def updateNewPrices(self):
"""Updates the prices to display current live PnL. Function is called when the 'Refresh EOD Prices' button is clicked
"""
for i in self.pnlitems.index:
#trade=self.pnlitems.loc[i]
if self.pnlitems.loc[i, 'PriceT'] == 0 and self.pnlitems.loc[
i,
'EOD_Pos'] != 0: ##I'm not sure why this line is here...
self.pnlitems.loc[i, 'PriceT'] = self.fc.closing_price_query(
self.pnlitems.loc[i, 'ISIN']
) ##Uncomment this line if PriceT is only to be loaded by querying closing prices from Front
self.pnlitems.loc[i, 'dP'] = self.pnlitems.loc[
i, 'PriceT'] - self.pnlitems.loc[i, 'PriceY']
self.pnlitems.loc[i, 'SOD_PnL'] = self.pnlitems.loc[
i, 'SOD_Pos'] * self.pnlitems.loc[i, 'dP'] / 100.
newTradesBB = self.newTrades[
(self.newTrades['Book'] == self.pnlitems.loc[i, 'Book'])
& (self.newTrades['ISIN'] == self.pnlitems.loc[i, 'ISIN']
)].copy()
if newTradesBB.shape[0] != 0:
newTradesBB = newTradesBB.join(self.pnlitems['PriceT'],
on='ISIN')
newTradesBB['TradePnL'] = newTradesBB['Qty'] * (
newTradesBB['PriceT'] - newTradesBB['Price']) / 100.
newTradesBB['TradePnL'].fillna(0, inplace=True)
self.pnlitems.loc[
i, 'Trade_PnL'] = newTradesBB['TradePnL'].sum()
self.pnlitems.loc[i, 'Total_PnL'] = self.pnlitems.loc[
i, 'SOD_PnL'] + self.pnlitems.loc[i, 'Trade_PnL']
#print i,self.pnlitems.loc[i,'CRNCY']
self.pnlitems.loc[i, 'USD_Total_PnL'] = self.pnlitems.loc[
i, 'Total_PnL'] / ccy.get_value(
self.pnlitems.loc[i, 'CRNCY'].values[0],
'2015') #what's the pb in get value here
def updateNewPrices(self):
"""Updates new prices by fetching data from FRONT. Function is called when the 'Refresh OED Prices is clicked'
"""
for i in self.pnlitems.index:
#trade=self.pnlitems.loc[i]
if self.pnlitems.loc[
i, 'PriceT'] == 0 and self.pnlitems.loc[i, 'EOD_Pos'] != 0:
self.pnlitems.loc[i, 'PriceT'] = self.fc.closing_price_query(
self.pnlitems.loc[i, 'ISIN'])
self.pnlitems.loc[i, 'dP'] = self.pnlitems.loc[
i, 'PriceT'] - self.pnlitems.loc[i, 'PriceY']
self.pnlitems.loc[i, 'SOD_PnL'] = self.pnlitems.loc[
i, 'SOD_Pos'] * self.pnlitems.loc[i, 'dP'] / 100.
newTradesBB = self.newTrades[
(self.newTrades['Book'] == self.pnlitems.loc[i, 'Book'])
& (self.newTrades['ISIN'] == self.pnlitems.loc[i, 'ISIN']
)].copy()
if newTradesBB.shape[0] != 0:
newTradesBB = newTradesBB.join(self.pnlitems['PriceT'],
on='ISIN')
newTradesBB['TradePnL'] = newTradesBB['Qty'] * (
newTradesBB['PriceT'] - newTradesBB['Price']) / 100.
self.pnlitems.loc[
i, 'Trade_PnL'] = newTradesBB['TradePnL'].sum()
self.pnlitems.loc[i, 'Total_PnL'] = self.pnlitems.loc[
i, 'SOD_PnL'] + self.pnlitems.loc[i, 'Trade_PnL']
print i, self.pnlitems.loc[i, 'CRNCY']
self.pnlitems.loc[i, 'USD_Total_PnL'] = self.pnlitems.loc[
i, 'Total_PnL'] / ccy.get_value(
self.pnlitems.loc[i, 'CRNCY'].values[0],
'2015') #what's the pb in get value here
def feedLivePrices(self,message):
"""Updates current prices from bloomberg. Function is called by guiWidgets > LivePnLTabPanel.livePrices()
When a new bond price becomes available, the bond analytics for that bond is updated. Functions then sends out
a 'REFRESH_TREE' message to update the Live PnL tree.
