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portfolio.py
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portfolio.py
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import yaml
import pandas as pd
import yfinance as yf
import matplotlib.pyplot as plt
import numpy as np
import pickle
pd.set_option("display.max_columns", None)
pd.set_option("expand_frame_repr", True)
pd.options.mode.chained_assignment = None # default='warn'
pd.set_option("display.precision", 2)
class portfolio_data:
def __init__(self):
self.portfolio_struct={
'Share': [],
'Qty': 0.0,
'Mean buy price': 0.0,
'Total Invest.': 0.0,
'Comms': 0.0,
'Cur. price': 0.0,
'Currency': 0.0,
'Total Currency': 0.0,
'Total CHF': 0.0,
'P&L Currency': 0.0,
'P&L CHF': 0.0,
'P&L %': 0.0,
'Type': 0.0,
'Last 1Y Div.': 0.0,
'Annual Rev. CHF': 0.0,
}
self.currency_ref_struct={
'Ticker': [],
'Type': 0.0,
}
self.sectors_struct={
'Ticker': [],
'Health care': 0.0,
'Consumer Stapples': 0.0,
'Financials': 0.0,
'Industrials': 0.0,
'Consumer Discretionary': 0.0,
'Basic Materials': 0.0,
'Technology': 0.0,
'Real Estate': 0.0,
'Communication': 0.0,
'Utilities': 0.0,
'Energy': 0.0,
'Cash/Derivatives': 0.0,
}
self.sectors_struct_noticker={
'Health care': [],
'Consumer Stapples': 0.0,
'Financials': 0.0,
'Industrials': 0.0,
'Consumer Discretionary': 0.0,
'Basic Materials': 0.0,
'Technology': 0.0,
'Real Estate': 0.0,
'Communication': 0.0,
'Utilities': 0.0,
'Energy': 0.0,
'Cash/Derivatives': 0.0,
}
self.market_struct={
'Ticker': [],
'USA': 0.0,
'EUROPE': 0.0,
'Pacific': 0.0,
'Emerging markets': 0.0,
'Middle East': 0.0,
'Other': 0.0,
}
self.market_struct_noticker={
'USA': [],
'EUROPE': 0.0,
'Pacific': 0.0,
'Emerging markets': 0.0,
'Middle East': 0.0,
'Other': 0.0,
}
self.portfolio_struct_filename='data/portfolio_struct.p'
self.currency_ref_struct_filename='data/currency_ref_struct.p'
self.sectors_struct_filename='data/sectors_struct.p'
self.sectors_struct_noticker_filename='data/sectors_struct_noticker.p'
self.market_struct_filename='data/market_struct.p'
self.market_struct_noticker_filename='data/market_struct_noticker.p'
def create(self):
pickle.dump( self.portfolio_struct, open( self.portfolio_struct_filename, "wb" ) )
pickle.dump( self.currency_ref_struct, open( self.currency_ref_struct_filename, "wb" ) )
pickle.dump( self.sectors_struct, open( self.sectors_struct_filename, "wb" ) )
pickle.dump( self.sectors_struct_noticker, open( self.sectors_struct_noticker_filename, "wb" ) )
pickle.dump( self.market_struct, open( self.market_struct_filename, "wb" ) )
pickle.dump( self.market_struct_noticker, open( self.market_struct_noticker_filename, "wb" ) )
def get_portfolio_struct(self):
return pickle.load( open( self.portfolio_struct_filename, "rb" ) )
def get_currency_ref_struct(self):
return pickle.load( open( self.currency_ref_struct_filename, "rb" ) )
def get_sectors_struct(self):
return pickle.load( open( self.sectors_struct_filename, "rb" ) )
def get_sectors_struct_noticker(self):
return pickle.load( open( self.sectors_struct_noticker_filename, "rb" ) )
def get_market_struct(self):
return pickle.load( open( self.market_struct_filename, "rb" ) )
def get_market_struct_noticker(self):
return pickle.load( open( self.market_struct_noticker_filename, "rb" ) )
class portfolio:
def __init__(self, tickers_filename, chf_usd_rate):
self.pf_data=portfolio_data()
self.pf_data.create()
self.portfolio = pd.DataFrame(self.pf_data.get_portfolio_struct())
self.currency_ref = pd.DataFrame(self.pf_data.get_currency_ref_struct())
self.annual_rev_chf=0.
