当多个条件等于True时，设置'Buy‘信号/backtest的最佳方法(股票数据)

Question

使用每日Date、Open、High、Low、Close股票数据，我试图更好地理解在回测多个条件时要使用的语句类型的好方法。例如：

#Signal:
Todays Close > Todays Open  AND
Yesterdays Close > Yesterdays Open  AND
Todays Close >= Todays High - 10%

#Position:
If ALL of the signal conditions above are true, then "Buy" tomorrow at (todays High + 5%) and "Sell" at the Close of the day. 
**To take the position I would have to test that the "Buy" condition was satisfied on the 'tomorrow' bar

#Calculate Return:
If Position taken, calculate profit or loss for the day

我见过示例算法，但许多示例只是基本的移动平均交叉系统(一个条件)，使用矢量化方法非常简单。

当你有像上面这样的多个条件时，有人能告诉我一个很好的编码方法吗？

Answer 1

假设您的数据已按日期排序并按顺序编制索引，请尝试执行以下操作：

cond1 = df['Close'] > df['Open']
cond2 = df['Close'].shift() > df['Open'].shift()
cond3 = df['Close'] >= (df['High'] * 0.9)
signal = df[cond1 & cond2 & cond3]

df.loc[signal.index + 1, 'BuyAt'] = (signal['High'] * 1.05).values
df.loc[signal.index + 1, 'SellAt'] = df.loc[signal.index + 1, 'Close']
df['PnL'] = df['SellAt'] - df['BuyAt']

结果(来自雅虎财经的MSFT股票价格)：

        Date        Open        High         Low       Close       BuyAt      SellAt       PnL
0  2019-01-02   99.550003  101.750000   98.940002  101.120003         NaN         NaN       NaN
1  2019-01-03  100.099998  100.190002   97.199997   97.400002         NaN         NaN       NaN
2  2019-01-04   99.720001  102.510002   98.930000  101.930000         NaN         NaN       NaN
3  2019-01-07  101.639999  103.269997  100.980003  102.059998         NaN         NaN       NaN
4  2019-01-08  103.040001  103.970001  101.709999  102.800003  108.433497  102.800003 -5.633494
5  2019-01-09  103.860001  104.879997  103.239998  104.269997         NaN         NaN       NaN
6  2019-01-10  103.220001  103.750000  102.379997  103.599998         NaN         NaN       NaN
7  2019-01-11  103.190002  103.440002  101.639999  102.800003  108.937500  102.800003 -6.137497
8  2019-01-14  101.900002  102.870003  101.260002  102.050003         NaN         NaN       NaN
9  2019-01-15  102.510002  105.050003  101.879997  105.010002         NaN         NaN       NaN
10 2019-01-16  105.260002  106.260002  104.959999  105.379997  110.302503  105.379997 -4.922506
11 2019-01-17  105.000000  106.629997  104.760002  106.120003  111.573002  106.120003 -5.452999
12 2019-01-18  107.459999  107.900002  105.910004  107.709999  111.961497  107.709999 -4.251498
13 2019-01-22  106.750000  107.099998  104.860001  105.680000  113.295002  105.680000 -7.615002
14 2019-01-23  106.120003  107.040001  105.339996  106.709999         NaN         NaN       NaN
15 2019-01-24  106.860001  107.000000  105.339996  106.199997         NaN         NaN       NaN
16 2019-01-25  107.239998  107.879997  106.199997  107.169998         NaN         NaN       NaN
17 2019-01-28  106.260002  106.480003  104.660004  105.080002         NaN         NaN       NaN
18 2019-01-29  104.879997  104.970001  102.169998  102.940002         NaN         NaN       NaN
19 2019-01-30  104.620003  106.379997  104.330002  106.379997         NaN         NaN       NaN

在我看来，这是一个失败的策略！