def sell(remc, share, date):
'''
:returns: tuple, (sold rem, new rem)
sold rem is the positions being sold while new rem is the positions being held
'''
rem = copy(remc)
share = myround(share)
date = convert_date(date)
totposition = sum([pos[1] for pos in rem]) # the remaining shares
if totposition == 0:
return ([], [])
if (date - rem[-1][0]).days < 0:
raise Exception(_errmsg)
if share > totposition:
share = totposition # not raise error when you sell more than you buy
soldrem = []
newrem = []
for i, pos in enumerate(rem):
if share > myround(sum([rem[j][1] for j in range(i + 1)])):
soldrem.append(rem[i])
elif share == myround(sum([rem[j][1] for j in range(i + 1)])):
soldrem.append(rem[i])
elif share < myround(sum([rem[j][1] for j in range(i + 1)])):
if share > sum([rem[j][1] for j in range(i)]):
soldrem.append([rem[i][0], share - sum([rem[j][1] for j in range(i)])])
newrem.append([rem[i][0], sum([rem[j][1] for j in range(i + 1)]) - share])
elif share <= sum([rem[j][1] for j in range(i)]):
newrem.append(rem[i])
return (soldrem, newrem)
def status_gen(self, date):
# 过滤交易日这一需求，交给各个类自由裁量，这里网格类就需要过掉非交易日干扰，
# 而定投类中则不过掉，遇到非交易日顺延定投更合理些
if date.strftime("%Y-%m-%d") not in opendate:
return 0
if date == self.start:
if self.buypercent[0] == 0:
self.pos += 1
return myround(self.totmoney / self.division)
else:
return 0
value = self.price[self.price["date"] <= date].iloc[-1].loc["netvalue"]
valueb = self.price[
self.price["date"] <= date].iloc[-2].loc["netvalue"]
action = 0
for i, buypt in enumerate(self.buypts):
if (value - buypt) <= 0 and (valueb - buypt) > 0 and self.pos <= i:
self.pos += 1
action += myround(self.totmoney / self.division)
for j, sellpt in enumerate(self.sellpts):
if (value - sellpt) >= 0 and (valueb -
sellpt) < 0 and self.pos > j:
action += -1 / self.pos
self.pos += -1
return action
def dailyreport(self, date=yesterdayobj()):
date = convert_date(date)
partcftb = self.cftable[self.cftable["date"] <= date]
value = self.get_netvalue(date)
if len(partcftb) == 0:
reportdict = {
"基金名称": [self.name],
"基金代码": [self.code],
"当日净值": [value],
"持有份额": [0],
"基金现值": [0],
"基金总申购": [0],
"历史最大占用": [0],
"基金分红与赎回": [0],
"基金收益总额": [0],
}
df = pd.DataFrame(reportdict, columns=reportdict.keys())
return df
# totinput = myround(-sum(partcftb.loc[:,'cash']))
totinput = myround(-sum(
[row["cash"]
for _, row in partcftb.iterrows() if row["cash"] < 0]))
totoutput = myround(
sum([
row["cash"] for _, row in partcftb.iterrows()
if row["cash"] > 0
]))
currentshare = myround(sum(partcftb.loc[:, "share"]))
currentcash = myround(currentshare * value)
btnk = bottleneck(partcftb)
turnover = turnoverrate(partcftb, date)
ereturn = myround(currentcash + totoutput - totinput)
if currentshare == 0:
unitcost = 0
else:
unitcost = round((totinput - totoutput) / currentshare, 4)
if btnk == 0:
returnrate = 0
else:
returnrate = round((ereturn / btnk) * 100, 4)
reportdict = {
"基金名称": [self.name],
"基金代码": [self.code],
"当日净值": [value],
"单位成本": [unitcost],
"持有份额": [currentshare],
"基金现值": [currentcash],
"基金总申购": [totinput],
"历史最大占用": [btnk],
"基金持有成本": [totinput - totoutput],
"基金分红与赎回": [totoutput],
"换手率": [turnover],
"基金收益总额": [ereturn],
"投资收益率": [returnrate],
}
df = pd.DataFrame(reportdict, columns=reportdict.keys())
return df
def status_gen(self, date):
if date.strftime("%Y-%m-%d") not in opendate:
return 0
rows = self.price[self.price["date"] <= date]
if len(rows) == 1:
return 0
value = rows.iloc[-1].loc[self.col]
valueb = rows.iloc[-2].loc[self.col]
action = 0
if self.buylow is True:
judge = 1
else:
judge = -1
for i, term in enumerate(self.buy):
if (judge * (value - term[0]) <= 0 < judge * (valueb - term[0])
and self.pos + sum([it[1] for it in self.buy[i:]]) <= 1):
self.pos += term[1]
action += myround(self.totmoney * term[1])
self.selllevel = 0
if self.sell is not None:
for i, term in enumerate(self.sell):
if (judge * (value - term[0]) >= 0 > judge * (valueb - term[0])
and self.pos > 0 and self.selllevel <= i):
deltaaction = myround(term[1] /
sum([it[1] for it in self.sell[i:]]))
action -= (1 + action) * deltaaction # 需考虑一日卖出多仓的情形
self.pos = (1 - deltaaction) * self.pos
self.selllevel = i + 1
return action
def shuhui(self, share, date, rem):
"""
give the cashout considering redemption rates as zero.
