python实现海龟交易法则
时间: 2023-07-07 14:44:06 浏览: 111
海龟交易法则是一种经典的交易策略,它主要基于趋势跟随的原则,使用一组简单的技术指标来确定买入和卖出的时机。下面是使用Python实现海龟交易法则的基本步骤:
1. 导入必要的库
```python
import pandas as pd
import numpy as np
import talib
import matplotlib.pyplot as plt
```
2. 获取数据
```python
df = pd.read_csv('data.csv', index_col='date', parse_dates=True)
```
3. 计算指标
```python
df['high_price_20'] = df['high'].rolling(window=20).max()
df['low_price_20'] = df['low'].rolling(window=20).min()
df['atr_20'] = talib.ATR(df['high'], df['low'], df['close'], timeperiod=20)
df['buy_price'] = df['high_price_20'] + 0.5 * df['atr_20']
df['sell_price'] = df['low_price_20'] - 0.5 * df['atr_20']
```
4. 定义交易信号
```python
df['buy_signal'] = np.where(df['close'] > df['buy_price'], 1, 0)
df['sell_signal'] = np.where(df['close'] < df['sell_price'], -1, 0)
df['signal'] = df['buy_signal'] + df['sell_signal']
```
5. 计算持仓
```python
df['position'] = df['signal'].cumsum()
```
6. 计算收益
```python
df['returns'] = np.log(df['close'] / df['close'].shift(1))
df['strategy_returns'] = df['position'].shift(1) * df['returns']
```
7. 可视化结果
```python
df[['close', 'position']].plot(subplots=True, figsize=(10, 6))
plt.show()
```
这样就可以使用Python实现海龟交易法则,对股票进行交易了。需要注意的是,这只是一个基本的实现方式,实际应用中可能需要根据具体情况进行调整和优化。
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