PnLTreeView.onRefreshTree listens to the REFRESH_TREE event.
"""
newPrice=message.data
bond=newPrice.name
# Only updates the bond's PriceT if it is in self.pnlitems
if bond in list(self.pnlitems['Bond']):
i=self.pnlitems['Bond']==bond
#Update bond analytics
self.pnlitems.loc[i,'PriceT']=newPrice['MID'] #PriceT is now the new mid price
self.pnlitems.loc[i,'dP']=self.pnlitems.loc[i,'PriceT']-self.pnlitems.loc[i,'PriceY']#Get the new dP for the bond
self.pnlitems.loc[i,'SOD_PnL']=self.pnlitems.loc[i,'SOD_Pos']*self.pnlitems.loc[i,'dP']/100.#SOD_PnL = SOD_pos * dP
##Get new trades
#Create a newtradesBB DataFrame
newtradesBB = pandas.DataFrame(columns=self.newTrades.columns)
#For each bond, there may be multiplie entries in pnlitems, each with its own 'Book' and 'ISIN', which may be
#the same or different. Therefore for each line in the pnlitems, we want to grab the items in the newtrades file
#that corresponds to the same book and isin.
for m in range(len(self.pnlitems.loc[i,['Book','ISIN']])):
book = self.pnlitems.loc[i,['Book','ISIN']].values[m][0]
isin = self.pnlitems.loc[i,['Book','ISIN']].values[m][1]
#Grab lines in newtrades that has the same 'Book' and 'ISIN' as the pnlitems
line = self.newTrades[(self.newTrades['Book']==book)&(self.newTrades['ISIN']==isin)]
if len(line) !=0:#If the line exist in newtrades, we append it to newtradesBB
for n in range(len(line)):
newtradesBB.loc[len(newtradesBB)]=line.iloc[n]
#Grab priceT from pnlitems
newtradesBB.loc[len(newtradesBB)-1,'PriceT']=(self.pnlitems[self.pnlitems['ISIN']==isin]['PriceT'].values[0])
#Calculate the TradePnL for that new trade if it exists.
if len(newtradesBB)!=0:
newtradesBB['TradePnL']=newtradesBB['Qty']*(newtradesBB['PriceT']-newtradesBB['Price'])/100.
newtradesBB['TradePnL'].fillna(0,inplace=True)
#newtradesBB DataFrame now contains all newtrades fields + PriceT and TradePnL.
#Now, we need to sum up all the trades for the same bond&isin, then add it to the pnlitems corresponding to the
#same book and isin
for m in range(len(newtradesBB)):
book = newtradesBB.loc[m,'Book']
isin = newtradesBB.loc[m,'ISIN']
newtradesSum=newtradesBB.loc[(newtradesBB['Book']==book)&(newtradesBB['ISIN']==isin),'TradePnL'].sum()
self.pnlitems.loc[(self.pnlitems['Book']==book)&(self.pnlitems['ISIN']==isin),'Trade_PnL']=newtradesSum
#Now, compute the Total_PnL and USD_Total_PnL
self.pnlitems.loc[i,'Total_PnL']=self.pnlitems.loc[i,'SOD_PnL'] + self.pnlitems.loc[i,'Trade_PnL']
self.pnlitems.loc[i,'USD_Total_PnL'] = self.pnlitems.loc[i,'Total_PnL']/ccy.get_value(self.pnlitems.loc[i,'CRNCY'].values[0],'2015')
#Once all the analytics are updated, send out a 'REFRESH_TREE' event
if wxVersion=='2.8':
pub.sendMessage('REFRESH_TREE', self.pnlitems.loc[i])
else:
pub.sendMessage('REFRESH_TREE', message=MessageContainer(self.pnlitems.loc[i]))
def updateBondPrice(self, bond, price):
for book in LDNFLOWBOOKS:
for isin in [bonds.loc[bond, 'REGS'], bonds.loc[bond, '144A']]:
key = book + '-' + isin
if key in self.df.index:
ddp = price - self.df.loc[key, 'PriceT']
self.df.loc[key, 'SOD_PnL'] = self.df.loc[
key, 'SOD_Pos'] + self.df.loc[key, 'SOD_Pos'] * ddp
self.df.loc[key, 'Trade_PnL'] = self.df.loc[
key, 'Trade_PnL'] + self.df.loc[key, 'dPos'] * ddp
self.df.loc[key, 'Total_PnL'] = self.df.loc[
key, 'Trade_PnL'] + self.df.loc[key, 'SOD_PnL']
self.df.loc[key, 'USD_Total_PnL'] = self.df.loc[
key, 'Trade_PnL'] / ccy.get_value(
self.df.loc[key, 'CRNCY'], '2016')
self.df.loc[key, 'dP'] = self.df.loc[key, 'dP'] + ddp
self.df.loc[key, 'PriceT'] = price
pass
pass
pass
#placeholder - call a refresh tree
pass
def getBookPnL(self, book):
"""Function to get PnLitems and calculate PnL for the specified book.
