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A high-frequency trading and market-making backtesting tool accounts for limit orders, queue positions, and latencies, utilizing full tick data for trades and order books.

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HftBacktest

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High-Frequency Trading Backtesting Tool in Python

This Python framework is designed for developing high-frequency trading and market-making strategies. It focuses on accounting for both feed and order latencies, as well as the order queue position for order fill simulation. The framework aims to provide more accurate market replay-based backtesting, based on full order book and trade tick feed data.

Key Features

  • Working in Numba JIT function.
  • Complete tick-by-tick simulation with a variable time interval.
  • Full order book reconstruction based on L2 feeds(Market-By-Price).
  • Backtest accounting for both feed and order latency, using provided models or your own custom model.
  • Order fill simulation that takes into account the order queue position, using provided models or your own custom model.

Documentation

See full document here.

Getting started

Installation

hftbacktest supports Python 3.8+. You can install hftbacktest using pip:

pip install hftbacktest

Or you can clone the latest development version from the Git repository with:

git clone https://github.com/nkaz001/hftbacktest

Data Source & Format

Please see Data or Data Preparation.

A Quick Example

Get a glimpse of what backtesting with hftbacktest looks like with these code snippets:

@njit
def simple_two_sided_quote(hbt, stat):
    max_position = 5
    half_spread = hbt.tick_size * 20
    skew = 1
    order_qty = 0.1
    last_order_id = -1
    order_id = 0

    # Checks every 0.1s
    while hbt.elapse(100_000):
        # Clears cancelled, filled or expired orders.
        hbt.clear_inactive_orders()

        # Obtains the current mid-price and computes the reservation price.
        mid_price = (hbt.best_bid + hbt.best_ask) / 2.0
        reservation_price = mid_price - skew * hbt.position * hbt.tick_size

        buy_order_price = reservation_price - half_spread
        sell_order_price = reservation_price + half_spread

        last_order_id = -1
        # Cancel all outstanding orders
        for order in hbt.orders.values():
            if order.cancellable:
                hbt.cancel(order.order_id)
                last_order_id = order.order_id

        # All order requests are considered to be requested at the same time.
        # Waits until one of the order cancellation responses is received.
        if last_order_id >= 0:
            hbt.wait_order_response(last_order_id)

        # Clears cancelled, filled or expired orders.
        hbt.clear_inactive_orders()

            last_order_id = -1
        if hbt.position < max_position:
            # Submits a new post-only limit bid order.
            order_id += 1
            hbt.submit_buy_order(
                order_id,
                buy_order_price,
                order_qty,
                GTX
            )
            last_order_id = order_id

        if hbt.position > -max_position:
            # Submits a new post-only limit ask order.
            order_id += 1
            hbt.submit_sell_order(
                order_id,
                sell_order_price,
                order_qty,
                GTX
            )
            last_order_id = order_id

        # All order requests are considered to be requested at the same time.
        # Waits until one of the order responses is received.
        if last_order_id >= 0:
            hbt.wait_order_response(last_order_id)

        # Records the current state for stat calculation.
        stat.record(hbt)

Examples

You can find more examples in examples directory.

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A high-frequency trading and market-making backtesting tool accounts for limit orders, queue positions, and latencies, utilizing full tick data for trades and order books.

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