Esempio n. 1
0
 def insert_dividends(self):
     print( "Insert new dividends" )
     mdb_query = Query()
     iex = Iex()
     #Get all symbols in MongoDB
     #mdb_symbols = mdb_query.get_active_companies()
     #Get current date
     currDate = datetime.datetime.now().strftime("%Y-%m-%d")
 
     #Get existing portfolios
     portfolios = mdb_query.get_portfolios(currDate)[["portfolioID","inceptionDate"]]
     #Loop through portfolios
     mdb_symbols = pandas.DataFrame()
     for portfolio_index, portfolio_row in portfolios.iterrows():
         #Get portfolioID and inceptionDate
         portfolio = portfolio_row['portfolioID']
         inceptionDate = portfolio_row['inceptionDate']
         #Default to calculating holdings from inception
         date = inceptionDate
         #Get current holdings table
         holdings = mdb_query.get_holdings(portfolio, inceptionDate, "after")
         #print( holdings )
         mdb_symbols = mdb_symbols.append(holdings, ignore_index=True, sort=False)
         #print( mdb_symbols )
     mdb_symbols = mdb_symbols[mdb_symbols['symbol'] != 'USD']
     mdb_symbols = mdb_symbols['symbol'].unique().tolist()
     #print( mdb_symbols )
     #quit()
 
     #Get latest dividend in MongoDB for each symbol
     mdb_dividends = mdb_query.get_dividends( mdb_symbols, currDate, "latest" )
     #Initial call to print 0% progress
     printProgressBar(0, len(mdb_symbols), prefix = 'Progress:', suffix = '', length = 50)
     #flag = False
     #Loop through symbols
     for index, mdb_symbol in enumerate(mdb_symbols):
         #if mdb_symbol["symbol"] == "ZZZZZZZZZ":
         #    flag = True
         #if not flag:
         #    continue
         #Get 1m of dividends from IEX
         iex_dividends = iex.get_dividends( mdb_symbol, ref_range='1m' )
         #Get matching dividend in MongoDB
         mdb_dividend = mdb_dividends[ mdb_dividends['symbol'] == mdb_symbol ]
         #Select dividends more recent than MongoDB
         if not mdb_dividend.empty and not iex_dividends.empty:
             mask = iex_dividends['exDate'] > mdb_dividend['exDate'].iloc[0]
             iex_dividends = iex_dividends.loc[mask]
         #Insert if dividends exist
         if not iex_dividends.empty:
             #Update progress bar
             printProgressBar(index+1, len(mdb_symbols), prefix = 'Progress:', suffix = "Inserting dividend for " + mdb_symbol + "      ", length = 50)
             #print( iex_dividends )
             self.db.iex_dividends.insert_many( iex_dividends.to_dict('records') )
         else:
             #Update progress bar
             printProgressBar(index+1, len(mdb_symbols), prefix = 'Progress:', suffix = "No new data for " + mdb_symbol + "      ", length = 50)
Esempio n. 2
0
 def insert_holdings(self):
     print( "Calculate portfolio holdings" )
     mdb_query = Query()
     #Get current date
     currDate = datetime.datetime.now().strftime("%Y-%m-%d")
     #currDate = "2019-12-30"
     #Get existing portfolios
     portfolios = mdb_query.get_portfolios(currDate)[["portfolioID","inceptionDate"]]
     #Loop through portfolios
     for portfolio_index, portfolio_row in portfolios.iterrows():
         #Get portfolioID and inceptionDate
         portfolio = portfolio_row['portfolioID']
         inceptionDate = portfolio_row['inceptionDate']
         print( 'Calculating holdings for ', portfolio )
         #Default to calculating holdings from inception
         date = inceptionDate
         #Get current holdings table
         holdings = mdb_query.get_holdings(portfolio, currDate, "on")
         #print( holdings )
         #If holdings exist then calculate holdings from next date
         if not holdings.empty:
             date = holdings['lastUpdated'].max()
             date = (pandas.Timestamp(date) + pandas.DateOffset(days=1)).strftime('%Y-%m-%d')
         #If no existing holdings create 0 dollar entry to create table
         if holdings.empty:
             holding_dict = { "portfolioID": portfolio,
                                 "symbol": "USD",
                                 "endOfDayQuantity": 0.0,
                                 "lastUpdated": inceptionDate }
             holdings = pandas.DataFrame.from_dict(holding_dict, orient='index').T
         #Get all new transactions
         transactions = mdb_query.get_transactions(portfolio, date, "after")
 
         #Loop through dates and update holdings table
         while date <= currDate:
 
             #Insert dividends to transactions database and update transactions table
             #Dividends will be ahead of time so will be ready to be added on the correct date
 