if the date is not a trade date, then the purchase would happen on the next trade day, if the date is
in the furture, then the trade date is taken as yesterday.
:param share: float or int, number of shares to be sold
:param date: string or object of date
:returns: three elements tuple, the first is dateobj
the second is a positive float for cashout,
the third is a negative float for share decrease
"""
date = convert_date(date)
tots = sum([remitem[1] for remitem in rem if remitem[0] <= date])
if share > tots:
sh = tots
else:
sh = share
partprice = self.price[self.price["date"] >= date]
if len(partprice) == 0:
row = self.price[self.price["date"] < date].iloc[-1]
else:
row = partprice.iloc[0]
value = myround(sh * row.netvalue)
return (row.date, value, -myround(sh))
def _shengoucal(sg, sgf, value, label):
"""
Infer the share of buying fund by money input, the rate of fee in the unit of %,
and netvalue of fund
:param sg: positive float, 申购金额
:param sgf: positive float, 申购费，以％为单位，如 0.15 表示 0.15%
:param value: positive float, 对应产品的单位净值
:param label: integer, 1 代表份额正常进行四舍五入， 2 代表份额直接舍去小数点两位之后。金额部分都是四舍五入
:returns: tuple of two positive float, 净申购金额和申购份额
"""
jsg = myround(sg / (1 + sgf * 1e-2))
share = myround(jsg / value, label)
return (jsg, share)
def _shuhui_by_share(self, share, date, rem):
date = convert_date(date)
tots = sum([remitem[1] for remitem in rem if remitem[0] <= date])
if share > tots:
sh = tots
else:
sh = share
partprice = self.price[self.price["date"] >= date]
if len(partprice) == 0:
row = self.price[self.price["date"] < date].iloc[-1]
else:
row = partprice.iloc[0]
value = myround(sh * row.netvalue)
return (
row.date,
value,
-myround(sh),
) # TODO: 这里 myround 是否也和 round_label 有关，有待考证
def bottleneck(cftable):
"""
find the max total input in the history given cftable with cash column
:param cftable: pd.DataFrame of cftable
"""
if len(cftable) == 0:
return 0
# cftable = cftable.reset_index(drop=True) # unnecessary as iloc use natural rows instead of default index
inputl = [-sum(cftable.iloc[:i].cash) for i in range(1, len(cftable) + 1)]
return myround(max(inputl))
def shuhui(self, share, date, rem):
"""
give the cashout based on rem term considering redemption rates
:returns: three elements tuple, the first is dateobj
the second is a positive float for cashout,
the third is a negative float for share decrease
"""
# value = myround(share*self.price[self.price['date']==date].iloc[0].netvalue)
date = convert_date(date)
partprice = self.price[self.price["date"] >= date]
if len(partprice) == 0:
row = self.price[self.price["date"] < date].iloc[-1]
else:
row = partprice.iloc[0]
soldrem, _ = rm.sell(rem, share, row.date)
value = 0
sh = myround(sum([item[1] for item in soldrem]))
for d, s in soldrem:
value += myround(s * row.netvalue * (1 - self.feedecision(
(row.date - d).days) * 1e-2))
return (row.date, value, -sh)
def briefdailyreport(self, date=yesterdayobj()):
"""
quick summary of highly used attrs for trade
:param date: string or object of datetime
:returns: dict with several attrs: date, unitvalue, currentshare, currentvalue
"""
date = convert_date(date)
partcftb = self.cftable[self.cftable["date"] <= date]
if len(partcftb) == 0:
return {}
unitvalue = self.get_netvalue(date)
currentshare = myround(sum(partcftb.loc[:, "share"]))
