Neutral Futures Grid Trading Within a Price Range
Article Strategy library · Author: 51bitquant
Summary
This Binance futures strategy places buy and sell limit orders at intervals across a configured price range. It calculates grid spacing from the range’s upper and lower bounds and the number of grid levels, then uses the current bid to place orders on either side. When an order fills, it places a counter-order one grid step away and may replenish the same-side order ladder up to a configured limit.
The document says the approach works well in ranging conditions but can incur a large loss from a single stop during a trending market. The code tracks open orders and trade count, and cancels all orders if their combined count exceeds a threshold. It does not provide backtest results or a detailed stop mechanism, so the stated weakness and operational behavior should be assessed before use. Grid bounds, spacing, order size, and maximum open orders are configurable.
Key ideas
- The strategy distributes limit orders across a configured futures price range.
- Filled orders trigger counter-orders at adjacent grid levels.
- The grid replenishes orders while respecting a configured limit on each side.
- The document identifies prolonged trends as a risk for large losses.
- No backtest evidence or detailed stop implementation is provided.
Tags
Full text
# FutureNeutralGridStrategy
# FutureNeutralGridStrategy
币安合约中性网格
策略在震荡行情下表现很好，但是如果发生趋势行情，单次止损会比较大，导致亏损过多。
免责声明: 本策略仅供测试参考，本人不负有任何责任。使用前请熟悉代码。测试其中的bugs, 请清楚里面的功能后再使用。
币安邀请链接: https://www.binancezh.pro/cn/futures/ref/51bitquant
合约邀请码：51bitquant
## Source (MIT)
```python
from howtrader.app.cta_strategy import (
CtaTemplate,
StopOrder
)
from howtrader.trader.object import TickData, BarData, TradeData, OrderData
from howtrader.app.cta_strategy.engine import CtaEngine
from howtrader.trader.object import Status
from typing import Optional
from howtrader.trader.utility import BarGenerator
from decimal import Decimal
class FutureNeutralGridStrategy(CtaTemplate):
"""
币安合约中性网格
策略在震荡行情下表现很好，但是如果发生趋势行情，单次止损会比较大，导致亏损过多。
免责声明: 本策略仅供测试参考，本人不负有任何责任。使用前请熟悉代码。测试其中的bugs, 请清楚里面的功能后再使用。
币安邀请链接: https://www.binancezh.pro/cn/futures/ref/51bitquant
合约邀请码：51bitquant
"""
author = "51bitquant"
high_price = 0.0 # 执行策略的最高价.
low_price = 0.0 # 执行策略的最低价.
grid_count = 100 # 网格的数量.
order_volume = 0.05 # 每次下单的数量.
max_open_orders = 2 # 一边订单的数量.
trade_count = 0
parameters = ["high_price", "low_price", "grid_count", "order_volume", "max_open_orders"]
variables = ["trade_count"]
def __init__(self, cta_engine: CtaEngine, strategy_name, vt_symbol, setting):
""""""
super().__init__(cta_engine, strategy_name, vt_symbol, setting)
self.long_orders = [] # 所有的long orders.
self.short_orders = [] # 所有的short orders.
self.tick: Optional[TickData] = None
self.bg = BarGenerator(self.on_bar)
self.step_price = 0
def on_init(self):
"""
Callback when strategy is inited.
"""
self.write_log("策略初始化")
def on_start(self):
"""
Callback when strategy is started.
"""
self.write_log("策略启动")
def on_stop(self):
"""
Callback when strategy is stopped.
"""
self.write_log("策略停止")
def on_tick(self, tick: TickData):
"""
Callback of new tick data update.
"""
if tick and tick.bid_price_1 > 0:
self.tick = tick
self.bg.update_tick(tick)
def on_bar(self, bar: BarData):
"""
Callback of new bar data update.
"""
if not self.tick:
return
if len(self.long_orders) == 0 or len(self.short_orders) == 0:
self.step_price = (self.high_price - self.low_price) / self.grid_count
mid_count = round((self.tick.bid_price_1 - self.low_price) / self.step_price)
if len(self.long_orders) == 0:
for i in range(self.max_open_orders):
price = self.low_price + (mid_count - i - 1) * self.step_price
if price < self.low_price:
break
orders = self.buy(Decimal(price), Decimal(self.order_volume))
self.long_orders.extend(orders)
if len(self.short_orders) == 0:
for i in range(self.max_open_orders):
price = self.low_price + (mid_count + i + 1) * self.step_price
if price > self.high_price:
break
orders = self.short(Decimal(price), Decimal(self.order_volume))
self.short_orders.extend(orders)
if len(self.short_orders + self.long_orders) > 100:
self.cancel_all()
self.put_event()
def on_order(self, order: OrderData):
"""
Callback of new order data update.
"""
if order.vt_orderid not in (self.short_orders + self.long_orders):
return
if order.status == Status.ALLTRADED:
if order.vt_orderid in self.long_orders:
self.long_orders.remove(order.vt_orderid)
self.trade_count += 1
short_price = order.price + Decimal(self.step_price)
if short_price <= self.high_price:
orders = self.short(short_price, Decimal(self.order_volume))
self.short_orders.extend(orders)
if len(self.long_orders) < self.max_open_orders:
count = len(self.long_orders) + 1
long_price = order.price - Decimal(self.step_price) * Decimal(str(count))
if long_price >= self.low_price:
orders = self.buy(long_price, Decimal(self.order_volume))
self.long_orders.extend(orders)
if order.vt_orderid in self.short_orders:
self.short_orders.remove(order.vt_orderid)
self.trade_count += 1
long_price = order.price - Decimal(self.step_price)
if long_price >= self.low_price:
orders = self.buy(long_price, Decimal(self.order_volume))
self.long_orders.extend(orders)
if len(self.short_orders) < self.max_open_orders:
count = len(self.long_orders) + 1
short_price = order.price + Decimal(self.step_price) * Decimal(str(count))
if short_price <= self.high_price:
orders = self.short(short_price, Decimal(self.order_volume))
self.short_orders.extend(orders)
if not order.is_active():
if order.vt_orderid in self.long_orders:
self.long_orders.remove(order.vt_orderid)
elif order.vt_orderid in self.short_orders:
self.short_orders.remove(order.vt_orderid)
self.put_event()
def on_trade(self, trade: TradeData):
"""
Callback of new trade data update.
"""
self.put_event()
def on_stop_order(self, stop_order: StopOrder):
"""
Callback of stop order update.
"""
pass
```Shown in full with attribution under the source's licence. Licence: MIT
This summary was written by Stratmill's research agent from the original; it is not a copy of the source.