Keyword argument:
book : 'APGSG'/'HYCRE'/'KAZAK'/'RUSSI'/'SPCOR'/'SPOT'/'SPTEE'/'TURKE'/'STLBK'
"""
if self.tradeHistory==[]:
df = self.fc.load_book(book,self.today)
else:
#todaySOD=datetime.datetime.today()
#todaySOD=datetime.datetime(todaySOD.year,todaySOD.month,todaySOD.day)
#tdf=self.tradeHistory.df[(self.tradeHistory.df['Book']==book) & (self.tradeHistory.df['DateDT']<todaySOD)]
#print tdf.shape
# df = pandas.DataFrame(tdf.groupby('ISIN')['Qty'].sum())
# df = df[df['Qty']!=0]
# df['Bond']=allisins
# df = df.dropna()
# df = df.join(bonds['MATURITY'], on='Bond')
# df['MaturityDT']=df['MATURITY'].apply(getMaturityDate)
# df = df[df['MaturityDT']>=datetime.datetime.today()]
# df['ISIN'] = df.index
# df.rename(columns={'Qty':'SOD_Pos'},inplace=True)
df=self.tradeHistory.positionsByISINBook[self.tradeHistory.positionsByISINBook['Book']==book].copy()
df.set_index('ISIN',drop=False,inplace=True)
df['PriceY'] = 0.0
df['PriceT'] = 0.0
df = df[['Bond','ISIN','SOD_Pos','PriceY','PriceT']]
df['PriceY'] = df['ISIN'].apply(lambda i:self.fc.historical_price_query(i,self.yesterday))
df['PriceT'] = df['ISIN'].apply(lambda i:self.fc.closing_price_query(i))
df = df.drop_duplicates('ISIN')#seems some spurious data in STLBK
#print df
newTradesB=self.newTrades[self.newTrades['Book']==book].copy()
newIsins=set(newTradesB['ISIN'])-set(df['ISIN'])
for i in newIsins:
#print iz`
if not i in allisins:
continue
row=[allisins[i],i,0,self.fc.historical_price_query(i,self.yesterday),self.fc.closing_price_query(i)]
rowdf=pandas.DataFrame(data=[row],columns=df.columns)
df=df.append(rowdf,ignore_index=True)
df['dP']=df['PriceT']-df['PriceY']
#Added a try here, because program crashes if newTrades.csv is empty
try:
if book in self.positionDeltas.index.get_level_values('Book'): #This line can't execute if newTrades.csv is empty
df=df.join(self.positionDeltas[book],on='ISIN')
else:
df['Qty']=0
except:
df['Qty']=0 #Manually create a new column and hack it to 0
df['Qty'].fillna(0,inplace=True)
#print df
df.rename(columns={'Qty':'dPos'},inplace=True)
if self.tradeHistory==[]:
df.rename(columns={'Position':'EOD_Pos'},inplace=True)
df['SOD_Pos']=df['EOD_Pos']-df['dPos']
else:
df['EOD_Pos']=df['SOD_Pos']+df['dPos']
df['SOD_PnL']=df['SOD_Pos']*df['dP']/100.
df['Book']=book
df['Key']=df['ISIN'].apply(lambda x:book+'-'+x)
df=df.set_index('ISIN', drop=False, verify_integrity=True)
newTradesB=newTradesB.join(df['PriceT'],on='ISIN')
newTradesB['TradePnL']=newTradesB['Qty']*(newTradesB['PriceT']-newTradesB['Price'])/100.