currentvalue = myround(currentshare * unitvalue)
return {
"date": date,
"unitvalue": unitvalue,
"currentshare": currentshare,
"currentvalue": currentvalue,
}
def briefdailyreport(self, date=yesterdayobj()):
'''
quick summary of highly used attrs for trade
:param date: string or object of datetime
:returns: dict with several attrs: date, unitvalue, currentshare, currentvalue
'''
date = convert_date(date)
partcftb = self.cftable[self.cftable['date'] <= date]
if len(partcftb) == 0:
return {}
unitvalue = self.aim.price[
self.aim.price['date'] <= date].iloc[-1].netvalue
currentshare = myround(sum(partcftb.loc[:, 'share']))
currentvalue = myround(currentshare * unitvalue)
return {
'date': date,
'unitvalue': unitvalue,
'currentshare': currentshare,
'currentvalue': currentvalue
}
def _vcash(totmoney, totcftable, cashobj):
'''
return a virtue status table with a mf(cash) column based on the given tot money and cftable
'''
cashl = []
cashl.append(totmoney + totcftable.iloc[0].cash)
for i in range(len(totcftable) - 1):
date = totcftable.iloc[i + 1].date
delta = totcftable.iloc[i + 1].cash
if delta < 0:
cashl.append(myround(delta / cashobj.price[cashobj.price['date'] <= date].iloc[-1].netvalue))
else:
cashl.append(delta)
datadict = {'date': totcftable.loc[:, 'date'], 'mf': cashl}
return pd.DataFrame(data=datadict)
def shengou(self, value, date):
"""
give the realdate deltacash deltashare tuple based on purchase date and purchase amount
if the date is not a trade date, then the purchase would happen on the next trade day, if the date is
in the furture, then the trade date is taken as yesterday.
:param value: the money for purchase
:param date: string or object of date
:returns: three elements tuple, the first is the actual dateobj of commit
the second is a negative float for cashin,
the third is a positive float for share increase
"""
row = self.price[self.price["date"] >= date].iloc[0]
share = _shengoucal(value, self.rate, row.netvalue, label=self.label)[1]
return (row.date, -myround(value), share)
def trans(remc, coef, date):
'''
在基金份额折算时，将之前持有的仓位按现值折算，相当于前复权
:param coef: the factor shown in comment column of fundinfo().price, but with positive value
:param date: string in date form or datetime obj
:returns: new rem after converting
'''
rem = copy(remc)
date = convert_date(date)
if len(rem) == 0:
return []
if (date - rem[-1][0]).days <= 0:
raise Exception(_errmsg)
newrem = [[item[0], myround(item[1] * coef)] for item in rem]
return newrem
def unitcost(self, date=yesterdayobj()):
"""
give the unitcost of fund positions
:param date: string or object of datetime
:returns: float number of unitcost
"""
partcftb = self.cftable[self.cftable["date"] <= date]
if len(partcftb) == 0:
return 0
totnetinput = myround(-sum(partcftb.loc[:, "cash"]))
currentshare = self.briefdailyreport(date).get("currentshare", 0)
# totnetinput
if currentshare > 0:
unitcost = totnetinput / currentshare
else:
unitcost = 0
return unitcost
def buy(remc, share, date):
'''
:param remc: array of two-elements arrays, eg [[pd.Timestamp(), 50],[pd.Timestamp(), 30]
the first element in tuple is pandas.Timestamp object for date while the second
element is positive float for remaining shares, tuples in rem MUST be time ordered.
:param share: positive float, only 2 decimal is meaningful.
