Update app.py

app.py

@@ -67,8 +67,112 @@ def get_income_hvplot(ticker):
     # return ( DF.hvplot.line(y='Net Income') * DF.hvplot.scatter(y='Net Income').opts(color="red") )+ (DF.hvplot.line(y='Gross Profit') * DF.hvplot.scatter(y='Gross Profit').opts(color="red") )+ 
     # (DF.hvplot.line(y='Total Revenue') * DF.hvplot.scatter(y='Total Revenue').opts(color="red") )
 
+def lookup_discountedrate(betavalue):
+  betavsdiscountedrate = {1: 5, 1: 6, 1.1: 6.5, 1.2: 7, 1.3: 7.5, 1.4: 8, 1.5: 8.5, 1.6: 9}
+  if betavalue < 1:
+    return betavsdiscountedrate[1]  # Return the value for key 1 if key is below 1
+  elif betavalue > 1.6:
+    return betavsdiscountedrate[1.6]  # Return the value for key 1.6 if key is above 1.6
+  else:
+    # Find the closest key to the given key
+    closest_key = min(betavsdiscountedrate.keys(), key=lambda x: abs(x - betavalue))
 
+    # Get the corresponding value
+    value = betavsdiscountedrate[closest_key]
 
+    return value
+
+
+def calc_fairprice_CDF(ticker):
+  import yfinance as yf
+  yfobj = yf.Ticker(ticker)
+
+  #calculate eps growing next 5 years
+  EPSnext5Y = yfobj.get_info()['trailingPE'] / yfobj.get_info()['trailingPegRatio']
+
+  years = 10
+  #
+  cashflowinitial = yfobj.get_info()['operatingCashflow']
+
+  cashflowlst=[]
+  cashflow = cashflowinitial
+  for i in range(1,years+1):
+    cashflow = cashflow*(1+EPSnext5Y/100)
+    cashflowlst.append(cashflow)
+
+  discountedrate = lookup_discountedrate(yfobj.get_info()['beta'])
+
+  discountedfactorlst =[]
+  discountedvaluelst=[]
+  discountedfactor =1
+
+  for i in range(1,years+1):
+    discountedfactor =( 1 / (1+ discountedrate/100)**i)
+    discountedfactorlst.append(discountedfactor)
+    discountedvalue = discountedfactor * cashflowlst[i-1]
+    discountedvaluelst.append(discountedvalue)
+
+  PV10yearsCashFlow =0
+  for i in range(0,years):
+    PV10yearsCashFlow += discountedvaluelst[i]
+
+  #intrinsic value before cash/debt
+  intrinsicvaluebeforecashdebt = PV10yearsCashFlow / yfobj.get_info()['sharesOutstanding']
+
+  debtpershare = yfobj.get_info()['totalDebt'] / yfobj.get_info()['sharesOutstanding']
+  cashpershare = yfobj.get_info()['totalCash'] / yfobj.get_info()['sharesOutstanding']
+  intrinsicvalue = intrinsicvaluebeforecashdebt + cashpershare - debtpershare
+
+  previousClose = yfobj.get_info()['previousClose']
+  deviation = 100*(intrinsicvalue - previousClose) / previousClose
+  return intrinsicvalue , previousClose , deviation
+
+
+def calc_fairprice_DnetP(ticker):
+  import yfinance as yf
+  yfobj = yf.Ticker(ticker)
+
+  #calculate eps growing next 5 years
+  EPSnext5Y = yfobj.get_info()['trailingPE'] / yfobj.get_info()['trailingPegRatio']
+
+  years = 5
+  #
+  cashflowinitial = yfobj.get_info()['netIncomeToCommon']
+
+  cashflowlst=[]
+  cashflow = cashflowinitial
+  for i in range(1,years+1):
+    cashflow = cashflow*(1+EPSnext5Y/100)
+    cashflowlst.append(cashflow)
+
+  discountedrate = lookup_discountedrate(yfobj.get_info()['beta'])
+
+  discountedfactorlst =[]
+  discountedvaluelst=[]
+  discountedfactor =1
+
+  for i in range(1,years+1):
+    discountedfactor =( 1 / (1+ discountedrate/100)**i)
+    discountedfactorlst.append(discountedfactor)
+    discountedvalue = discountedfactor * cashflowlst[i-1]
+    discountedvaluelst.append(discountedvalue)
+
+  PV10yearsCashFlow =0
+  for i in range(0,years):
+    PV10yearsCashFlow += discountedvaluelst[i]
+
+  #intrinsic value before cash/debt
+  intrinsicvaluebeforecashdebt = PV10yearsCashFlow / yfobj.get_info()['sharesOutstanding']
+
+  debtpershare = yfobj.get_info()['totalDebt'] / yfobj.get_info()['sharesOutstanding']
+  cashpershare = yfobj.get_info()['totalCash'] / yfobj.get_info()['sharesOutstanding']
+  intrinsicvalue = intrinsicvaluebeforecashdebt + cashpershare - debtpershare
+
+  previousClose = yfobj.get_info()['previousClose']
+  intrinsicvalue= intrinsicvalue + previousClose
+
+  deviation = 100*(intrinsicvalue - previousClose) / previousClose
+  return intrinsicvalue , previousClose , deviation
     
 # tickers = ['AAPL', 'META', 'GOOG', 'IBM', 'MSFT','NKE','DLTR','DG']
 # ticker = pn.widgets.Select(name='Ticker', options=tickers)