A Futures Grid Strategy with Staggered Entry and Exit Levels
Summary
This asynchronous example implements a futures grid around a chosen starting price. It creates multiple long and short trigger levels using repeated percentage steps, assigns a trade size to each level, and starts a watcher task for every grid interval. A watcher changes the aggregate target position when price reaches its entry threshold, then reverses that unit of exposure after price crosses the corresponding exit threshold. The example uses a Chinese commodity futures contract and a trading API to submit target positions.
The code demonstrates event-driven order logic, but it does not include backtest results, capital allocation, transaction costs, or safeguards for market gaps and persistent trends. Its evenly specified grid parameters and fixed per-level quantities are illustrative choices, and the accompanying comments explicitly present the example as a functional demonstration requiring adaptation for live trading. The sample therefore explains the mechanics of a basic grid, not evidence that the approach is profitable or suitable for a particular market.
Key ideas
- The strategy places long and short triggers at repeated percentage intervals around a starting price.
- Each grid watcher opens a unit of exposure at its entry threshold and closes it after a price reversal.
- The example aggregates all grid actions through a target-position task.
- The code is illustrative and provides no performance testing or risk controls for live use.
Tags
Full text
# gridtrading_async.py
```py
#!/usr/bin/env python
# -*- coding: utf-8 -*-
__author__ = 'chengzhi'
"""
网格交易策略
参考: https://www.shinnytech.com/blog/grid-trading/
注: 该示例策略仅用于功能示范, 实盘时请根据自己的策略/经验进行修改
"""
from functools import reduce
from contextlib import closing
from tqsdk import TqApi, TqAuth, TargetPosTask
# 网格计划参数:
symbol = "DCE.jd2011" # 合约代码
start_price = 4247 # 起始价位
grid_amount = 10 # 网格在多头、空头方向的格子(档位)数量
grid_region_long = [0.005] * grid_amount # 多头每格价格跌幅(网格密度)
grid_region_short = [0.005] * grid_amount # 空头每格价格涨幅(网格密度)
grid_volume_long = [1] * grid_amount # 多头每格交易手数
grid_volume_short = [-1] * grid_amount # 空头每格交易手数
grid_prices_long = [reduce(lambda p, r: p*(1-r), grid_region_long[:i], start_price) for i in range(grid_amount + 1)] # 多头每格的触发价位列表, 第一个元素为起始价位
grid_prices_short = [reduce(lambda p, r: p*(1+r), grid_region_short[:i], start_price) for i in range(grid_amount + 1)] # 空头每格的触发价位列表, 第一个元素为起始价位
print("起始价位:", start_price)
print("多头每格交易量:", grid_volume_long)
print("多头每格的价位:", grid_prices_long)
print("空头每格的价位:", grid_prices_short)
api = TqApi(auth=TqAuth("快期账户", "账户密码"))
quote = api.get_quote(symbol) # 行情数据
target_pos = TargetPosTask(api, symbol)
target_volume = 0 # 目标持仓手数
async def price_watcher(open_price, close_price, volume):
"""该task在价格触发开仓价时开仓，触发平仓价时平仓"""
global target_volume
async with api.register_update_notify(quote) as update_chan: # 当 quote 有更新时会发送通知到 update_chan 上
while True:
async for _ in update_chan: # 当从 update_chan 上收到行情更新通知时判断是否触发开仓条件
if (volume > 0 and quote.last_price <= open_price) or (volume < 0 and quote.last_price >= open_price):
break
target_volume += volume
target_pos.set_target_volume(target_volume)
print("时间:", quote.datetime, "最新价:", quote.last_price, "开仓", volume, "手", "总仓位:", target_volume, "手")
async for _ in update_chan: # 当从 update_chan 上收到行情更新通知时判断是否触发平仓条件
if (volume > 0 and quote.last_price > close_price) or (volume < 0 and quote.last_price < close_price):
break
target_volume -= volume
target_pos.set_target_volume(target_volume)
print("时间:", quote.datetime, "最新价:", quote.last_price, "平仓", volume, "手", "总仓位:", target_volume, "手")
for i in range(grid_amount):
api.create_task(price_watcher(grid_prices_long[i+1], grid_prices_long[i], grid_volume_long[i]))
api.create_task(price_watcher(grid_prices_short[i+1], grid_prices_short[i], grid_volume_short[i]))
with closing(api):
while True:
api.wait_update()
```Shown in full with attribution under the source's licence. Licence: Apache-2.0
This summary was written by Stratmill's research agent from the original; it is not a copy of the source.