:param date: string in the date form or datetime object
:returns: new rem after the buying
'''
rem = copy(remc)
share = myround(share)
date = convert_date(date)
if len(rem) == 0:
return [[date, share]]
elif (date - rem[-1][0]).days > 0:
rem.append([date, share])
return rem
elif (date - rem[-1][0]).days == 0:
rem[-1][1] = rem[-1][1] + share
return rem
else:
raise Exception(_errmsg)
def dailyreport(self, date=yesterdayobj()):
"""
breif report dict of certain date status on the fund investment
:param date: string or obj of date, show info of the date given
:returns: dict of various data on the trade positions
"""
date = convert_date(date)
partcftb = self.cftable[self.cftable["date"] <= date]
print(partcftb)
value = self.aim.price[
self.aim.price["date"] <= date].iloc[-1].netvalue
if len(partcftb) == 0:
reportdict = {
"基金名称": [self.aim.name],
"基金代码": [self.aim.code],
"当日净值": [value],
"持有份额": [0],
"基金现值": [0],
"基金总申购": [0],
"历史最大占用": [0],
"基金分红与赎回": [0],
"基金收益总额": [0],
}
df = pd.DataFrame(reportdict, columns=reportdict.keys())
return df
# totinput = myround(-sum(partcftb.loc[:,'cash']))
totinput = myround(-sum(
[row["cash"]
for _, row in partcftb.iterrows() if row["cash"] < 0]))
totoutput = myround(
sum([
row["cash"] for _, row in partcftb.iterrows()
if row["cash"] > 0
]))
currentshare = myround(sum(partcftb.loc[:, "share"]))
currentcash = myround(currentshare * value)
btnk = bottleneck(partcftb)
turnover = turnoverrate(partcftb, date)
ereturn = myround(currentcash + totoutput - totinput)
if currentshare == 0:
unitcost = 0
else:
unitcost = round((totinput - totoutput) / currentshare, 4)
if btnk == 0:
returnrate = 0
else:
returnrate = round((ereturn / btnk) * 100, 4)
reportdict = {
"基金名称": [self.aim.name],
"基金代码": [self.aim.code],
"当日净值": [value],
"单位成本": [unitcost],
"持有份额": [currentshare],
"基金现值": [currentcash],
"基金总申购": [totinput],
"历史最大占用": [btnk],
"基金持有成本": [totinput - totoutput],
"基金分红与赎回": [totoutput],
"换手率": [turnover],
"基金收益总额": [ereturn],
"投资收益率": [returnrate],
}
df = pd.DataFrame(reportdict, columns=reportdict.keys())
return df
def dailyreport(self, date=yesterdayobj()):
'''
breif report dict of certain date status on the fund investment
:param date: string or obj of date, show info of the date given
:returns: dict of various data on the trade positions
'''
date = convert_date(date)
partcftb = self.cftable[self.cftable['date'] <= date]
value = self.aim.price[
self.aim.price['date'] <= date].iloc[-1].netvalue
if len(partcftb) == 0:
reportdict = {
'基金名称': [self.aim.name],
'基金代码': [self.aim.code],
'当日净值': [value],
'持有份额': [0],
'基金现值': [0],
'基金总申购': [0],
'历史最大占用': [0],
'基金分红与赎回': [0],
'基金收益总额': [0]
}
df = pd.DataFrame(reportdict, columns=reportdict.keys())
return df
# totinput = myround(-sum(partcftb.loc[:,'cash']))
totinput = myround(-sum(
[row['cash']
for _, row in partcftb.iterrows() if row['cash'] < 0]))
totoutput = myround(
sum([
row['cash'] for _, row in partcftb.iterrows()
if row['cash'] > 0
]))
currentshare = myround(sum(partcftb.loc[:, 'share']))
currentcash = myround(currentshare * value)
btnk = bottleneck(partcftb)
turnover = turnoverrate(partcftb, date)
ereturn = myround(currentcash + totoutput - totinput)
if currentshare == 0:
unitcost = 0
else:
unitcost = round((totinput - totoutput) / currentshare, 4)
if btnk == 0:
returnrate = 0
else:
returnrate = round((ereturn / btnk) * 100, 4)
reportdict = {
'基金名称': [self.aim.name],
'基金代码': [self.aim.code],
'当日净值': [value],
