#!/usr/bin/env python
# -*- coding: utf-8 -*-
__author__ = 'limin'
'''
海龟策略 (难度：中级)
参考: https://www.shinnytech.com/blog/turtle/
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
'''
import json
import time
from tqsdk import TqApi, TargetPosTask
from tqsdk.ta import ATR
class Turtle:
def __init__(self, symbol, account=None, donchian_channel_open_position=20, donchian_channel_stop_profit=10,
atr_day_length=20, max_risk_ratio=0.5):
self.account = account # 交易账号
self.symbol = symbol # 合约代码
self.donchian_channel_open_position = donchian_channel_open_position # 唐奇安通道的天数周期(开仓)
self.donchian_channel_stop_profit = donchian_channel_stop_profit # 唐奇安通道的天数周期(止盈)
self.atr_day_length = atr_day_length # ATR计算所用天数
self.max_risk_ratio = max_risk_ratio # 最高风险度
self.state = {
"position": 0, # 本策略净持仓数(正数表示多头，负数表示空头，0表示空仓)
"last_price": float("nan"), # 上次调仓价
}
self.n = 0 # 平均真实波幅(N值)
self.unit = 0 # 买卖单位
self.donchian_channel_high = 0 # 唐奇安通道上轨
self.donchian_channel_low = 0 # 唐奇安通道下轨
self.api = TqApi(self.account)
self.quote = self.api.get_quote(self.symbol)
# 由于ATR是路径依赖函数，因此使用更长的数据序列进行计算以便使其值稳定下来
kline_length = max(donchian_channel_open_position + 1, donchian_channel_stop_profit + 1, atr_day_length * 5)
self.klines = self.api.get_kline_serial(self.symbol, 24 * 60 * 60, data_length=kline_length)
self.account = self.api.get_account()
self.target_pos = TargetPosTask(self.api, self.symbol)
def recalc_paramter(self):
# 平均真实波幅(N值)
self.n = ATR(self.klines, self.atr_day_length)["atr"].iloc[-1]
# 买卖单位
self.unit = int((self.account.balance * 0.01) / (self.quote.volume_multiple * self.n))
# 唐奇安通道上轨：前N个交易日的最高价
self.donchian_channel_high = max(self.klines.high[-self.donchian_channel_open_position - 1:-1])
# 唐奇安通道下轨：前N个交易日的最低价
self.donchian_channel_low = min(self.klines.low[-self.donchian_channel_open_position - 1:-1])
print("唐其安通道上下轨: %f, %f" % (self.donchian_channel_high, self.donchian_channel_low))
return True
def set_position(self, pos):
self.state["position"] = pos
self.state["last_price"] = self.quote["last_price"]
self.target_pos.set_target_volume(self.state["position"])
def try_open(self):
"""开仓策略"""
while self.state["position"] == 0:
self.api.wait_update()
if self.api.is_changing(self.klines.iloc[-1], "datetime"): # 如果产生新k线,则重新计算唐奇安通道及买卖单位
self.recalc_paramter()
if self.api.is_changing(self.quote, "last_price"):
print("最新价: %f" % self.quote.last_price)
if self.quote.last_price > self.donchian_channel_high: # 当前价>唐奇安通道上轨，买入1个Unit；(持多仓)
print("当前价>唐奇安通道上轨，买入1个Unit(持多仓): %d 手" % self.unit)
self.set_position(self.state["position"] + self.unit)
elif self.quote.last_price < self.donchian_channel_low: # 当前价<唐奇安通道下轨，卖出1个Unit；(持空仓)
print("当前价<唐奇安通道下轨，卖出1个Unit(持空仓): %d 手" % self.unit)
self.set_position(self.state["position"] - self.unit)
def try_close(self):
"""交易策略"""
while self.state["position"] != 0:
self.api.wait_update()
if self.api.is_changing(self.quote, "last_price"):
print("最新价: ", self.quote.last_price)
if self.state["position"] > 0: # 持多单
# 加仓策略: 如果是多仓且行情最新价在上一次建仓（或者加仓）的基础上又上涨了0.5N，就再加一个Unit的多仓,并且风险度在设定范围内(以防爆仓)
if self.quote.last_price >= self.state[
"last_price"] + 0.5 * self.n and self.account.risk_ratio <= self.max_risk_ratio:
print("加仓:加1个Unit的多仓")
self.set_position(self.state["position"] + self.unit)
# 止损策略: 如果是多仓且行情最新价在上一次建仓（或者加仓）的基础上又下跌了2N，就卖出全部头寸止损
elif self.quote.last_price <= self.state["last_price"] - 2 * self.n:
print("止损:卖出全部头寸")
self.set_position(0)
# 止盈策略: 如果是多仓且行情最新价跌破了10日唐奇安通道的下轨，就清空所有头寸结束策略,离场
if self.quote.last_price <= min(self.klines.low[-self.donchian_channel_stop_profit - 1:-1]):
print("止盈:清空所有头寸结束策略,离场")
self.set_position(0)
elif self.state["position"] < 0: # 持空单
# 加仓策略: 如果是空仓且行情最新价在上一次建仓（或者加仓）的基础上又下跌了0.5N，就再加一个Unit的空仓,并且风险度在设定范围内(以防爆仓)
if self.quote.last_price <= self.state[
"last_price"] - 0.5 * self.n and self.account.risk_ratio <= self.max_risk_ratio:
print("加仓:加1个Unit的空仓")
self.set_position(self.state["position"] - self.unit)
# 止损策略: 如果是空仓且行情最新价在上一次建仓（或者加仓）的基础上又上涨了2N，就平仓止损
elif self.quote.last_price >= self.state["last_price"] + 2 * self.n:
print("止损:卖出全部头寸")
self.set_position(0)
# 止盈策略: 如果是空仓且行情最新价升破了10日唐奇安通道的上轨，就清空所有头寸结束策略,离场
if self.quote.last_price >= max(self.klines.high[-self.donchian_channel_stop_profit - 1:-1]):
print("止盈:清空所有头寸结束策略,离场")
self.set_position(0)
def strategy(self):
"""海龟策略"""
print("等待K线及账户数据...")
deadline = time.time() + 5
while not self.recalc_paramter():
if not self.api.wait_update(deadline=deadline):
raise Exception("获取数据失败，请确认行情连接正常并已经登录交易账户")
while True:
self.try_open()
self.try_close()
turtle = Turtle("SHFE.au1912")
print("策略开始运行")
try:
turtle.state = json.load(open("turtle_state.json", "r")) # 读取数据: 本策略目标净持仓数,上一次开仓价
except FileNotFoundError:
pass
print("当前持仓数: %d, 上次调仓价: %f" % (turtle.state["position"], turtle.state["last_price"]))
try:
turtle.strategy()
finally:
turtle.api.close()
json.dump(turtle.state, open("turtle_state.json", "w")) # 保存数据