我正在嘗試使用下面的代碼計算投資組合隨時間的回撤。我嘗試使用 .expanding() 函數(shù)，但似乎無法獲得所需的輸出。如果有人能讓我知道我哪里出錯了，我真的很感激。def drawdown_2(arr): tot_return = arr.add(1).cumprod() max_return = tot_return.add(1).cummax() return (tot_return / max_return) - 1df['Drawdown'] = df.groupby(df.portfolio)['performance'].expanding().apply(drawdown_2)輸入數(shù)據(jù)的格式如下portfolio period performanceport1 201501 0.003718port1 201502 -0.004890port1 201503 -0.004171port1 201504 -0.006922port1 201505 0.003545port1 201506 0.003545port1 201507 0.006901port1 201508 0.000101port1 201509 0.009081port1 201510 0.003062port1 201511 -0.008425port1 201512 0.002580port2 201501 0.009135port2 201502 0.009149port2 201503 -0.004252port2 201504 -0.008788port2 201505 -0.006210port2 201506 0.006020port2 201507 0.002983port2 201508 0.008498port2 201509 0.008080port2 201510 0.000138port2 201511 -0.008425port2 201512 0.002580所需的輸出是一個數(shù)組，它是投資組合先前的最大值與投資組合的當(dāng)前值之間的差。上述投入的回撤數(shù)字如下所示，采用所需格式：portfolio period performance Drawdownport1 201501 0.003718 0.00000port1 201502 -0.004890 -0.00490port1 201503 -0.004171 -0.00900port1 201504 -0.006922 -0.01590port1 201505 0.003545 -0.01240port1 201506 0.003545 -0.00890port1 201507 0.006901 -0.00210port1 201508 0.000101 -0.00200port1 201509 0.009081 0.00000port1 201510 0.003062 0.00000port1 201511 -0.008425 -0.00842port1 201512 0.002580 -0.00587port2 201501 0.009135 0.00000port2 201502 0.009149 0.00000port2 201503 -0.004252 -0.00430port2 201504 -0.008788 -0.01300port2 201505 -0.006210 -0.01910port2 201506 0.006020 -0.01320port2 201507 0.002983 -0.01030port2 201508 0.008498 -0.00190port2 201509 0.008080 0.00000port2 201510 0.000138 0.00000port2 201511 -0.008425 -0.00860port2 201512 0.002580 -0.00605提前感謝一百萬的幫助。
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UYOU
TA貢獻(xiàn)1878條經(jīng)驗 獲得超4個贊
我正在使用 yfinance 的數(shù)據(jù)：
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
計算累積回報、滾動最大峰值以及尾隨峰值的回撤：
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
累積回報和峰值：
回撤：
編輯：剛剛注意到您正在處理 2 個投資組合回報，所以這并沒有真正回答您的問題......
我認(rèn)為這會做你想要的：
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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