'单位成本': [unitcost],
'持有份额': [currentshare],
'基金现值': [currentcash],
'基金总申购': [totinput],
'历史最大占用': [btnk],
'基金持有成本': [totinput - totoutput],
'基金分红与赎回': [totoutput],
'换手率': [turnover],
'基金收益总额': [ereturn],
'投资收益率': [returnrate]
}
df = pd.DataFrame(reportdict, columns=reportdict.keys())
return df
def _addrow(self):
"""
Return cashflow table with one more line or raise an exception if there is no more line to add
The same logic also applies to rem table
关于对于一个基金多个操作存在于同一交易日的说明：无法处理历史买入第一笔同时是分红日的情形, 事实上也不存在这种情形。无法处理一日多笔买卖的情形。
同一日既有卖也有买不现实，多笔买入只能在 csv 上合并记录，由此可能引起份额计算 0.01 的误差。可以处理分红日买入卖出的情形。
分级份额折算日封闭无法买入，所以程序直接忽略当天的买卖。因此不会出现多个操作共存的情形。
"""
# the design on data remtable is disaster, it is very dangerous though works now
code = self.aim.code
if len(self.cftable) == 0:
if len(self.status[self.status[code] != 0]) == 0:
raise Exception("no other info to be add into cashflow table")
i = 0
while self.status.iloc[i].loc[code] == 0:
i += 1
value = self.status.iloc[i].loc[code]
date = self.status.iloc[i].date
if value > 0:
rdate, cash, share = self.aim.shengou(value, date)
rem = rm.buy([], share, rdate)
else:
raise TradeBehaviorError("You cannot sell first when you never buy")
elif len(self.cftable) > 0:
recorddate = list(self.status.date)
lastdate = self.cftable.iloc[-1].date + pd.Timedelta(1, unit="d")
while (lastdate not in self.aim.specialdate) and (
(lastdate not in recorddate)
or (
(lastdate in recorddate)
and (
self.status[self.status["date"] == lastdate].loc[:, code].any()
== 0
)
)
):
lastdate += pd.Timedelta(1, unit="d")
if (lastdate - yesterdayobj()).days >= 1:
raise Exception("no other info to be add into cashflow table")
date = lastdate
label = self.aim.dividend_label # 现金分红 0, 红利再投 1
cash = 0
share = 0
rem = self.remtable.iloc[-1].rem
rdate = date
if (date in recorddate) and (date not in self.aim.zhesuandate):
# deal with buy and sell and label the fenhongzaitouru, namely one label a 0.05 in the original table to label fenhongzaitouru
value = self.status[self.status["date"] == date].iloc[0].loc[code]
fenhongmark = round(10 * value - int(10 * value), 1)
if fenhongmark == 0.5 and label == 0:
label = 1 # fenhong reinvest
value = round(value, 1)
elif fenhongmark == 0.5 and label == 1:
label = 0
value = round(value, 1)
if value > 0: # value stands for purchase money
rdate, dcash, dshare = self.aim.shengou(value, date)
rem = rm.buy(rem, dshare, rdate)
elif value < -0.005: # value stands for redemp share
rdate, dcash, dshare = self.aim.shuhui(
-value, date, self.remtable.iloc[-1].rem
)
_, rem = rm.sell(rem, -dshare, rdate)
elif value >= -0.005 and value < 0:
# value now stands for the ratio to be sold in terms of remain positions, -0.005 stand for sell 100%
remainshare = sum(self.cftable.loc[:, "share"])
ratio = -value / 0.005
rdate, dcash, dshare = self.aim.shuhui(
remainshare * ratio, date, self.remtable.iloc[-1].rem
)
_, rem = rm.sell(rem, -dshare, rdate)
else: # in case value=0, when specialday is in record day
rdate, dcash, dshare = date, 0, 0
cash += dcash
share += dshare
if date in self.aim.specialdate: # deal with fenhong and xiazhe
comment = (
self.aim.price[self.aim.price["date"] == date]
.iloc[0]
.loc["comment"]
)
if isinstance(comment, float):
if comment < 0:
dcash2, dshare2 = (
0,
sum([myround(sh * (-comment - 1)) for _, sh in rem]),
) # xiazhe are seperately carried out based on different purchase date
rem = rm.trans(rem, -comment, date)
