Python股票量化程序

import tushare as ts
import pandas as pd
import numpy as np

# 策略参数
stock_code = '000001'  # 股票代码
buy_threshold = 1.02   # 买入阈值
sell_threshold = 0.98  # 卖出阈值
window_size = 10       # 均线窗口大小

# 获取股票数据
df = ts.get_hist_data(stock_code)

# 数据清洗
df.dropna(inplace=True)  # 去除缺失数据

# 计算均线
df['ma'] = df['close'].rolling(window=window_size).mean()

# 交易规则
hold_flag = False   # 持仓标志
buy_price = 0       # 买入价格
profit = 0          # 收益

for i in range(window_size, len(df)):
    # 判断买入
    if not hold_flag and df.iloc[i]['close'] > df.iloc[i]['ma'] * buy_threshold:
        hold_flag = True
        buy_price = df.iloc[i]['close']
        print('买入：', df.index[i], buy_price)

    # 判断卖出
    if hold_flag and df.iloc[i]['close'] < df.iloc[i]['ma'] * sell_threshold:
        hold_flag = False
        sell_price = df.iloc[i]['close']
        profit += (sell_price - buy_price) / buy_price
        print('卖出：', df.index[i], sell_price, '收益：', profit)

# 输出总收益率
print('总收益率：', profit)