#self.newTradesB=newTradesB
isinPnL=newTradesB.groupby('ISIN')['TradePnL'].sum()
df['Trade_PnL']=isinPnL
df['Trade_PnL'].fillna(0,inplace=True)
df['Total_PnL']=df['SOD_PnL']+df['Trade_PnL']
df=df[df['Total_PnL']!=0]
df=df.join(bonds['CNTRY_OF_RISK'], on='Bond')
df=df.join(bonds['CRNCY'], on='Bond')
df=df.join(bonds['TICKER'], on='Bond')
df=df.join(countries.set_index('Country code'), on='CNTRY_OF_RISK')
df.rename(columns={'Long name':'Country','TICKER':'Issuer'},inplace=True)
del df['CNTRY_OF_RISK']
df['USD_Total_PnL']=df['Total_PnL']
nusd=df[df['CRNCY']!='USD'][['USD_Total_PnL','Total_PnL','CRNCY']].copy()
for c in ccy.index:
i = nusd['CRNCY']==c
nusd.loc[i,'USD_Total_PnL']=nusd['Total_PnL']/ccy.get_value(c,'2015')
df.loc[df['CRNCY']!='USD','USD_Total_PnL']=nusd['USD_Total_PnL']
##HACK - could be pandas bug - https://github.com/pydata/pandas/issues/6322##
df['Region'].fillna('US',inplace=True)
df['Country'].fillna('US',inplace=True)
df['Issuer'].fillna('US',inplace=True)
##
df.sort(['Region','Country','Bond'],inplace=True)
df=df[['Key','Book','Bond','ISIN','CRNCY','Issuer','Region','Country','SOD_Pos','EOD_Pos','dPos','PriceY','PriceT','dP','SOD_PnL','Trade_PnL','Total_PnL','USD_Total_PnL']]
return df
def updateBondPrice(self,bond,price):
for book in LDNFLOWBOOKS:
for isin in [bonds.loc[bond,'REGS'],bonds.loc[bond,'144A']]:
key=book+'-'+isin
if key in self.df.index:
ddp=price-self.df.loc[key,'PriceT']
self.df.loc[key,'SOD_PnL'] = self.df.loc[key,'SOD_Pos'] + self.df.loc[key,'SOD_Pos']*ddp
self.df.loc[key,'Trade_PnL'] = self.df.loc[key,'Trade_PnL'] + self.df.loc[key,'dPos']*ddp
self.df.loc[key,'Total_PnL'] = self.df.loc[key,'Trade_PnL'] + self.df.loc[key,'SOD_PnL']
self.df.loc[key,'USD_Total_PnL'] = self.df.loc[key,'Trade_PnL'] / ccy.get_value(self.df.loc[key,'CRNCY'],'2016')
self.df.loc[key,'dP'] = self.df.loc[key,'dP'] + ddp
self.df.loc[key,'PriceT'] = price
pass
pass
pass
#placeholder - call a refresh tree
pass
def updateNewPrices(self):
"""Updates the prices to display current live PnL. Function is called when the 'Refresh EOD Prices' button is clicked
"""
for i in self.pnlitems.index:
#trade=self.pnlitems.loc[i]
if self.pnlitems.loc[i,'PriceT']==0 and self.pnlitems.loc[i,'EOD_Pos']!=0: ##I'm not sure why this line is here...
self.pnlitems.loc[i,'PriceT']=self.fc.closing_price_query(self.pnlitems.loc[i,'ISIN']) ##Uncomment this line if PriceT is only to be loaded by querying closing prices from Front
self.pnlitems.loc[i,'dP']=self.pnlitems.loc[i,'PriceT']-self.pnlitems.loc[i,'PriceY']
self.pnlitems.loc[i,'SOD_PnL']=self.pnlitems.loc[i,'SOD_Pos']*self.pnlitems.loc[i,'dP']/100.
