量化交易 - 简单实战

核心策略

N日突破择时策略（海龟交易法则）

超参数

观察候选集
买入候选集
超参数: N1， N2， Rate，买入价，买入数量

核心代码

wait = {'stock_name' : {'N1': 10, 'N2' : 5, 'Rate' : 0.2}}
order = {'stock_name' : {'value' : 256, 'quantity' : 10}}
# 读取数据
df_stockload = web.DataReader("600410.SS", "yahoo", datetime.datetime(2018,10,1), datetime.datetime(2019,4,1))
print(df_stockload.describe())
# 最近N1交易日最高
df_stockload['N1_High'] = df_stockload.High.rolling(window=N1).max()#计算最近N1个交易日最高价
print(df_stockload.info())
# 目前出现过的最大值填充前N1个nan
expan_max = df_stockload.Close.expanding().max()
print(expan_max)
# 同理最小值
df_stockload['N2_Low'] = df_stockload.Low.rolling(window=N2).min()#计算最近N2个交易日最低价
print(df_stockload.head())

expan_min = df_stockload.Close.expanding().min()
df_stockload['N2_Low'].fillna(value=expan_min,inplace=True)#目前出现过的最小值填充前N2个nan
print(df_stockload.head())
# 寻找时间序列
""" 收盘价超过N1最高价 买入股票持有"""
buy_index = stock_df[stock_df.Close > stock_df.N1_High.shift(1)].index
print(buy_index)
"""
DatetimeIndex(['2018-11-13', '2018-11-15', '2018-11-16', '2019-02-25',
               '2019-03-05', '2019-03-06', '2019-03-07', '2019-03-08',
               '2019-03-25'],
              dtype='datetime64[ns]', name='Date', freq=None)
"""
""" 收盘价超过N2最低价 卖出股票持有"""
sell_index = stock_df[stock_df.Close < stock_df.N2_Low.shift(1)].index
print(sell_index)
"""
DatetimeIndex(['2018-10-10', '2018-10-11', '2018-10-12', '2018-10-15',
               '2018-10-16', '2018-12-18', '2018-12-25', '2019-01-02',
               '2019-01-29', '2019-01-31'],
              dtype='datetime64[ns]', name='Date', freq=None)
"""
# 将signal序列使用shift(1)
df_stockload['signal'] = df_stockload.signal.shift(1)
print(df_stockload.signal)
# 填充空值
df_stockload['signal'].fillna(value=0, inplace=True)
print(df_stockload.signal)

部署

通过crontab和http://sc.ftqq.com/3.version来部署任务