用python详细的写海龟策略

海龟策略是一种经典的交易策略，其核心思想是在市场趋势明显的情况下，通过趋势跟踪的方法进行交易，以获取盈利。下面是用Python详细写海龟策略的步骤：

1. 导入必要的库

import pandas as pd
import numpy as np
import talib as ta
import matplotlib.pyplot as plt
import tushare as ts

2. 获取股票数据

df = ts.get_k_data('600519', start='2010-01-01', end='2020-12-31')
df.index = pd.to_datetime(df['date'])
df = df[['open', 'high', 'low', 'close', 'volume']]

3. 计算海龟策略中的唐奇安通道和ATR

df['20_high'] = ta.MAX(df['high'], timeperiod=20)
df['10_low'] = ta.MIN(df['low'], timeperiod=10)
df['ATR'] = ta.ATR(df['high'], df['low'], df['close'], timeperiod=20)

4. 计算海龟策略中的进出场信号

df['long_signal'] = df['close'] > df['20_high']
df['short_signal'] = df['close'] < df['10_low']

5. 计算海龟策略中的头寸规模和止损价位

df['position'] = 0
df['position'] = np.where(df['long_signal'], 1, df['position'])
df['position'] = np.where(df['short_signal'], -1, df['position'])
df['position'] = df['position'].shift(1)

df['ATR'] = df['ATR'].fillna(method='ffill')

df['stop_loss'] = 0
df['stop_loss'] = np.where(df['position'] == 1, df['close'] - 2 * df['ATR'], df['stop_loss'])
df['stop_loss'] = np.where(df['position'] == -1, df['close'] + 2 * df['ATR'], df['stop_loss'])

6. 计算海龟策略中的持仓盈亏和总盈亏

df['pnl'] = df['position'] * (df['close'] - df['close'].shift(1))
df['cum_pnl'] = df['pnl'].cumsum()

7. 绘制总盈亏曲线

df['cum_pnl'].plot()
plt.show()

这就是用Python详细写海龟策略的步骤。通过这种方法，我们可以轻松地实现海龟策略，并对其进行优化和改进。