帮我写一段股票多因子回测框架的代码
时间: 2023-12-06 21:03:59 浏览: 28
以下是一个基本的股票多因子回测框架的代码:
```
import pandas as pd
import numpy as np
import datetime as dt
# 设置回测起始和结束日期
start_date = dt.date(2015, 1, 1)
end_date = dt.date(2020, 12, 31)
# 读取股票数据
stock_data = pd.read_csv('stock_data.csv', index_col=0, parse_dates=True)
stock_data = stock_data.loc[start_date:end_date]
# 读取因子数据
factor_data = pd.read_csv('factor_data.csv', index_col=0, parse_dates=True)
factor_data = factor_data.loc[start_date:end_date]
# 定义因子权重,这里假设有三个因子
factor_weights = np.array([0.3, 0.4, 0.3])
# 计算每个股票每个交易日的因子得分
factor_scores = factor_data.dot(factor_weights)
# 定义投资组合大小
portfolio_size = 1000000
# 计算每个股票每个交易日的仓位
weights = factor_scores / factor_scores.abs().sum(axis=1).fillna(0)
weights = weights.fillna(0)
weights[weights.abs() < 0.01] = 0
# 计算每个股票每个交易日的收益
returns = stock_data.pct_change()
# 计算投资组合每个交易日的收益
portfolio_returns = (weights.shift(1) * returns).sum(axis=1)
# 计算投资组合每个交易日的累计收益
cumulative_returns = (1 + portfolio_returns).cumprod()
# 输出回测结果
print('回测期间从{}到{},投资组合的累计收益为{}。'.format(start_date, end_date, cumulative_returns[-1]))
```