如何解决使用.expandingPython计算投资组合亏损
我正在尝试使用以下代码来计算投资组合随时间推移的缩编。我尝试使用.expanding（）函数，但似乎无法获得所需的输出。如果有人能让我知道我要去哪里错了，我将不胜感激。
def drawdown_2(arr):
tot_return = arr.add(1).cumprod()
max_return = tot_return.add(1).cummax()
return (tot_return / max_return) - 1
df['Drawdown'] = df.groupby(df.portfolio)['performance'].expanding().apply(drawdown_2)
输入数据的格式如下
portfolio period performance
port1 201501 0.003718
port1 201502 -0.004890
port1 201503 -0.004171
port1 201504 -0.006922
port1 201505 0.003545
port1 201506 0.003545
port1 201507 0.006901
port1 201508 0.000101
port1 201509 0.009081
port1 201510 0.003062
port1 201511 -0.008425
port1 201512 0.002580
port2 201501 0.009135
port2 201502 0.009149
port2 201503 -0.004252
port2 201504 -0.008788
port2 201505 -0.006210
port2 201506 0.006020
port2 201507 0.002983
port2 201508 0.008498
port2 201509 0.008080
port2 201510 0.000138
port2 201511 -0.008425
port2 201512 0.002580
期望输出是一个数组，它是投资组合的先前最大值和投资组合的当前值之间的差。以下是上述输入的缩图，格式如下：
portfolio period performance Drawdown
port1 201501 0.003718 0.00000
port1 201502 -0.004890 -0.00490
port1 201503 -0.004171 -0.00900
port1 201504 -0.006922 -0.01590
port1 201505 0.003545 -0.01240
port1 201506 0.003545 -0.00890
port1 201507 0.006901 -0.00210
port1 201508 0.000101 -0.00200
port1 201509 0.009081 0.00000
port1 201510 0.003062 0.00000
port1 201511 -0.008425 -0.00842
port1 201512 0.002580 -0.00587
port2 201501 0.009135 0.00000
port2 201502 0.009149 0.00000
port2 201503 -0.004252 -0.00430
port2 201504 -0.008788 -0.01300
port2 201505 -0.006210 -0.01910
port2 201506 0.006020 -0.01320
port2 201507 0.002983 -0.01030
port2 201508 0.008498 -0.00190
port2 201509 0.008080 0.00000
port2 201510 0.000138 0.00000
port2 201511 -0.008425 -0.00860
port2 201512 0.002580 -0.00605
多谢您一百万。
解决方法
我正在使用yfinance的数据：
import yfnance as yf
df = yf.download('aapl',start='2020-01-01')[['Close']]
df['Chg'] = df['Close'].pct_change()
Close
Date
2019-12-31 73.412498
2020-01-02 75.087502
2020-01-03 74.357498
2020-01-06 74.949997
2020-01-07 74.597504
... ...
2020-09-03 120.879997
2020-09-04 120.959999
2020-09-08 112.820000
2020-09-09 117.320000
2020-09-10 118.930000
计算累积收益，最大滚动峰值以及从随后的峰值回落的计算如下：
df['Cum_ret'] = (1+ df['Chg']).cumprod() # cumulative return
df['Peaks'] = df['Cum_ret'].cummax() # cumulative peaks
df['Drawdown'] = (df['Cum_ret'] - df['Peaks']) / df['Peaks'] # drawdown from trailing peak
累计收益和峰值：
缩图：
编辑：刚注意到您有2个投资组合收益要处理，所以这并没有真正回答您的问题...
我认为这将满足您的要求
df['Drawdown'] = df.groupby('portfolio')['performance'].apply(drawdown_2)
portfolio period performance Drawdown
0 port1 201501 0.003718 0.000000
1 port1 201502 -0.004890 -0.004890
2 port1 201503 -0.004171 -0.009041
3 port1 201504 -0.006922 -0.015900
4 port1 201505 0.003545 -0.012411
5 port1 201506 0.003545 -0.008910
6 port1 201507 0.006901 -0.002071
7 port1 201508 0.000101 -0.001970
8 port1 201509 0.009081 0.000000
9 port1 201510 0.003062 0.000000
10 port1 201511 -0.008425 -0.008425
11 port1 201512 0.002580 -0.005867
12 port2 201501 0.009135 0.000000
13 port2 201502 0.009149 0.000000
14 port2 201503 -0.004252 -0.004252
15 port2 201504 -0.008788 -0.013003
16 port2 201505 -0.006210 -0.019132
17 port2 201506 0.006020 -0.013227
18 port2 201507 0.002983 -0.010284
19 port2 201508 0.008498 -0.001873
20 port2 201509 0.008080 0.000000
21 port2 201510 0.000138 0.000000
22 port2 201511 -0.008425 -0.008425
23 port2 201512 0.002580 -0.005867
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