股票均线突破选股法全解析：从理论到代码实现

import tushare as ts
import pandas as pd

# 获取沪深300成分股数据（2020-2023）
df = ts.pro_bar(ts_code='000300.SH', adj='qfq', 
                start_date='20200101', end_date='20231231')

# 计算均线系统
df['ma5'] = df['close'].rolling(5).mean()
df['ma20'] = df['close'].rolling(20).mean()
df['ma60'] = df['close'].rolling(60).mean()

# 金叉突破信号
df['golden_cross'] = (df['ma5'] > df['ma20']) & (df['ma5'].shift(1) <= df['ma20'].shift(1))

# 均线粘合突破（5/20/60日标准差<2%）
df['volatility'] = df[['ma5','ma20','ma60']].std(axis=1)/df['close']
df['convergence_break'] = (df['volatility'] < 0.02) & (df['close'] > df['ma60'])

# 平台突破（连续3日站稳20日均线）
df['platform_break'] = (df['close'] > df['ma20']) & \
                       (df['close'].shift(1) > df['ma20'].shift(1)) & \
                       (df['close'].shift(2) > df['ma20'].shift(2))

# 成交量验证（突破日量能大于5日均量）
df['volume_filter'] = df['vol'] > df['vol'].rolling(5).mean()

# MACD辅助验证
df['dif'] = df['close'].ewm(span=12).mean() - df['close'].ewm(span=26).mean()
df['signal_filter'] = df['dif'] > df['dif'].rolling(9).mean()

# 综合信号生成
df['final_signal'] = (df['golden_cross'] | df['convergence_break']) & \
                     df['volume_filter'] & df['signal_filter']

# 根据波动率动态调整均线周期
def dynamic_window(volatility):
    if volatility < 0.1: return 10  # 低波动缩短周期
    elif 0.1 <= volatility < 0.2: return 20
    else: return 30

df['dynamic_ma'] = df['close'].rolling(
    df['volatility'].apply(dynamic_window)).mean()

# 动态仓位计算（基于ATR波动率）
def position_size(close, atr, risk=0.02, capital=100000):
    return min(int((capital * risk) / (atr * 2)), 3000)  # 单票最大仓位30%

df['atr'] = df['high'].rolling(14).max() - df['low'].rolling(14).min()
df['position'] = df.apply(lambda x: position_size(x['close'], x['atr']), axis=1)