Update app.py

app.py

@@ -54,8 +54,12 @@ def get_financial_statements(ticker):
     q_balance_statement = pd.DataFrame(get_jsonparsed_data(base_url+'balance-sheet-statement/' + ticker + '?period=quarter' + '&apikey=' + apiKey))
     q_balance_statement = q_balance_statement.set_index('date').drop(columns_drop, axis=1)
     q_balance_statement = q_balance_statement.apply(pd.to_numeric, errors='coerce')
+
+    # shares outstanding
+    shs_data = get_jsonparsed_data('https://financialmodelingprep.com/api/v4/shares_float?symbol=' + ticker + '&apikey=' + apiKey)
+    shares_outstanding = shs_data[0]['outstandingShares']
         
-    return q_cash_flow_statement, cash_flow_statement, final_cash_flow_statement, q_balance_statement, latest_year
+    return q_cash_flow_statement, cash_flow_statement, final_cash_flow_statement, q_balance_statement, latest_year, shares_outstanding
  
  
 # check stability of cash flows
@@ -90,7 +94,7 @@ def get_statements_data(final_cash_flow_statement, q_balance_statement):
 # EPS next 5Y is the estimated earnings growth for next 5 years (if this is not present on finviz, we will use EPS next Y instead)
 # Beta captures the volatility of the stock, used for estimating discount rate later
 # Shs Outstand is the number of shares present in the market
-metric = ['Price', 'EPS next Y', 'EPS next 5Y', 'Beta', 'Shs Outstand']
+metric = ['Price', 'EPS next Y', 'EPS next 5Y', 'Beta']
 
 def fundamental_metric(soup, metric):
     # the table which stores the data in Finviz has html table attribute class of 'snapshot-td2'
@@ -136,35 +140,33 @@ def parse_finviz_dict(finviz_dict):
     EPS_growth_6Y_to_10Y = EPS_growth_5Y/2  # Half the previous growth rate, conservative estimate
     # Long term = previous growth rate or around long term inflation rate, whichever is lower to be conservative estimate
     long_term_growth_rate = np.minimum(EPS_growth_6Y_to_10Y, 3)
-    shares_outstanding = finviz_dict['Shs Outstand']
     beta = finviz_dict['Beta']
     current_price = finviz_dict['Price']
     
-    return EPS_growth_5Y, EPS_growth_6Y_to_10Y, long_term_growth_rate, beta, shares_outstanding, current_price
+    return EPS_growth_5Y, EPS_growth_6Y_to_10Y, long_term_growth_rate, beta, current_price
 
 
 ## Estimate Discount Rate from Beta
 def estimate_discount_rate(beta):
     # Beta shows the volatility of the stock, 
     # the higher the beta, we want to be more conservative by increasing the discount rate also.
-    discount_rate = 7
+    discount_rate = 9
     if(beta<0.80):
-        discount_rate = 5
+        discount_rate = 7
     elif(beta>=0.80 and beta<1):
-        discount_rate = 6
+        discount_rate = 8
     elif(beta>=1 and beta<1.1):
-        discount_rate = 6.5
+        discount_rate = 8.5
     elif(beta>=1.1 and beta<1.2):
-        discount_rate = 7
+        discount_rate = 9
     elif(beta>=1.2 and beta<1.3):
-        discount_rate = 7.5
+        discount_rate = 9.5
     elif(beta>=1.3 and beta<1.4):
-        discount_rate = 8
+        discount_rate = 10
     elif(beta>=1.4 and beta<1.6):
-        discount_rate = 8.5
+        discount_rate = 10.5
     elif(beta>=1.61):
-        discount_rate = 9   
-
+        discount_rate = 11   
     return discount_rate
 
 
@@ -285,7 +287,7 @@ def plot_forecasted_cash_flows(ticker, forecast_cash_flows_df):
 def run_all_steps(ticker):
     ticker = ticker.upper() # make sure ticker is caps
     
-    q_cash_flow_statement, cash_flow_statement, final_cash_flow_statement, q_balance_statement, latest_year = get_financial_statements(ticker)
+    q_cash_flow_statement, cash_flow_statement, final_cash_flow_statement, q_balance_statement, latest_year, shares_outstanding = get_financial_statements(ticker)
 
     fig_cash_flow = plot_cash_flow(ticker, cash_flow_statement)
 
@@ -293,7 +295,7 @@ def run_all_steps(ticker):
 
     finviz_dict = get_finviz_data(ticker)
 
-    EPS_growth_5Y, EPS_growth_6Y_to_10Y, long_term_growth_rate, beta, shares_outstanding, current_price = parse_finviz_dict(finviz_dict)
+    EPS_growth_5Y, EPS_growth_6Y_to_10Y, long_term_growth_rate, beta, current_price = parse_finviz_dict(finviz_dict)
 
     discount_rate = estimate_discount_rate(beta)