes, trades, or bars.
:::warning[L2 and L3 book data]
If you specify `L2_MBP` or `L3_MBO` as the venue's `book_type`, quotes and bars will not update the
book. Ensure you provide order book delta data, otherwise orders may appear as though they are never
filled.
:::
:::warning[L1 ignores order book deltas]
When using `L1_MBP` (the default), order book deltas are ignored by the matching engine. If you
subscribe to order book deltas, set the venue `book_type` to `L2_MBP` or `L3_MBO`. This also applies
to sandbox execution, where the matching engine uses the same `book_type` configuration.
:::Shown in full with attribution under the source's licence. Licence: LGPL-3.0
This summary was written by Stratmill's research agent from the original; it is not a copy of the source.