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docs: update the README and the example.
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nkaz001 committed Aug 14, 2024
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Expand Up @@ -4,11 +4,6 @@ HftBacktest

|codeql| |python| |pypi| |downloads| |rustc| |crates| |license| |docs| |roadmap| |github|

**The master branch is switched to hftbacktest-2.0.0-alpha, which uses the Rust implementation as the backend. If you want to see the current version 1.8.4, please check out the corresponding tag.**

* `Browse v1.8.4 <https://github.com/nkaz001/hftbacktest/tree/20cd9470a431e90c526eca6975ef389073c9aca5>`_
* `Docs v1.8.4 <https://hftbacktest.readthedocs.io/en/v1.8.4/>`_

High-Frequency Trading Backtesting Tool
=======================================

Expand All @@ -28,10 +23,6 @@ support the following features.
* Backtesting of multi-asset and multi-exchange models
* Deployment of a live trading bot using the same algorithm code: currently for Binance Futures and Bybit. (Rust-only)

Example: The complete process of backtesting Binance Futures
------------------------------------------------------------
`high-frequency gridtrading <https://github.com/nkaz001/hftbacktest/blob/master/hftbacktest/examples/gridtrading.ipynb>`_: The complete process of backtesting Binance Futures using a high-frequency grid trading strategy implemented in Rust.

Documentation
=============

Expand Down Expand Up @@ -60,6 +51,8 @@ Data Source & Format

Please see `Data <https://hftbacktest.readthedocs.io/en/latest/data.html>`_ or `Data Preparation <https://hftbacktest.readthedocs.io/en/latest/tutorials/Data%20Preparation.html>`_.

You can also find some data `here <https://reach.stratosphere.capital/data/usdm/>`_, hosted by the supporter.

A Quick Example
---------------

Expand All @@ -68,83 +61,98 @@ Get a glimpse of what backtesting with hftbacktest looks like with these code sn
.. code-block:: python
@njit
def simple_two_sided_quote(hbt):
max_position = 5
half_spread = hbt.tick_size * 20
skew = 1
order_qty = 0.1
last_order_id = -1
order_id = 0
def market_making_algo(hbt):
asset_no = 0
tick_size = hbt.depth(asset_no).tick_size
lot_size = hbt.depth(asset_no).lot_size
# Checks every 0.1s
while hbt.elapse(100_000_000) == 0:
# Clears cancelled, filled or expired orders.
# in nanoseconds
while hbt.elapse(10_000_000) == 0:
hbt.clear_inactive_orders(asset_no)
# Gets the market depth.
a = 1
b = 1
c = 1
hs = 1
# Alpha, it can be a combination of several indicators.
forecast = 0
# In HFT, it can be various measurements of short-term market movements,
# such as the high-low range in the last X minutes.
volatility = 0
# Delta risk, it can be a combination of several risks.
position = hbt.position(asset_no)
risk = (c + volatility) * position
half_spread = (c + volatility) * hs
max_notional_position = 1000
notional_qty = 100
depth = hbt.depth(asset_no)
# Obtains the current mid-price and computes the reservation price.
mid_price = (depth.best_bid + depth.best_ask) / 2.0
reservation_price = mid_price - skew * hbt.position(asset_no) * depth.tick_size
buy_order_price = reservation_price - half_spread
sell_order_price = reservation_price + half_spread
# fair value pricing = mid_price + a * forecast
# or underlying(correlated asset) + adjustment(basis + cost + etc) + a * forecast
# risk skewing = -b * risk
reservation_price = mid_price + a * forecast - b * risk
new_bid = reservation_price - half_spread
new_ask = reservation_price + half_spread
last_order_id = -1
# Cancel all outstanding orders
orders = hbt.orders(asset_no)
values = orders.values()
while True:
order = values.next()
if order is None:
break
if order.cancellable:
hbt.cancel(asset_no, order.order_id)
last_order_id = order.order_id
new_bid_tick = min(np.round(new_bid / tick_size), depth.best_bid_tick)
new_ask_tick = max(np.round(new_ask / tick_size), depth.best_ask_tick)
# 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(asset_no, last_order_id)
order_qty = np.round(notional_qty / mid_price / lot_size) * lot_size
# Clears cancelled, filled or expired orders.
hbt.clear_inactive_orders(asset_no)
# Elapses a process time.
if not hbt.elapse(1_000_000) != 0:
return False
last_order_id = -1
if hbt.position < max_position:
# Submits a new post-only limit bid order.
order_id += 1
hbt.submit_buy_order(
asset_no,
order_id,
buy_order_price,
order_qty,
GTX,
LIMIT,
False
)
last_order_id = -1
update_bid = True
update_ask = True
buy_limit_exceeded = position * mid_price > max_notional_position
sell_limit_exceeded = position * mid_price < -max_notional_position
orders = hbt.orders(asset_no)
order_values = orders.values()
while order_values.has_next():
order = order_values.get()
if order.side == BUY:
if order.price_tick == new_bid_tick or buy_limit_exceeded:
update_bid = False
if order.cancellable and (update_bid or buy_limit_exceeded):
hbt.cancel(asset_no, order.order_id, False)
last_order_id = order.order_id
elif order.side == SELL:
if order.price_tick == new_ask_tick or sell_limit_exceeded:
update_ask = False
if order.cancellable and (update_ask or sell_limit_exceeded):
hbt.cancel(asset_no, order.order_id, False)
last_order_id = order.order_id
# It can be combined with a grid trading strategy by submitting multiple orders to capture better spreads and
# have queue position.
# This approach requires more sophisticated logic to efficiently manage resting orders in the order book.
if update_bid:
# There is only one order at a given price, with new_bid_tick used as the order ID.
order_id = new_bid_tick
hbt.submit_buy_order(asset_no, order_id, new_bid_tick * tick_size, order_qty, GTX, LIMIT, False)
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(
asset_no,
order_id,
sell_order_price,
order_qty,
GTX,
LIMIT,
False
)
if update_ask:
# There is only one order at a given price, with new_ask_tick used as the order ID.
order_id = new_ask_tick
hbt.submit_sell_order(asset_no, order_id, new_ask_tick * tick_size, order_qty, GTX, LIMIT, False)
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(asset_no, last_order_id)
# Waits for the order response for a maximum of 5 seconds.
timeout = 5_000_000_000
if not hbt.wait_order_response(asset_no, last_order_id, timeout):
return False
return True
Tutorials
Expand All @@ -166,6 +174,10 @@ Examples

You can find more examples in `examples <https://github.com/nkaz001/hftbacktest/tree/master/examples>`_ directory and `Rust examples <https://github.com/nkaz001/hftbacktest/tree/master/rust/examples>`_.

The complete process of backtesting Binance Futures
---------------------------------------------------
`high-frequency gridtrading <https://github.com/nkaz001/hftbacktest/blob/master/hftbacktest/examples/gridtrading.ipynb>`_: The complete process of backtesting Binance Futures using a high-frequency grid trading strategy implemented in Rust.

Migration to V2
===============
Please see the `migration guide <https://hftbacktest.readthedocs.io/en/latest/Migration%20To%20v2.html>`_.
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