             #Get dividends for all holdings except USD
             div_holdings = holdings[ ~holdings["symbol"].isin(["USD"]) ]
             dividends = mdb_query.get_dividends(div_holdings["symbol"].unique().tolist(), date, "on")
             #Get rid of any non-USD dividends
             if not dividends.empty:
                 dividends = dividends[ dividends['currency'] == 'USD' ]
 
             if not dividends.empty:
                 #Get dividends with exDate = date
                 div_date = dividends[ dividends.exDate == date ]
                 #Loop through dividends
                 for d_index, dividend in div_date.iterrows():
                     #print( dividend )
                     #Is dividend already in transactions?
                     #If not insert it
                     #Skip dividends with bad data entries
                     if not dividend.amount:
                         print( "Skipping dividend as amount is empty!" )
                         continue
                     if dividend.paymentDate == None:
                         print( "Skipping dividend as paymentDate is None!" )
                         continue
                     transactions_paymentDate = transactions
                     if not transactions.empty:
                         transactions_paymentDate = transactions[ (transactions.date == dividend.paymentDate) & (transactions.symbol == dividend.symbol) & (transactions.type == 'dividend') ]
                     holding_quantity = holdings[holdings["symbol"] == dividend.symbol]["endOfDayQuantity"]
                     holding_quantity.reset_index(drop=True, inplace=True)
                     if transactions_paymentDate.empty and (holding_quantity != 0).any():
                         transaction_table = { "portfolioID": portfolio,
                                                 "symbol": dividend.symbol,
                                                 "type": "dividend",
                                                 "date": dividend.paymentDate,
                                                 "price": float(dividend.amount),
                                                 "volume": holding_quantity.iloc[0],
                                                 "commission": 0.0 }
                         transactions = transactions.append( pandas.DataFrame.from_dict(transaction_table, orient='index').T, ignore_index=True, sort=False )
                         insert_pf_transactions = True
                         if insert_pf_transactions:
                             print( "Inserting dividend: " + date )
                             print( transaction_table )
                             self.db.pf_transactions.insert_one( transaction_table )
 
             #Now attend to transactions on date
             if transactions.empty:
                 #Increment date
                 date = (pandas.Timestamp(date) + pandas.DateOffset(days=1)).strftime('%Y-%m-%d')
                 continue
             transactions_date = transactions[transactions.date == date]
             #Loop through transactions
             for t_index, transaction in transactions_date.iterrows():
                 print( "Inserting transaction:" )
                 print( transaction )
                 #Get any existing holding for the transaction symbol
                 if transaction.type == "dividend":
                     holding = holdings[holdings.symbol == "USD"]
                 else:
                     holding = holdings[holdings.symbol == transaction.symbol]
                 holding.reset_index(drop=True, inplace=True)
                 #print( holding )
                 #Remove that holding from holdings table
                 if not holding.empty:
                     holdings = holdings[ ~holdings["symbol"].isin([holding['symbol'].iloc[0]]) ]
                 #print( holdings )
                 #Add any dividends to the holdings table
                 if transaction.type == "dividend":
                     holding["endOfDayQuantity"] = holding["endOfDayQuantity"] + (transaction.price * transaction.volume)
                     holding["lastUpdated"] = date
                     holdings = holdings.append( holding, ignore_index=True, sort=False )
                 #Add any deposits to the holdings table
                 if transaction.type == "deposit":
                     holding["endOfDayQuantity"] = holding["endOfDayQuantity"] + (transaction.price * transaction.volume)
                     holding["lastUpdated"] = date
                     holdings = holdings.append( holding, ignore_index=True, sort=False )
                 #Add any stocks purchased to the holdings table
                 if transaction.type == "buy":
                     holding_dict = {}
                     if not holding.empty:
                         holding_dict = { "portfolioID": transaction.portfolioID,
                                          "symbol": transaction.symbol,
                                          "endOfDayQuantity": holding["endOfDayQuantity"].iloc[0] + transaction.volume,
                                          "lastUpdated": date }
                     else:
                         holding_dict = { "portfolioID": transaction.portfolioID,
                                          "symbol": transaction.symbol,
                                          "endOfDayQuantity": transaction.volume,
                                          "lastUpdated": date }
                     #print( holding_dict )
                     holdings = holdings.append( pandas.DataFrame.from_dict(holding_dict, orient='index').T, ignore_index=True, sort=False )
                     #Adjust cash entry accordingly
                     cash = holdings[holdings.symbol == "USD"]
                     holdings = holdings[ ~holdings["symbol"].isin(["USD"]) ]
                     cash["endOfDayQuantity"] = cash["endOfDayQuantity"] - (transaction.price * transaction.volume)
                     cash["lastUpdated"] = date
                     holdings = holdings.append( cash, ignore_index=True, sort=False )
                 #print( holdings )
                 #Remove any stocks sold from the holdings table
                 if transaction.type == "sell":
                     if not holding.empty:
                         holding["endOfDayQuantity"] = holding["endOfDayQuantity"] - transaction.volume
                         holding["lastUpdated"] = date
                         holdings = holdings.append( holding, ignore_index=True, sort=False )
                     else:
                         raise Exception("Trying to sell unowned stock!")
                     #Adjust cash entry accordingly
                     cash = holdings[holdings.symbol == "USD"]
                     holdings = holdings[ ~holdings["symbol"].isin(["USD"]) ]
                     cash["endOfDayQuantity"] = cash["endOfDayQuantity"] + (transaction.price * transaction.volume)
                     cash["lastUpdated"] = date
                     holdings = holdings.append( cash, ignore_index=True, sort=False )
                 #print( holdings )
             #Upload new holdings entries to MongoDB
             holdings_date = holdings[holdings.lastUpdated == date]
             if not holdings_date.empty:
                 print( "New holdings:" )
                 print( holdings_date )
                 insert_holdings_tx = True
                 if insert_holdings_tx:
                     print( "Inserting holdings for " + portfolio )
                     self.db.pf_holdings.insert_many( holdings_date.to_dict('records') )
             #Increment date
             date = (pandas.Timestamp(date) + pandas.DateOffset(days=1)).strftime('%Y-%m-%d')