# myround(sum(cftable.loc[:,'share'])*(-comment-1))
elif comment > 0 and label == 0:
dcash2, dshare2 = (
myround(sum(self.cftable.loc[:, "share"]) * comment),
0,
)
rem = rm.copy(rem)
elif comment > 0 and label == 1:
dcash2, dshare2 = (
0,
myround(
sum(self.cftable.loc[:, "share"])
* (
comment
/ self.aim.price[self.aim.price["date"] == date]
.iloc[0]
.netvalue
)
),
)
rem = rm.buy(rem, dshare2, date)
cash += dcash2
share += dshare2
else:
raise ParserFailure("comments not recoginized")
self.cftable = self.cftable.append(
pd.DataFrame([[rdate, cash, share]], columns=["date", "cash", "share"]),
ignore_index=True,
)
self.remtable = self.remtable.append(
pd.DataFrame([[rdate, rem]], columns=["date", "rem"]), ignore_index=True
)
def _addrow(self):
"""
Return cashflow table with one more line or raise an exception if there is no more line to add
The same logic also applies to rem table
关于对于一个基金多个操作存在于同一交易日的说明：无法处理历史买入第一笔同时是分红日的情形, 事实上也不存在这种情形。无法处理一日多笔买卖的情形。
同一日既有卖也有买不现实，多笔买入只能在 csv 上合并记录，由此可能引起份额计算 0.01 的误差。可以处理分红日买入卖出的情形。
分级份额折算日封闭无法买入，所以程序直接忽略当天的买卖。因此不会出现多个操作共存的情形。
"""
# the design on data remtable is disaster, it is very dangerous though works now
# possibly failing cases include:
# 买卖日记录是节假日，而顺延的日期恰好是折算日（理论上无法申赎）或分红日（可能由于 date 和 rdate 的错位而没有考虑到），
# 又比如周日申购记录，周一申购记录，那么周日记录会现金流记在周一，继续现金流标更新将从周二开始，周一数据被丢弃
code = self.aim.code
if len(self.cftable) == 0:
if len(self.status[self.status[code] != 0]) == 0:
raise Exception("no other info to be add into cashflow table")
i = 0
while self.status.iloc[i].loc[code] == 0:
i += 1
value = self.status.iloc[i].loc[code]
date = self.status.iloc[i].date
self.lastdate = date
if len(self.price[self.price["date"] >= date]) > 0:
date = self.price[self.price["date"] >= date].iloc[0]["date"]
else:
date = self.price[self.price["date"] <= date].iloc[-1]["date"]
# 这里没有像下边部分一样仔细处理单独的 lastdate，hopefully 不会出现其他奇怪的问题，有 case 再说
# https://github.com/refraction-ray/xalpha/issues/47
# 凭直觉这个地方的处理很可能还有其他 issue
if value > 0:
feelabel = 100 * value - int(100 * value)
if round(feelabel, 1) == 0.5:
# binary encoding, 10000.005 is actually 10000.0050...1, see issue #59
feelabel = feelabel - 0.5
if abs(feelabel) < 1e-4:
feelabel = 0
else:
feelabel *= 100
else:
feelabel = None
value = int(value * 100) / 100
assert feelabel is None or feelabel >= 0.0, "自定义申购费必须为正值"
rdate, cash, share = self.aim.shengou(value,
date,
fee=feelabel)
rem = rm.buy([], share, rdate)
else:
raise TradeBehaviorError(
"You cannot sell first when you never buy")
elif len(self.cftable) > 0:
# recorddate = list(self.status.date)
if not getattr(self, "lastdate", None):
lastdate = self.cftable.iloc[-1].date + pd.Timedelta(1,
unit="d")
else:
lastdate = self.lastdate + pd.Timedelta(1, unit="d")
while (lastdate not in self.aim.specialdate) and (
(lastdate not in self.recorddate_set) or
((lastdate in self.recorddate_set) and
(self.status[self.status["date"] ==
lastdate].loc[:, code].any() == 0))):
lastdate += pd.Timedelta(1, unit="d")
if (lastdate - yesterdayobj()).days >= 1:
raise Exception(
"no other info to be add into cashflow table")
if (lastdate - yesterdayobj()).days >= 1:
raise Exception("no other info to be add into cashflow table")
date = lastdate
# 无净值日优先后移，无法后移则前移
# 还是建议日期记录准确，不然可能有无法完美兼容的错误出现
if len(self.price[self.price["date"] >= date]) > 0:
date = self.price[self.price["date"] >= date].iloc[0]["date"]
else:
date = self.price[self.price["date"] <= date].iloc[-1]["date"]
if date != lastdate and date in list(self.status.date):
