Merge branch 'main' of https://github.com/arjunlimat/finmodels

tamilselvanarjun · Mar 18, 2024 · 99e48b5 · 99e48b5
2 parents 321f29c + acba9ef
commit 99e48b5
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Showing 12 changed files with 20 additions and 18 deletions.
diff --git a/build/lib/finmodels/dcf.py b/build/lib/finmodels/dcf.py
@@ -1,4 +1,3 @@
-# financial_models/dcf.py
 def calculate_dcf(cash_flows, discount_rate):
     """
     Calculate the Discounted Cash Flow (DCF) valuation.
@@ -10,5 +9,5 @@ def calculate_dcf(cash_flows, discount_rate):
     Returns:
     - DCF value
     """
-    dcf_value = sum(cf / (1 + discount_rate) ** (i + 1) for i, cf in enumerate(cash_flows))
-    return dcf_value
+    dcf_value = sum(cf / (1 + discount_rate) ** i for i, cf in enumerate(cash_flows))
+    return dcf_value
diff --git a/build/lib/finmodels/ipo.py b/build/lib/finmodels/ipo.py
@@ -8,7 +8,7 @@ def __init__(self, initial_valuation, funds_raised, operating_income, growth_rat
 
     def calculate_ipo_valuation(self):
         # Calculate the IPO valuation using a simple discounted cash flow (DCF) model
-        discount_factor = 1 / (1 + self.growth_rate)
+        discount_factor = 1 + self.growth_rate
         future_cash_flows = [self.operating_income * (discount_factor ** year) for year in range(1, self.years + 1)]
         total_cash_flows = sum(future_cash_flows)
         ipo_valuation = self.initial_valuation + total_cash_flows + self.funds_raised
@@ -18,7 +18,6 @@ def print_summary(self):
         ipo_valuation = self.calculate_ipo_valuation()
         print(f"IPO Valuation after {self.years} years: ${ipo_valuation:,.2f}")
 
-
 # Example usage
 #initial_valuation = 500000000  # Initial company valuation before IPO
 #funds_raised = 100000000  # Funds raised during the IPO

diff --git a/build/lib/finmodels/portfolio_optimization.py b/build/lib/finmodels/portfolio_optimization.py
@@ -1,4 +1,3 @@
-# financial_models/portfolio_optimization.py
 import numpy as np
 import cvxpy as cp
 
@@ -11,7 +10,7 @@ def optimize_portfolio(expected_returns, covariance_matrix):
     - covariance_matrix: Covariance matrix of asset returns
 
     Returns:
-    - Optimal portfolio weights
+    - Optimal portfolio weights if successful, None otherwise
     """
     num_assets = len(expected_returns)
 
@@ -30,4 +29,8 @@ def optimize_portfolio(expected_returns, covariance_matrix):
     problem = cp.Problem(objective, constraints)
     problem.solve()
 
-    return weights.value
+    if problem.status == 'optimal':
+        return weights.value
+    else:
+        print("Optimization problem could not be solved.")
+        return None
diff --git a/dist/finmodels-2.0.0-py3-none-any.whl b/dist/finmodels-2.0.0-py3-none-any.whl
diff --git a/dist/finmodels-2.0.0.tar.gz b/dist/finmodels-2.0.0.tar.gz
diff --git a/dist/finmodels-2.0.3-py3-none-any.whl b/dist/finmodels-2.0.3-py3-none-any.whl
diff --git a/dist/finmodels-2.0.3.tar.gz b/dist/finmodels-2.0.3.tar.gz
diff --git a/finmodels.egg-info/PKG-INFO b/finmodels.egg-info/PKG-INFO
@@ -1,6 +1,6 @@
 Metadata-Version: 2.1
 Name: finmodels
-Version: 2.0.0
+Version: 2.0.3
 Summary: finmodels is a Python package that provides various financial models for analysis and optimization.
 Home-page: https://github.com/arjunlimat/finmodels
 Author: Tamilselvan_Arjunan

diff --git a/finmodels/dcf.py b/finmodels/dcf.py
@@ -1,4 +1,3 @@
-# financial_models/dcf.py
 def calculate_dcf(cash_flows, discount_rate):
     """
     Calculate the Discounted Cash Flow (DCF) valuation.
@@ -10,5 +9,5 @@ def calculate_dcf(cash_flows, discount_rate):
     Returns:
     - DCF value
     """
-    dcf_value = sum(cf / (1 + discount_rate) ** (i + 1) for i, cf in enumerate(cash_flows))
-    return dcf_value
+    dcf_value = sum(cf / (1 + discount_rate) ** i for i, cf in enumerate(cash_flows))
+    return dcf_value
diff --git a/finmodels/ipo.py b/finmodels/ipo.py
@@ -8,7 +8,7 @@ def __init__(self, initial_valuation, funds_raised, operating_income, growth_rat
 
     def calculate_ipo_valuation(self):
         # Calculate the IPO valuation using a simple discounted cash flow (DCF) model
-        discount_factor = 1 / (1 + self.growth_rate)
+        discount_factor = 1 + self.growth_rate
         future_cash_flows = [self.operating_income * (discount_factor ** year) for year in range(1, self.years + 1)]
         total_cash_flows = sum(future_cash_flows)
         ipo_valuation = self.initial_valuation + total_cash_flows + self.funds_raised
@@ -18,7 +18,6 @@ def print_summary(self):
         ipo_valuation = self.calculate_ipo_valuation()
         print(f"IPO Valuation after {self.years} years: ${ipo_valuation:,.2f}")
 
-
 # Example usage
 #initial_valuation = 500000000  # Initial company valuation before IPO
 #funds_raised = 100000000  # Funds raised during the IPO

diff --git a/finmodels/portfolio_optimization.py b/finmodels/portfolio_optimization.py
@@ -1,4 +1,3 @@
-# financial_models/portfolio_optimization.py
 import numpy as np
 import cvxpy as cp
 
@@ -11,7 +10,7 @@ def optimize_portfolio(expected_returns, covariance_matrix):
     - covariance_matrix: Covariance matrix of asset returns
 
     Returns:
-    - Optimal portfolio weights
+    - Optimal portfolio weights if successful, None otherwise
     """
     num_assets = len(expected_returns)
 
@@ -30,4 +29,8 @@ def optimize_portfolio(expected_returns, covariance_matrix):
     problem = cp.Problem(objective, constraints)
     problem.solve()
 
-    return weights.value
+    if problem.status == 'optimal':
+        return weights.value
+    else:
+        print("Optimization problem could not be solved.")
+        return None
diff --git a/setup.py b/setup.py
@@ -5,7 +5,7 @@
 
 setup(
     name='finmodels',
-    version='2.0.0',
+    version='2.0.3',
     packages=find_packages(),
     install_requires=[
         'numpy',