See Also

• Optimization - Performance optimization techniques
• Performance Issues - Troubleshooting: Performance optimization techniques
• Data Management - Guide: Data handling and management
• Exchanges - Data handling and management
• Strategy Development - Guide: Strategy development and implementation
• Optimization - Strategy development and implementation

High-Frequency Trading (HFT) Backtesting Documentation

The SimMode class, also known as the planar backtester, utilizes Open-High-Low-Close-Volume (OHLCV) data to simulate the execution of trades.

Reasons to Avoid Tick-by-Tick Backtesting

Tick-by-tick backtesting may not be ideal due to several factors:

• Data Availability: Bid/ask tick data is often difficult to obtain and can be extremely voluminous, leading to increased resource consumption.
• Data Reconstruction: Attempting to reconstruct order book data from trade history is speculative and can introduce significant bias.
• Overfitting Risks: High-detail backtesting can cause strategies to overfit to specific market maker behaviors, resulting in additional bias.
• Computational Costs: Intensive data and computational requirements may limit backtesting to a short time frame, insufficient for evaluating performance through different market conditions.

Implementing HFT Backtesting

Two approaches are available for HFT-style backtesting.

Built-in Tick-Based Backtesting

SimMode ships with a tick-based backtester that replays the market's trade stream trade by trade — no new execution mode is needed. See Running a Backtest → Tick-by-Tick Backtesting for the full details. In short:

• Each universe asset needs a tick DataFrame with :timestamp, :price, :amount columns (the schema returned by Planar.Fetch.fetch_trades), stored with Planar.Instances.setticks!.
• The strategy implements ping!(s, ctx, tick) instead of call!.
• The backtest runs with:

ctx = TickContext(Sim(), TradeTickRange(s))
start!(s, ctx)

OHLCV-Based Approach

• A simpler method involves using the OHLCV model with extremely short-duration candles, such as 1s candles. The backtester processes time steps, typically using the strategy's base timeframe. By selecting a 1s timeframe and supplying the corresponding candles, you can achieve the desired time resolution for your backtest.