总览
我正在重新测试交易策略，并希望能够根据策略的性能逐日查看损益。
方法
我存储的股票数据带有表示“ NoTrade”，“ Win”和“ Loss”的交易信号。 NoTrade表示未进行任何交易，Win表示已进行了交易且有利可图，而亏损则表示已进行了交易但无利可图。我编写了一个循环来检查是否有信号。如果有赢或亏，那么我的帐户余额会更新以反映盈亏。
数据框
WinLoss ProfitAndLossPofChg AccountBalance
D
2010-12-08 NoTrade 0.000000 2000.0
2010-12-09 NoTrade 0.000000 2000.0
2010-12-10 NoTrade 0.000000 2000.0
2010-12-13 NoTrade 0.000000 2000.0
2010-12-14 NoTrade 0.000000 2000.0
2010-12-15 Loss -0.030842 2000.0
2010-12-16 Win 0.000539 2000.0
2010-12-17 NoTrade 0.000000 2000.0
2010-12-20 NoTrade 0.000000 2000.0
2010-12-21 NoTrade 0.000000 2000.0
2010-12-22 Win 0.014686 2000.0
2010-12-23 NoTrade 0.000000 2000.0
2010-12-27 NoTrade 0.000000 2000.0
2010-12-28 Loss -0.006190 2000.0
2010-12-29 NoTrade 0.000000 2000.0
2010-12-30 NoTrade 0.000000 2000.0
2010-12-31 NoTrade 0.000000 2000.0
2011-01-03 Loss -0.055686 2000.0
2011-01-04 Loss -0.025471 2000.0
2011-01-05 Loss -0.051420 2000.0
2011-01-06 Loss -0.000299 2000.0
2011-01-07 NoTrade 0.000000 2000.0
2011-01-10 NoTrade 0.000000 2000.0
2011-01-11 Win 0.003719 2000.0
2011-01-12 NoTrade 0.000000 2000.0
2011-01-13 Loss -0.041218 2000.0
2011-01-14 Win 0.033365 2000.0
2011-01-18 Win 0.018628 2000.0
2011-01-19 NoTrade 0.000000 2000.0
2011-01-20 Loss -0.020820 2000.0
码
def ProfitAndLoss(DataFrame):
df = DataFrame
for i in df.WinLoss:
if i == "NoTrade":
df.AccountBalance = df.AccountBalance.shift(-1)
elif i == "Win":
df.AccountBalance = df.AccountBalance.shift(-1) * df.ProfitAndLossPofChg
elif i == "Loss":
df.AccountBalance = df.AccountBalance.shift(-1) * df.ProfitAndLossPofChg
输出量
WinLoss ProfitAndLossPofChg AccountBalance
D
2010-12-08 NoTrade 0.000000 0.0
2010-12-09 NoTrade 0.000000 0.0
2010-12-10 NoTrade 0.000000 0.0
2010-12-13 NoTrade 0.000000 0.0
2010-12-14 NoTrade 0.000000 0.0
2010-12-15 Loss -0.030842 -0.0
2010-12-16 Win 0.000539 0.0
2010-12-17 NoTrade 0.000000 0.0
2010-12-20 NoTrade 0.000000 0.0
2010-12-21 NoTrade 0.000000 0.0
2010-12-22 Win 0.014686 0.0
2010-12-23 NoTrade 0.000000 0.0
2010-12-27 NoTrade 0.000000 0.0
2010-12-28 Loss -0.006190 -0.0
2010-12-29 NoTrade 0.000000 0.0
2010-12-30 NoTrade 0.000000 0.0
2010-12-31 NoTrade 0.000000 0.0
2011-01-03 Loss -0.055686 -0.0
2011-01-04 Loss -0.025471 -0.0
2011-01-05 Loss -0.051420 -0.0
2011-01-06 Loss -0.000299 -0.0
2011-01-07 NoTrade 0.000000 0.0
2011-01-10 NoTrade 0.000000 0.0
2011-01-11 Win 0.003719 0.0
2011-01-12 NoTrade 0.000000 0.0
2011-01-13 Loss -0.041218 -0.0
2011-01-14 Win 0.033365 0.0
2011-01-18 Win 0.018628 0.0
2011-01-19 NoTrade 0.000000 0.0
2011-01-20 Loss -0.020820 -0.0
问题
如您所见，我的帐户余额全为零；没有显示起始帐户余额为$ 2000.00的滚动损益。在我的职能中，我认为，如果没有交易，则仅获取前几天的余额并使其成为今天的余额，或者如果是成功或失败的交易，则将前几天的余额乘以当前损益。我认为这将显示连续的盈亏总额，但我想我觉得错了。这是我不知道的长话。
最佳答案
def ProfitAndLoss(df):
df = df.copy()
df = df.reset_index()
for index,row in df.iterrows():
if index == 0:
continue
if row['WinLoss'] == "NoTrade":
df['AccountBalance'][index] = df['AccountBalance'][index-1]
elif row['WinLoss'] in ["Win", "Loss"]:
df['AccountBalance'][index] = df['AccountBalance'][index-1] * (1 + df['ProfitAndLossPofChg'][index])
return df
print(ProfitAndLoss(df).set_index('D'))
输出：
WinLoss ProfitAndLossPofChg AccountBalance
D
2010-12-08 NoTrade 0.000000 2000.000000
2010-12-09 NoTrade 0.000000 2000.000000
2010-12-10 NoTrade 0.000000 2000.000000
2010-12-13 NoTrade 0.000000 2000.000000
2010-12-14 NoTrade 0.000000 2000.000000
2010-12-15 Loss -0.030842 1938.316000
2010-12-16 Win 0.000539 1939.360752
2010-12-17 NoTrade 0.000000 1939.360752
2010-12-20 NoTrade 0.000000 1939.360752
2010-12-21 NoTrade 0.000000 1939.360752
2010-12-22 Win 0.014686 1967.842204
2010-12-23 NoTrade 0.000000 1967.842204
2010-12-27 NoTrade 0.000000 1967.842204
2010-12-28 Loss -0.006190 1955.661261
2010-12-29 NoTrade 0.000000 1955.661261
2010-12-30 NoTrade 0.000000 1955.661261
2010-12-31 NoTrade 0.000000 1955.661261
2011-01-03 Loss -0.055686 1846.758308
2011-01-04 Loss -0.025471 1799.719527
2011-01-05 Loss -0.051420 1707.177949
2011-01-06 Loss -0.000299 1706.667503
2011-01-07 NoTrade 0.000000 1706.667503
2011-01-10 NoTrade 0.000000 1706.667503
2011-01-11 Win 0.003719 1713.014599
2011-01-12 NoTrade 0.000000 1713.014599
2011-01-13 Loss -0.041218 1642.407564
2011-01-14 Win 0.033365 1697.206492
2011-01-18 Win 0.018628 1728.822055
2011-01-19 NoTrade 0.000000 1728.822055
2011-01-20 Loss -0.020820 1692.827979