newTradesBB=self.newTrades[(self.newTrades['Book']==self.pnlitems.loc[i,'Book']) & (self.newTrades['ISIN']==self.pnlitems.loc[i,'ISIN'])].copy()
if newTradesBB.shape[0]!=0:
newTradesBB=newTradesBB.join(self.pnlitems['PriceT'],on='ISIN')
newTradesBB['TradePnL']=newTradesBB['Qty']*(newTradesBB['PriceT']-newTradesBB['Price'])/100.
newTradesBB['TradePnL'].fillna(0,inplace=True)
self.pnlitems.loc[i,'Trade_PnL']=newTradesBB['TradePnL'].sum()
self.pnlitems.loc[i,'Total_PnL']=self.pnlitems.loc[i,'SOD_PnL']+self.pnlitems.loc[i,'Trade_PnL']
#print i,self.pnlitems.loc[i,'CRNCY']
self.pnlitems.loc[i,'USD_Total_PnL']=self.pnlitems.loc[i,'Total_PnL']/ccy.get_value(self.pnlitems.loc[i,'CRNCY'].values[0],'2015')#what's the pb in get value here
def updateNewPrices(self):
"""Updates new prices by fetching data from FRONT. Function is called when the 'Refresh OED Prices is clicked'
"""
for i in self.pnlitems.index:
#trade=self.pnlitems.loc[i]
if self.pnlitems.loc[i,'PriceT']==0 and self.pnlitems.loc[i,'EOD_Pos']!=0:
self.pnlitems.loc[i,'PriceT']=self.fc.closing_price_query(self.pnlitems.loc[i,'ISIN'])
self.pnlitems.loc[i,'dP']=self.pnlitems.loc[i,'PriceT']-self.pnlitems.loc[i,'PriceY']
self.pnlitems.loc[i,'SOD_PnL']=self.pnlitems.loc[i,'SOD_Pos']*self.pnlitems.loc[i,'dP']/100.
newTradesBB=self.newTrades[(self.newTrades['Book']==self.pnlitems.loc[i,'Book']) & (self.newTrades['ISIN']==self.pnlitems.loc[i,'ISIN'])].copy()
if newTradesBB.shape[0]!=0:
newTradesBB=newTradesBB.join(self.pnlitems['PriceT'],on='ISIN')
newTradesBB['TradePnL']=newTradesBB['Qty']*(newTradesBB['PriceT']-newTradesBB['Price'])/100.
self.pnlitems.loc[i,'Trade_PnL']=newTradesBB['TradePnL'].sum()
self.pnlitems.loc[i,'Total_PnL']=self.pnlitems.loc[i,'SOD_PnL']+self.pnlitems.loc[i,'Trade_PnL']
print i,self.pnlitems.loc[i,'CRNCY']
self.pnlitems.loc[i,'USD_Total_PnL']=self.pnlitems.loc[i,'Total_PnL']/ccy.get_value(self.pnlitems.loc[i,'CRNCY'].values[0],'2015')#what's the pb in get value here
def getBookPnL(self, book):
"""Function to get PnLitems and calculate PnL for the specified book.
Keyword argument:
book : 'APGSG'/'HYCRE'/'KAZAK'/'RUSSI'/'SPCOR'/'SPOT'/'SPTEE'/'TURKE'/'STLBK'
"""
if self.tradeHistory == []:
df = self.fc.load_book(book, self.today)
else:
#todaySOD=datetime.datetime.today()
#todaySOD=datetime.datetime(todaySOD.year,todaySOD.month,todaySOD.day)
#tdf=self.tradeHistory.df[(self.tradeHistory.df['Book']==book) & (self.tradeHistory.df['DateDT']<todaySOD)]
#print tdf.shape
# df = pandas.DataFrame(tdf.groupby('ISIN')['Qty'].sum())
# df = df[df['Qty']!=0]
# df['Bond']=allisins
# df = df.dropna()
# df = df.join(bonds['MATURITY'], on='Bond')
# df['MaturityDT']=df['MATURITY'].apply(getMaturityDate)
# df = df[df['MaturityDT']>=datetime.datetime.today()]
# df['ISIN'] = df.index
# df.rename(columns={'Qty':'SOD_Pos'},inplace=True)
df = self.tradeHistory.positionsByISINBook[
self.tradeHistory.positionsByISINBook['Book'] == book].copy()
df.set_index('ISIN', drop=False, inplace=True)
df['PriceY'] = 0.0
df['PriceT'] = 0.0
df = df[['Bond', 'ISIN', 'SOD_Pos', 'PriceY', 'PriceT']]
df['PriceY'] = df['ISIN'].apply(
lambda i: self.fc.historical_price_query(i, self.yesterday))
