K线形态识别_早晨(希望)之星和早晨(希望)十字星

写在前面：

1. 本文中提到的“K线形态查看工具”的具体使用操作请查看该博文；

2. K线形体所处背景，诸如处在上升趋势、下降趋势、盘整等，背景内容在K线形态策略代码中没有体现；

3. 文中知识内容来自书籍《K线技术分析》by邱立波。

目录

解说

技术特征

技术含义

K线形态策略代码

结果

解说

早晨之星又称希望之星、启明星，是三根K线的组合。其中第一根是阴线，第三根是深入第一根阴线实体的阳线，第二根是在阴线和阳线下方的小阴线或小阳线。第二根K线是十字线时，该组合形态又叫早晨十字星、希望十字星，是早晨之星的特殊形态。早晨之星、早晨十字星的阴线和阳线之间也可以是两根小K线。

技术特征

1）出现在下跌趋势中。

2）由三根K线组成，第一根是阴线，第二根是低开小阴线、小阳线或十字线，第三根是阳线。

3）第三根K线实体深入到第一根K线实体之内。

技术含义

早晨之星和早晨十字星是见底反转信号，后市看涨。

K线形态策略代码

def excute_strategy(daily_file_path):'''名称：早晨(希望)之星和早晨(希望)十字星识别：1. 由三根K线组成，第一根是阴线，第二根是低开小阴线、小阳线或十字线2. 第三根是阳线，第三根K线实体深入到第一根K线实体之内3. 中间的小阴线、小阳线或十字线，可以是连续两根自定义：1. 第一根为长阴线，第三根实体两端相对第一根实体两端都上下不超过0.5%2. 中间部分最高价在第一根实体三分之二下面，即两者重合部分不超过第一根实体下三分之一前置条件：计算时间区间 2021-01-01 到 2022-01-01:param daily_file_path: 股票日数据文件路径:return:'''import pandas as pdimport osstart_date_str = '2021-01-01'end_date_str = '2022-01-01'df = pd.read_csv(daily_file_path,encoding='utf-8')# 删除停牌的数据df = df.loc[df['openPrice'] > 0].copy()df['o_date'] = df['tradeDate']df['o_date'] = pd.to_datetime(df['o_date'])df = df.loc[(df['o_date'] >= start_date_str) & (df['o_date']<=end_date_str)].copy()# 保存未复权收盘价数据df['close'] = df['closePrice']# 计算前复权数据df['openPrice'] = df['openPrice'] * df['accumAdjFactor']df['closePrice'] = df['closePrice'] * df['accumAdjFactor']df['highestPrice'] = df['highestPrice'] * df['accumAdjFactor']df['lowestPrice'] = df['lowestPrice'] * df['accumAdjFactor']# 开始计算df['type'] = 0df.loc[df['closePrice']>=df['openPrice'],'type'] = 1df.loc[df['closePrice']0.04),'big_body_yeah'] = 1df['small_yeah'] = 0df.loc[df['body_length']/df['closePrice'].shift(1)<0.015,'small_yeah'] = 1df['sort_three_yeah'] = 0df['sort_four_yeah'] = 0df.loc[(df['big_body_yeah']==1) & (df['small_yeah'].shift(-1)==1) & (df['type'].shift(-2)==1),'sort_three_yeah'] = 1df.loc[(df['big_body_yeah']==1) & (df['small_yeah'].shift(-1)==1) &(df['small_yeah'].shift(-2)==1) & (df['type'].shift(-3)==1),'sort_four_yeah'] = 1df['three_yeah'] = 0df['four_yeah'] = 0df.loc[(df['sort_three_yeah']==1) & (abs(df['closePrice']-df['openPrice'].shift(-2))/df['body_length']<0.005) & (abs(df['openPrice']-df['closePrice'].shift(-2))/df['body_length']<0.005),'three_yeah'] = 1df.loc[(df['sort_three_yeah']==1) & (abs(df['closePrice']-df['openPrice'].shift(-3))/df['body_length']<0.005) & (abs(df['openPrice']-df['closePrice'].shift(-3))/df['body_length']<0.005),'four_yeah'] = 1df['three_m_yeah'] = 0df['four_m_yeah'] = 0df.loc[(df['three_yeah']==1) & ((df['body_length']*0.33+df['closePrice'])>df['highestPrice'].shift(-1)),'three_m_yeah'] = 1df.loc[(df['four_yeah']==1) & ((df['body_length']*0.33+df['closePrice'])>df['highestPrice'].shift(-1)) & ((df['body_length']*0.33+df['closePrice'])>df['highestPrice'].shift(-2)),'four_m_yeah'] = 1df['signal'] = 0df['signal_name'] = ''df.loc[df['three_m_yeah']==1,'signal'] = 1df.loc[df['three_m_yeah']==1,'signal_name'] = '三'df.loc[df['four_m_yeah']==1,'signal'] = 2df.loc[df['four_m_yeah']==1,'signal_name'] = '四'file_name = os.path.basename(daily_file_path)title_str = file_name.split('.')[0]line_data = {'title_str':title_str,'whole_header':['日期','收','开','高','低'],'whole_df':df,'whole_pd_header':['tradeDate','closePrice','openPrice','highestPrice','lowestPrice'],'start_date_str':start_date_str,'end_date_str':end_date_str,'signal_type':'duration','duration_len':[-1,-2],'temp':len(df.loc[(df['signal']==1) | (df['signal']==2)])}return line_data

结果