# 日期平移到了其他记录日，很可能出现问题!
logger.warning(
"账单日期 %s 非 %s 的净值记录日期，日期智能平移后 %s 与账单其他日期重合！交易处理极可能出现问题！！ "
"靠后日期的记录被覆盖" % (lastdate, self.code, date))
self.lastdate = lastdate
if date > lastdate:
self.lastdate = date
# see https://github.com/refraction-ray/xalpha/issues/27, begin new date from last one in df is not reliable
label = self.aim.dividend_label # 现金分红 0, 红利再投 1
cash = 0
share = 0
rem = self.remtable.iloc[-1].rem
rdate = date
if (lastdate
in self.recorddate_set) and (date
not in self.aim.zhesuandate):
# deal with buy and sell and label the fenhongzaitouru, namely one label a 0.05 in the original table to label fenhongzaitouru
value = self.status[
self.status["date"] <= lastdate].iloc[-1].loc[code]
if date in self.aim.fenhongdate: # 0.05 的分红行为标记，只有分红日才有效
fenhongmark = round(10 * value - int(10 * value), 1)
if fenhongmark == 0.5 and label == 0:
label = 1 # fenhong reinvest
value = value - math.copysign(0.05, value)
elif fenhongmark == 0.5 and label == 1:
label = 0
value = value - math.copysign(0.05, value)
if value > 0: # value stands for purchase money
feelabel = 100 * value - int(100 * value)
if int(10 * feelabel) == 5:
feelabel = (feelabel - 0.5) * 100
else:
feelabel = None
value = int(value * 100) / 100
rdate, dcash, dshare = self.aim.shengou(
value, date, fee=feelabel
) # shengou fee is in the unit of percent, different than shuhui case
rem = rm.buy(rem, dshare, rdate)
elif value < -0.005: # value stands for redemp share
feelabel = int(100 * value) - 100 * value
if int(10 * feelabel) == 5:
feelabel = feelabel - 0.5
else:
feelabel = None
value = int(value * 100) / 100
rdate, dcash, dshare = self.aim.shuhui(
-value, date, self.remtable.iloc[-1].rem, fee=feelabel)
_, rem = rm.sell(rem, -dshare, rdate)
elif value >= -0.005 and value < 0:
# value now stands for the ratio to be sold in terms of remain positions, -0.005 stand for sell 100%
remainshare = sum(self.cftable[
self.cftable["date"] <= date].loc[:, "share"])
ratio = -value / 0.005
rdate, dcash, dshare = self.aim.shuhui(
remainshare * ratio, date, self.remtable.iloc[-1].rem,
0)
_, rem = rm.sell(rem, -dshare, rdate)
else: # in case value=0, when specialday is in record day
rdate, dcash, dshare = date, 0, 0
cash += dcash
share += dshare
if date in self.aim.specialdate: # deal with fenhong and xiazhe
comment = self.price[self.price["date"] ==
date].iloc[0].loc["comment"]
if isinstance(comment, float):
if comment < 0:
dcash2, dshare2 = (
0,
sum([
myround(sh * (-comment - 1)) for _, sh in rem
]),
) # xiazhe are seperately carried out based on different purchase date
rem = rm.trans(rem, -comment, date)
# myround(sum(cftable.loc[:,'share'])*(-comment-1))
elif comment > 0 and label == 0:
dcash2, dshare2 = (
myround(
sum(self.cftable.loc[:, "share"]) * comment),
0,
)
rem = rm.copy(rem)
elif comment > 0 and label == 1:
dcash2, dshare2 = (
0,
myround(
sum(self.cftable.loc[:, "share"]) *
(comment / self.price[self.price["date"] ==
date].iloc[0].netvalue)),
)
rem = rm.buy(rem, dshare2, date)
cash += dcash2
share += dshare2
else:
raise ParserFailure("comments not recognized")
self.cftable = self.cftable.append(
pd.DataFrame([[rdate, cash, share]],
columns=["date", "cash", "share"]),
ignore_index=True,
)
self.remtable = self.remtable.append(pd.DataFrame(
[[rdate, rem]], columns=["date", "rem"]),
ignore_index=True)