Python编程学动量自动化：通达信短线异动起飞指标

    
import pandas as pd
import matplotlib.pyplot as plt

def plot_signals(df):
    plt.figure(figsize=(12, 6))
    plt.plot(df.index, df['CLOSE'], label='Close Price')
    
    # 标记信号位置
    signals = df[df['LIJIN']]
    plt.scatter(signals.index, 
                signals['CLOSE'], 
                color='red', 
                label='LIJIN Signal')
    
    plt.title('Trading Signals')
    plt.legend()
    plt.show()

# 在示例使用部分添加
plot_signals(df)
def calculate_lijin_signals(df):
    # 计算基础指标
    df['LIJINE'] = (df['VOL'] * (df['CLOSE'] - df['OPEN'])) / (df['CLOSE'] + df['OPEN'] + 1e-8)
    
    # 计算EMA指标
    df['LIJINE1'] = df['LIJINE'].ewm(span=38, adjust=False).mean()
    df['LIJINW'] = df['LIJINE1'].ewm(span=8, adjust=False).mean()
    
    # 计算移动平均
    df['LIJINW1'] = df['LIJINW'].rolling(3).mean()
    df['LIJINW2'] = df['LIJINW'].rolling(10).mean()

    # 计算均线组合
    df['MA41'] = df['CLOSE'].rolling(41).mean()
    df['LIJIN111'] = df['MA41'] * 1.10
    df['MA23'] = df['CLOSE'].rolling(23).mean()
    df['LIJIN211'] = df['MA23'] * 1.05
    
    # 计算复合均线
    ma3 = df['CLOSE'].rolling(3).mean()
    ma6 = df['CLOSE'].rolling(6).mean()
    ma12 = df['CLOSE'].rolling(12).mean()
    ma24 = df['CLOSE'].rolling(24).mean()
    df['LIJIN311'] = (ma3 + ma6 + ma12 + ma24) / 4
    
    # 计算高价均线
    df['LIJIN411'] = df['HIGH'].rolling(5).mean()

    # 条件判断
    df['LIJIN511'] = df['CLOSE'] > df[


    
'CLOSE'].shift(1) * 1.088
    df['LIJIN911'] = (df['VOL'] > 0).astype(int)  # 假设DYNAINFO(17)表示有效成交量
    df['LIJIN101'] = df['LIJIN911']

    # 定义交叉函数
    def crossover(s1, s2):
        return (s1 > s2) & (s1.shift(1) <= s2.shift(1))

    # 计算交叉信号
    cross1 = crossover(df['LIJIN411'], df['LIJIN111'])
    cross2 = crossover(df['LIJIN311'], df['LIJIN111'])
    cross3 = crossover(df['LIJIN311'], df['LIJIN211'])

    # 最终信号合成
    df['LIJIN'] = (cross1 | cross2 | cross3) & df['LIJIN511'] & df['LIJIN101']
    
    return df

学习分享