self.total_invest_chf=0.00
if chf_usd_rate>0:
self.chf_usd_rate=chf_usd_rate
else:
self.get_chf_usd_rate()
print('1 CHF = %.4f USD' %self.chf_usd_rate)
self.read_tickers_file(tickers_filename)
def get_chf_usd_rate(self):
chf_usd = yf.Ticker("CHFUSD=X")
hist = chf_usd.history(period="1d")
self.chf_usd_rate=hist['Close'][-1]
return
def get_ticker_1y_dividend(self,ticker):
"""
read last year data for ticker
returns the sum of dividends
"""
tmp = yf.Ticker(ticker).history(period='1Y')
try:
return tmp['Dividends'].sum()
except:
return 0
def get_ticker_current_rate(self,ticker):
x = yf.Ticker(ticker)
hist = x.history(period="2d")
return hist['Close'][-1]
def get_ticker_support(self,ticker_ref, ticker):
result=ticker_ref.loc[ticker_ref['Ticker'] == ticker]
if len(result)>0:
index=result.index[0]
support=ticker_ref['Support'][index]
else:
index=-1
support='?'
return support
def get_ticker_type(self,ticker_ref, ticker):
result=ticker_ref.loc[ticker_ref['Ticker'] == ticker]
if len(result)>0:
index=result.index[0]
the_type=ticker_ref['Type'][index]
else:
index=-1
the_type='?'
return the_type
def read_tickers_file(self,tickers_filename):
try:
with open(tickers_filename) as file:
self.tickers = yaml.load(file, Loader=yaml.FullLoader)
#print(self.tickers)
except:
print('Error: unable to read %s.' %tickers_filename)
#print('----')
for k in self.tickers:
#print(k)
self.currency_ref=self.currency_ref.append( {
'Ticker': k,
#'Support':self.tickers[k]['Support'],
'Type':self.tickers[k]['Type'],
}, ignore_index=True)
#print('----')
#print(self.currency_ref)
return
def read_transactions_file(self,transactions_filename):
try:
with open(transactions_filename) as file:
self.transactions = yaml.load(file, Loader=yaml.FullLoader)
except:
print('Error: unable to read %s.' %tickers_filename)
def process_transactions(self,transactions_filename, display=False):
self.read_transactions_file(transactions_filename)
for k in self.transactions:
t=self.transactions[k]
date=t['Date']
#print(t)
if t['Action']=='INJECT_CURRENCY':
currency=t['Currency']
qty=t['Qty']
result=self.portfolio.loc[self.portfolio['Share'] == currency]
if len(result)>0:
index=result.index[0]
else:
#print('Adding',currency,'to portfolio')
self.portfolio = self.portfolio.append({
'Share':currency,
'Qty':0.0,
'Mean buy price':1,
'Total Invest.':0,
'Cur. price':1,
'Currency':0.0,
'Total Currency':0.0,
'Total CHF':0.0,
'P&L Currency':0.0,
'P&L CHF':0.0,
'P&L %': 0.0,
#'Support':self.get_ticker_support(self.currency_ref,currency),