df['PriceT'] = df['ISIN'].apply(
lambda i: self.fc.closing_price_query(i))
df = df.drop_duplicates('ISIN') #seems some spurious data in STLBK
#print df
newTradesB = self.newTrades[self.newTrades['Book'] == book].copy()
newIsins = set(newTradesB['ISIN']) - set(df['ISIN'])
for i in newIsins:
#print iz`
if not i in allisins:
continue
row = [
allisins[i], i, 0,
self.fc.historical_price_query(i, self.yesterday),
self.fc.closing_price_query(i)
]
rowdf = pandas.DataFrame(data=[row], columns=df.columns)
df = df.append(rowdf, ignore_index=True)
df['dP'] = df['PriceT'] - df['PriceY']
#Added a try here, because program crashes if newTrades.csv is empty
try:
if book in self.positionDeltas.index.get_level_values(
'Book'
): #This line can't execute if newTrades.csv is empty
df = df.join(self.positionDeltas[book], on='ISIN')
else:
df['Qty'] = 0
except:
df['Qty'] = 0 #Manually create a new column and hack it to 0
df['Qty'].fillna(0, inplace=True)
#print df
df.rename(columns={'Qty': 'dPos'}, inplace=True)
if self.tradeHistory == []:
df.rename(columns={'Position': 'EOD_Pos'}, inplace=True)
df['SOD_Pos'] = df['EOD_Pos'] - df['dPos']
else:
df['EOD_Pos'] = df['SOD_Pos'] + df['dPos']
df['SOD_PnL'] = df['SOD_Pos'] * df['dP'] / 100.
df['Book'] = book
df['Key'] = df['ISIN'].apply(lambda x: book + '-' + x)
df = df.set_index('ISIN', drop=False, verify_integrity=True)
newTradesB = newTradesB.join(df['PriceT'], on='ISIN')
newTradesB['TradePnL'] = newTradesB['Qty'] * (
newTradesB['PriceT'] - newTradesB['Price']) / 100.
#self.newTradesB=newTradesB
isinPnL = newTradesB.groupby('ISIN')['TradePnL'].sum()
df['Trade_PnL'] = isinPnL
df['Trade_PnL'].fillna(0, inplace=True)
df['Total_PnL'] = df['SOD_PnL'] + df['Trade_PnL']
df = df[df['Total_PnL'] != 0]
df = df.join(bonds['CNTRY_OF_RISK'], on='Bond')
df = df.join(bonds['CRNCY'], on='Bond')
df = df.join(bonds['TICKER'], on='Bond')
df = df.join(countries.set_index('Country code'), on='CNTRY_OF_RISK')
df.rename(columns={
'Long name': 'Country',
'TICKER': 'Issuer'
},
inplace=True)
del df['CNTRY_OF_RISK']
df['USD_Total_PnL'] = df['Total_PnL']
nusd = df[df['CRNCY'] != 'USD'][[
'USD_Total_PnL', 'Total_PnL', 'CRNCY'
]].copy()
for c in ccy.index:
i = nusd['CRNCY'] == c
nusd.loc[i, 'USD_Total_PnL'] = nusd['Total_PnL'] / ccy.get_value(
c, '2015')
df.loc[df['CRNCY'] != 'USD', 'USD_Total_PnL'] = nusd['USD_Total_PnL']
##HACK - could be pandas bug - https://github.com/pydata/pandas/issues/6322##
df['Region'].fillna('US', inplace=True)
df['Country'].fillna('US', inplace=True)
df['Issuer'].fillna('US', inplace=True)
##
df.sort(['Region', 'Country', 'Bond'], inplace=True)
df = df[[
'Key', 'Book', 'Bond', 'ISIN', 'CRNCY', 'Issuer', 'Region',
'Country', 'SOD_Pos', 'EOD_Pos', 'dPos', 'PriceY', 'PriceT', 'dP',
'SOD_PnL', 'Trade_PnL', 'Total_PnL', 'USD_Total_PnL'
]]
return df
def feedLivePrices(self, message):
"""Updates current prices from bloomberg. Function is called by guiWidgets > LivePnLTabPanel.livePrices()
When a new bond price becomes available, the bond analytics for that bond is updated. Functions then sends out
a 'REFRESH_TREE' message to update the Live PnL tree.
