股票量化交易源代码

您好，以下是一些股票量化交易的源代码示例：

1.多因子选股策略源码

```python

import numpy as np

import pandas as pd

# 假设我们有两个因子：PE和PB

data = pd.DataFrame({

    'Stock': ['A', 'B', 'C', 'D'],

    'PE': [10, 15, 8, 12],

    'PB': [2, 1.5, 2.5, 2]

})

# 根据PE和PB因子计算得分

data['Score'] = data['PE'] + data['PB']

# 选择得分最高的股票

selected_stocks = data.sort_values(by='Score', ascending=False).head(2)

print(selected_stocks)

```

2.简单的均线策略源码

```python

import numpy as np

import pandas as pd

import matplotlib.pyplot as plt

data = pd.DataFrame({

    'Date': pd.date_range(start='2023-01-01', periods=100),

    'Close': np.random.normal(100, 10, 100)  # 生成一些模拟数据

})

data.set_index('Date', inplace=True)

# 计算20日移动均线

data['Moving Average'] = data['Close'].rolling(window=20).mean()

# 生成交易信号

data['Position'] = 0

data.loc[data['Close'] > data['Moving Average'], 'Position'] = 1  # 买入信号

data.loc[data['Close'] < data['Moving Average'], 'Position'] = -1  # 卖出信号

# 绘制价格和均线

plt.figure(figsize=(14, 7))

plt.plot(data['Close'], label='Close Price')

plt.plot(data['Moving Average'], label='Moving Average')

plt.legend()

plt.show()

```

3.统计套利策略源码

```python

import numpy as np

import pandas as pd

import matplotlib.pyplot as plt

np.random.seed(42)

data = pd.DataFrame({

    'Date': pd.date_range(start='2023-01-01', periods=250),

    'Stock_A': np.random.normal(0, 1, 250).cumsum() + 50,

    'Stock_B': np.random.normal(0, 1, 250).cumsum() + 50

})

data.set_index('Date', inplace=True)

# 计算两个股票的价差

data['Spread'] = data['Stock_A'] - data['Stock_B']

# 计算价差的移动平均和标准差

window = 20

data['Spread Mean'] = data['Spread'].rolling(window=window).mean()

data['Spread Std'] = data['Spread'].rolling(window=window).std()

# 设置买入和卖出的阈值

entry_z = 2  # 买入Z分数

exit_z = 0   # 卖出Z分数

data['Upper Threshold'] = data['Spread Mean'] + entry_z * data['Spread Std']

data['Lower Threshold'] = data['Spread Mean'] - entry_z * data['Spread Std']

# 生成交易信号

data['Position'] = 0

data.loc[data['Spread'] > data['Upper Threshold'], 'Position'] = -1  # 做空Stock A，做多Stock B

data.loc[data['Spread'] < data['Lower Threshold'], 'Position'] = 1   # 做多Stock A，做空Stock B

# 绘制股票价格和交易信号

plt.figure(figsize=(14, 7))

plt.subplot(211)

plt.plot(data['Stock_A'], label='Stock A')

plt.plot(data['Stock_B'], label='Stock B')

plt.title('Stock Prices')

plt.legend()

plt.subplot(212)

plt.plot(data['Spread'], label='Spread')

plt.plot(data['Spread Mean'], label='Mean Spread')

plt.fill_between(data.index, data['Upper Threshold'], data['Lower Threshold'], color='gray', alpha=0.3, label='Entry Zone')

plt.plot(data.index, data['Position'] * 10, label='Trading Signal', color='magenta', marker='o', linestyle='None')

plt.title('Spread and Trading Signals')

plt.legend()

plt.show()

``

这些代码示例提供了不同量化交易策略的基本框架，您可以根据自己的需求进行修改和扩展。希望对您有所帮助！