'Type':self.get_ticker_type(self.currency_ref,currency),
'Last 1Y Div.': 0.0,
'Annual Rev. CHF': 0.0,
}, ignore_index=True)
result=self.portfolio.loc[self.portfolio['Share'] == currency]
index=result.index[0]
self.portfolio['Qty'][index]+=qty
self.portfolio['Currency'][index]=currency
self.total_invest_chf+=qty
if display:
print("%s %-16s %+8.2f %s" %(date,t['Action'],qty,currency))
elif t['Action']=='BUY_CURRENCY':
to_currency=t['Currency']
from_currency=t['With']
qty=t['Qty']
rate=t['Rate']
result=self.portfolio.loc[self.portfolio['Share'] == to_currency]
if len(result)>0:
index_to=result.index[0]
else:
#print('Adding',to_currency,'to portfolio')
self.portfolio = self.portfolio.append({
'Share':to_currency,
'Qty':0.0,
'Mean buy price':1,
'Total Invest.':0,
'Cur. price':1,
'Currency':0.0,
'Total Currency':0.0,
'Total CHF':0.0,
'P&L Currency':0.0,
'P&L CHF':0.0,
'P&L %': 0.0,
#'Support':self.get_ticker_support(self.currency_ref,currency),
'Type':self.get_ticker_type(self.currency_ref,currency),
'Last 1Y Div.': 0.0,
'Annual Rev. CHF': 0.0,
}, ignore_index=True)
result=self.portfolio.loc[self.portfolio['Share'] == to_currency]
index_to=result.index[0]
result=self.portfolio.loc[self.portfolio['Share'] == from_currency]
if len(result)>0:
index_from=result.index[0]
else:
print('ERROR, currency',from_currency,'not found.')
self.portfolio['Qty'][index_to]+=qty*rate
self.portfolio['Qty'][index_from]-=qty+t['Comm']
self.portfolio['Currency'][index_to]=to_currency
if display:
print("%s %-16s %+8.2f %3s => %+8.2f %3s" %(date,t['Action'],qty,from_currency,qty*rate,to_currency))
elif t['Action']=='BUY_SHARE':
ticker=t['Ticker']
currency=t['Currency']
qty=t['Qty']
rate=t['Rate']
result=self.portfolio.loc[self.portfolio['Share'] == ticker]
if len(result)>0:
index_to=result.index[0]
else:
#print('Adding',ticker,'to portfolio')
self.portfolio = self.portfolio.append({
'Share':ticker,
'Qty':0.0,
'Mean buy price':0.0,
'Total Invest.':0,
'Comms': 0.0,
'Cur. price':0.0,
'Currency':0.0,
'Total Currency':0.0,
'Total CHF':0.0,
'P&L Currency':0.0,
'P&L CHF':0.0,
'P&L %': 0.0,
#'Support':self.get_ticker_support(self.currency_ref,ticker),
'Type':self.get_ticker_type(self.currency_ref,ticker),
'Last 1Y Div.': 0.0,
'Annual Rev. CHF': 0.0,
}, ignore_index=True)
result=self.portfolio.loc[self.portfolio['Share'] == ticker]
index_to=result.index[0]
result=self.portfolio.loc[self.portfolio['Share'] == currency]
if len(result)>0:
index_from=result.index[0]
else:
print('ERROR, currency',currency,'not found.')
