本文为Python语言实现海龟交易法则的源代码。

1. #!/usr/bin/env python
2. # -*- coding: utf-8 -*-
3. __author__ = 'limin'
4. 
   
5. '''
6. 海龟策略
7. 参考: https://www.shinnytech.com/blog/turtle/
8. 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
9. '''
10. 
    
11. import json
12. import time
13. from tqsdk import TqApi, TargetPosTask
14. from tqsdk.ta import ATR
15. 
    
16. 
    
17. class Turtle:
18. 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):
19. self.account = account # 交易账号
20. self.symbol = symbol # 合约代码
21. self.donchian_channel_open_position = donchian_channel_open_position # 唐奇安通道的天数周期(开仓)
22. self.donchian_channel_stop_profit = donchian_channel_stop_profit # 唐奇安通道的天数周期(止盈)
23. self.atr_day_length = atr_day_length # ATR计算所用天数
24. self.max_risk_ratio = max_risk_ratio # 最高风险度
25. self.state = {
26. "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)
27. "last_price": float("nan"), # 上次调仓价
28. }
29. 
    
30. self.n = 0 # 平均真实波幅(N值)
31. self.unit = 0 # 买卖单位
32. self.donchian_channel_high = 0 # 唐奇安通道上轨
33. self.donchian_channel_low = 0 # 唐奇安通道下轨
34. 
    
35. self.api = TqApi(self.account)
36. self.quote = self.api.get_quote(self.symbol)
37. # 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
38. kline_length = max(donchian_channel_open_position + 1, donchian_channel_stop_profit + 1, atr_day_length * 5)
39. self.klines = self.api.get_kline_serial(self.symbol, 24 * 60 * 60, data_length=kline_length)
40. self.account = self.api.get_account()
41. self.target_pos = TargetPosTask(self.api, self.symbol)
42. 
    
43. def recalc_paramter(self):
44. # 平均真实波幅(N值)
45. self.n = ATR(self.klines, self.atr_day_length)["atr"].iloc[-1]
46. # 买卖单位
47. self.unit = int((self.account.balance * 0.01) / (self.quote.volume_multiple * self.n))
48. # 唐奇安通道上轨：前N个交易日的最高价
49. self.donchian_channel_high = max(self.klines.high[-self.donchian_channel_open_position - 1:-1])
50. # 唐奇安通道下轨：前N个交易日的最低价
51. self.donchian_channel_low = min(self.klines.low[-self.donchian_channel_open_position - 1:-1])
52. print("唐其安通道上下轨: %f, %f" % (self.donchian_channel_high, self.donchian_channel_low))
53. return True
54. 
    
55. def set_position(self, pos):
56. self.state["position"] = pos
57. self.state["last_price"] = self.quote["last_price"]
58. self.target_pos.set_target_volume(self.state["position"])
59. 
    
60. def try_open(self):
61. """开仓策略"""
62. while self.state["position"] == 0:
63. self.api.wait_update()
64. 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
65. self.recalc_paramter()
66. if self.api.is_changing(self.quote, "last_price"):
67. print("最新价: %f" % self.quote.last_price)
68. 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)
69. print("当前价>唐奇安通道上轨，买入1个Unit(持多仓): %d 手" % self.unit)
70. self.set_position(self.state["position"] + self.unit)
71. 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)
72. print("当前价<唐奇安通道下轨，卖出1个Unit(持空仓): %d 手" % self.unit)
73. self.set_position(self.state["position"] - self.unit)
74. 
    
75. def try_close(self):
76. """交易策略"""
77. while self.state["position"] != 0:
78. self.api.wait_update()
79. if self.api.is_changing(self.quote, "last_price"):
80. print("最新价: ", self.quote.last_price)
81. if self.state["position"] > 0: # 持多单
82. # 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)
83. if self.quote.last_price >= self.state["last_price"] + 0.5 * self.n and self.account.risk_ratio <= self.max_risk_ratio:
84. print("加仓:加1个Unit的多仓")
85. self.set_position(self.state["position"] + self.unit)
86. # 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
87. elif self.quote.last_price <= self.state["last_price"] - 2 * self.n:
88. print("止损:卖出全部头寸")
89. self.set_position(0)
90. # 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
91. if self.quote.last_price <= min(self.klines.low[-self.donchian_channel_stop_profit - 1:-1]):
92. print("止盈:清空所有头寸结束策略,离场")
93. self.set_position(0)
94. 
    
95. elif self.state["position"] < 0: # 持空单
96. # 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)
97. if self.quote.last_price <= self.state["last_price"] - 0.5 * self.n and self.account.risk_ratio <= self.max_risk_ratio:
98. print("加仓:加1个Unit的空仓")
99. self.set_position(self.state["position"] - self.unit)
100. # 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
101. elif self.quote.last_price >= self.state["last_price"] + 2 * self.n:
102. print("止损:卖出全部头寸")
103. self.set_position(0)
104. # 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
105. if self.quote.last_price >= max(self.klines.high[-self.donchian_channel_stop_profit - 1:-1]):
106. print("止盈:清空所有头寸结束策略,离场")
107. self.set_position(0)
108. 
     
109. def strategy(self):
110. """海龟策略"""
111. print("等待K线及账户数据...")
112. deadline = time.time() + 5
113. while not self.recalc_paramter():
114. if not self.api.wait_update(deadline=deadline):
115. 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")
116. while True:
117. self.try_open()
118. self.try_close()
119. 
     
120. 
     
121. turtle = Turtle("SHFE.au1912")
122. print("策略开始运行")
123. try:
124. 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
125. except FileNotFoundError:
126. pass
127. print("当前持仓数: %d, 上次调仓价: %f" % (turtle.state["position"], turtle.state["last_price"]))
128. try:
129. turtle.strategy()
130. finally:
131. turtle.api.close()
132. json.dump(turtle.state, open("turtle_state.json", "w")) # 保存数据