震荡行情·高级策略·网格交易策略

10 Aug 2020, 22:27 · Views 1,683

通常我们可以把行情简单分为三类：震荡行情、趋势行情和趋势反转行情。

其中震荡行情较为常见，特点就是行情价格在一定区域内来回扫荡，通过反复高抛低吸的方式就能获得不菲的利润，并且震荡行情的止损往往只发生在行情突破的时刻，从盈亏比角度来说，震荡行情把握好入场点，就能把握好风险以及获利足够的利润。

以下要介绍的网格交易法就是专为震荡行情所设计的，规则如下：

品种沥青，基础价格2040，在这个基础上价格每上涨千分之五则加一手空，往下每下跌千分之五则加一手多，一共10档。

#!/usr/bin/env python
#  -*- coding: utf-8 -*-
__author__ = 'limin'

"""
参考: https://www.shinnytech.com/blo...
注: 该示例策略仅用于功能示范
"""
from datetime import date
from functools import reduce
from tqsdk import TqApi, TargetPosTask,TqSim,TqBacktest

SYMBOL = "SHFE.bu2006" # 合约代码
START_PRICE = 2040 # 起始价位
GRID_AMOUNT = 10 # 网格在多头、空头方向的格子(档位)数量

api = TqApi(TqSim(init_balance=100000),web_gui=":9875",backtest=TqBacktest(start_dt=date(2020, 3, 10), end_dt=date(2020,5, 8)))
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 = [i for i in range(GRID_AMOUNT + 1)]  # 多头每格持仓手数
grid_volume_short = [i for i in range(GRID_AMOUNT + 1)]  # 空头每格持仓手数
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
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

print("策略开始运行, 起始价位: %f, 多头每格持仓手数:%s, 多头每格的价位:%s, 空头每格的价位:%s" % (
START_PRICE, grid_volume_long, grid_prices_long, grid_prices_short))
quote = api.get_quote(SYMBOL)  # 行情数据
target_pos = TargetPosTask(api, SYMBOL)
position = api.get_position(SYMBOL)  # 持仓信息


def wait_price(layer):
 """等待行情最新价变动到其他档位,则进入下一档位或回退到上一档位; 如果从下一档位回退到当前档位,则设置为当前对应的持仓手数;
        layer : 当前所在第几个档位层次; layer>0 表示多头方向, layer<0 表示空头方向
    """
 if layer > 0 or quote.last_price <= grid_prices_long[1]:  # 是多头方向
 while True:
            api.wait_update()
 # 如果当前档位小于最大档位,并且最新价小于等于下一个档位的价格: 则设置为下一档位对应的手数后进入下一档位层次
 if layer < GRID_AMOUNT and quote.last_price <= grid_prices_long[layer + 1]:
                target_pos.set_target_volume(grid_volume_long[layer + 1])
 print("最新价: %f, 进入: 多头第 %d 档" % (quote.last_price, layer + 1))
                wait_price(layer + 1)
 # 从下一档位回退到当前档位后, 设置回当前对应的持仓手数
                target_pos.set_target_volume(grid_volume_long[layer + 1])
 # 如果最新价大于当前档位的价格: 则回退到上一档位
 if quote.last_price > grid_prices_long[layer]:
 print("最新价: %f, 回退到: 多头第 %d 档" % (quote.last_price, layer))
 return
 elif layer < 0 or quote.last_price >= grid_prices_short[1]:  # 是空头方向
        layer = -layer  # 转为正数便于计算
 while True:
            api.wait_update()
 # 如果当前档位小于最大档位层次,并且最新价大于等于下一个档位的价格: 则设置为下一档位对应的持仓手数后进入下一档位层次
 if layer < GRID_AMOUNT and quote.last_price >= grid_prices_short[layer + 1]:
                target_pos.set_target_volume(-grid_volume_short[layer + 1])
 print("最新价: %f, 进入: 空头第 %d 档" % (quote.last_price, layer + 1))
                wait_price(-(layer + 1))
 # 从下一档位回退到当前档位后, 设置回当前对应的持仓手数
                target_pos.set_target_volume(-grid_volume_short[layer + 1])
 # 如果最新价小于当前档位的价格: 则回退到上一档位
 if quote.last_price < grid_prices_short[layer]:
 print("最新价: %f, 回退到: 空头第 %d 档" % (quote.last_price, layer))
 return


while True:
    api.wait_update()
    wait_price(0)  # 从第0层开始进入网格
    target_pos.set_target_volume(0)

收益可观，但是缺点也很明显：

1、只适合震荡市；

2、网格的密集程度和中枢事前难以精确指定；

3、策略对止损的控制较弱，遭遇单边行情容易爆仓。

Reprinted from 知乎，the copyright all reserved by the original author.

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震荡行情·高级策略·网格交易策略

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