if display:
print("%s %-16s %8.2f %-10s at %8.2f %s (+comm=%.2f)" %(date,t['Action'],qty,ticker,rate,currency,t['Comm']))
# first buy of this ticker
if self.portfolio['Qty'][index_to]==0:
self.portfolio['Qty'][index_to]=qty
self.portfolio['Mean buy price'][index_to]=(qty*rate+t['Comm'])/qty
self.portfolio['Total Invest.'][index_to]=self.portfolio['Mean buy price'][index_to]*self.portfolio['Qty'][index_to]
self.portfolio['Comms'][index_to]=t['Comm']
# add more
else:
current_qty=self.portfolio['Qty'][index_to]
current_value=self.portfolio['Qty'][index_to]*self.portfolio['Mean buy price'][index_to]#+self.portfolio['Comms'][index_to]
new_qty=current_qty+qty
new_value=current_value+qty*rate+t['Comm']
new_rate=new_value/new_qty
self.portfolio['Qty'][index_to]=new_qty
self.portfolio['Mean buy price'][index_to]=new_rate
self.portfolio['Total Invest.'][index_to]=self.portfolio['Mean buy price'][index_to]*self.portfolio['Qty'][index_to]
self.portfolio['Comms'][index_to]+=t['Comm']
total=qty*rate+t['Comm']
#print('Total cost: ',total)
self.portfolio['Qty'][index_from]-=total
current_rate=self.get_ticker_current_rate(ticker)
self.portfolio['Cur. price'][index_to]=current_rate
self.portfolio['Currency'][index_to]=currency
for index in range(len(self.portfolio)):
self.portfolio['Total CHF'][index]=self.portfolio['Qty'][index]*self.portfolio['Cur. price'][index]
self.portfolio['Total Currency'][index]=self.portfolio['Total CHF'][index]
self.portfolio['P&L %'][index]=0
if self.portfolio['Total Invest.'][index]>0:
self.portfolio['P&L %'][index]=100*(self.portfolio['Total Currency'][index]-self.portfolio['Total Invest.'][index])/self.portfolio['Total Invest.'][index]
self.portfolio['P&L CHF'][index]=self.portfolio['Qty'][index]*(self.portfolio['Cur. price'][index]-self.portfolio['Mean buy price'][index])
self.portfolio['P&L Currency'][index]=self.portfolio['P&L CHF'][index]
if self.portfolio['Currency'][index]=='USD':
self.portfolio['Total CHF'][index]/=self.chf_usd_rate
self.portfolio['P&L CHF'][index]/=self.chf_usd_rate
if self.portfolio['Type'][index]!='Cash':
self.portfolio['Last 1Y Div.'][index]=self.get_ticker_1y_dividend(self.portfolio['Share'][index])
annual_rev_for_share=self.portfolio['Last 1Y Div.'][index]*self.portfolio['Qty'][index]
if self.portfolio['Currency'][index]=='USD':
self.annual_rev_chf+=annual_rev_for_share/self.chf_usd_rate
else:
self.annual_rev_chf+=annual_rev_for_share
self.portfolio['Annual Rev. CHF'][index]=annual_rev_for_share
self.ratio=100*self.portfolio['P&L CHF'].sum()/self.total_invest_chf
print('\n')
print('Total injected: %+9.2f CHF' %self.total_invest_chf)
print('Current value: %+9.2f CHF' %self.portfolio['Total CHF'].sum())
print('P&L: %+9.2f CHF (%.1f%%)' %(self.portfolio['P&L CHF'].sum(),self.ratio))
print('Est. annual rev.: %+9.2f CHF' %self.annual_rev_chf)
def compute_sectors_ratio(self):
self.sectors = pd.DataFrame(self.pf_data.get_sectors_struct())
self.sectors_details = pd.DataFrame(self.pf_data.get_sectors_struct())
self.sectors_ratio = pd.DataFrame(self.pf_data.get_sectors_struct_noticker())
# create a table with sectors ratio for each ticker => sectors
for t in (self.tickers):
if self.tickers[t]['Support']!='Currency':
info=self.tickers[t]['Sectors']
if 0:
tmp_o=self.pf_data.get_sectors_struct()
tmp_o['Ticker']=t
tmp_o['Health care']=info['Health care'],
tmp_o['Consumer Stapples']=info['Consumer Stapples'],
tmp_o['Financials']=info['Financials'],
tmp_o['Industrials']=info['Industrials'],
tmp_o['Consumer Discretionary']=info['Consumer Discretionary'],