PnLTreeView.onRefreshTree listens to the REFRESH_TREE event.
"""
newPrice = message.data
bond = newPrice.name
# Only updates the bond's PriceT if it is in self.pnlitems
if bond in list(self.pnlitems['Bond']):
i = self.pnlitems['Bond'] == bond
#Update bond analytics
self.pnlitems.loc[i, 'PriceT'] = newPrice[
'MID'] #PriceT is now the new mid price
self.pnlitems.loc[
i, 'dP'] = self.pnlitems.loc[i, 'PriceT'] - self.pnlitems.loc[
i, 'PriceY'] #Get the new dP for the bond
self.pnlitems.loc[i, 'SOD_PnL'] = self.pnlitems.loc[
i, 'SOD_Pos'] * self.pnlitems.loc[
i, 'dP'] / 100. #SOD_PnL = SOD_pos * dP
##Get new trades
#Create a newtradesBB DataFrame
newtradesBB = pandas.DataFrame(columns=self.newTrades.columns)
#For each bond, there may be multiplie entries in pnlitems, each with its own 'Book' and 'ISIN', which may be
#the same or different. Therefore for each line in the pnlitems, we want to grab the items in the newtrades file
#that corresponds to the same book and isin.
for m in range(len(self.pnlitems.loc[i, ['Book', 'ISIN']])):
book = self.pnlitems.loc[i, ['Book', 'ISIN']].values[m][0]
isin = self.pnlitems.loc[i, ['Book', 'ISIN']].values[m][1]
#Grab lines in newtrades that has the same 'Book' and 'ISIN' as the pnlitems
line = self.newTrades[(self.newTrades['Book'] == book)
& (self.newTrades['ISIN'] == isin)]
if len(
line
) != 0: #If the line exist in newtrades, we append it to newtradesBB
for n in range(len(line)):
newtradesBB.loc[len(newtradesBB)] = line.iloc[n]
#Grab priceT from pnlitems
newtradesBB.loc[len(newtradesBB) - 1, 'PriceT'] = (
self.pnlitems[self.pnlitems['ISIN'] ==
isin]['PriceT'].values[0])
#Calculate the TradePnL for that new trade if it exists.
if len(newtradesBB) != 0:
newtradesBB['TradePnL'] = newtradesBB['Qty'] * (
newtradesBB['PriceT'] - newtradesBB['Price']) / 100.
newtradesBB['TradePnL'].fillna(0, inplace=True)
#newtradesBB DataFrame now contains all newtrades fields + PriceT and TradePnL.
#Now, we need to sum up all the trades for the same bond&isin, then add it to the pnlitems corresponding to the
#same book and isin
for m in range(len(newtradesBB)):
book = newtradesBB.loc[m, 'Book']
isin = newtradesBB.loc[m, 'ISIN']
newtradesSum = newtradesBB.loc[(newtradesBB['Book'] == book) &
(newtradesBB['ISIN'] == isin),
'TradePnL'].sum()
self.pnlitems.loc[(self.pnlitems['Book'] == book) &
(self.pnlitems['ISIN'] == isin),
'Trade_PnL'] = newtradesSum
#Now, compute the Total_PnL and USD_Total_PnL
self.pnlitems.loc[i, 'Total_PnL'] = self.pnlitems.loc[
i, 'SOD_PnL'] + self.pnlitems.loc[i, 'Trade_PnL']
self.pnlitems.loc[i, 'USD_Total_PnL'] = self.pnlitems.loc[
i, 'Total_PnL'] / ccy.get_value(
self.pnlitems.loc[i, 'CRNCY'].values[0], '2015')
#Once all the analytics are updated, send out a 'REFRESH_TREE' event
if wxVersion == '2.8':
pub.sendMessage('REFRESH_TREE', self.pnlitems.loc[i])
else:
pub.sendMessage('REFRESH_TREE',
message=MessageContainer(self.pnlitems.loc[i]))