tmp_o['Basic Materials']=info['Basic Materials'],
tmp_o['Technology']=info['Technology'],
tmp_o['Real Estate']=info['Real Estate'],
tmp_o['Communication']=info['Communication'],
tmp_o['Utilities']=info['Utilities'],
tmp_o['Energy']=info['Energy'],
tmp_o['Cash/Derivatives']=info['Cash/Derivatives'],
self.sectors = self.sectors.append(tmp_o, ignore_index=True)
else:
self.sectors = self.sectors.append({
'Ticker': t,
'Health care': info['Health care'],
'Consumer Stapples': info['Consumer Stapples'],
'Financials': info['Financials'],
'Industrials': info['Industrials'],
'Consumer Discretionary': info['Consumer Discretionary'],
'Basic Materials': info['Basic Materials'],
'Technology': info['Technology'],
'Real Estate': info['Real Estate'],
'Communication': info['Communication'],
'Utilities': info['Utilities'],
'Energy': info['Energy'],
'Cash/Derivatives': info['Cash/Derivatives'],
}, ignore_index=True)
#sectors
# compute the value per sectors for all ticker => sectors_details
for i in range(len(self.portfolio)):
#print(p.portfolio.loc[i, "Share"], p.portfolio.loc[i, "Total CHF"])
ticker=self.portfolio.loc[i, "Share"]
total_chf=self.portfolio.loc[i, "Total CHF"]
if self.tickers[ticker]['Support']!='Currency':
result=self.sectors.loc[self.sectors['Ticker'] == ticker]
tmp=self.pf_data.get_sectors_struct()
#print(tmp)
for k in self.sectors_details.columns:
if k=='Ticker':
tmp[k]=ticker
else:
#print(k,result[k].to_numpy())
if result[k].to_numpy()[0]!=None and False==np.isnan(result[k].to_numpy()[0]):
tmp[k]=result[k].to_numpy()[0]*total_chf/100.
else:
tmp[k]=0
self.sectors_details = self.sectors_details.append(tmp, ignore_index=True)
# compute the ratio per sectors for all sectors => sectors_ratio
tmp=self.pf_data.get_sectors_struct_noticker()
for k in self.sectors_ratio.columns:
total=self.sectors_details[k].sum()/self.total_invest_chf*100
#print(k,total)
tmp[k]=total
self.sectors_ratio = self.sectors_ratio.append(tmp, ignore_index=True)
return self.sectors_ratio
def compute_market_ratio(self):
self.market = pd.DataFrame(self.pf_data.get_market_struct())
self.market_details = pd.DataFrame(self.pf_data.get_market_struct())
self.market_ratio = pd.DataFrame(self.pf_data.get_market_struct_noticker())
for t in (self.tickers):
if self.tickers[t]['Support']!='Currency':
info=self.tickers[t]['Markets']
tmp=self.pf_data.get_market_struct()
tmp['Ticker']=t
tmp['USA']=info['USA']
tmp['EUROPE']=info['EUROPE']
tmp['Pacific']=info['Pacific']
tmp['Emerging markets']=info['Emerging markets']
tmp['Middle East']=info['Middle East']
tmp['Other']=info['Other']
self.market = self.market.append(tmp, ignore_index=True)
#self.market
for i in range(len(self.portfolio)):
#print(p.portfolio.loc[i, "Share"], p.portfolio.loc[i, "Total CHF"])
ticker=self.portfolio.loc[i, "Share"]
total_chf=self.portfolio.loc[i, "Total CHF"]
if self.tickers[ticker]['Support']!='Currency':
result=self.market.loc[self.market['Ticker'] == ticker]
tmp=self.pf_data.get_market_struct()
for k in self.market_details.columns:
if k=='Ticker':
tmp[k]=ticker
else:
#print(k,result[k].to_numpy())
if result[k].to_numpy()[0]!=None and False==np.isnan(result[k].to_numpy()[0]):
tmp[k]=result[k].to_numpy()[0]*total_chf/100.
else:
tmp[k]=0
self.market_details = self.market_details.append(tmp, ignore_index=True)
tmp=self.pf_data.get_market_struct_noticker()
for k in self.market_ratio.columns:
total=self.market_details[k].sum()/self.total_invest_chf*100
tmp[k]=total
self.market_ratio = self.market_ratio.append(tmp, ignore_index=True)
return self.market_ratio