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Financial Modeling Toolkit

Welcome to the Financial Modeling Toolkit, a Python-based library for conducting financial analysis, valuation, risk management, and portfolio optimization.

Overview

This toolkit provides a set of classes and functions to perform various financial modeling tasks, including:

Net Present Value (NPV) calculation Internal Rate of Return (IRR) calculation Payback Period analysis Portfolio optimization for maximum Sharpe ratio Risk management with Value at Risk (VaR) Financial analysis metrics (e.g., profitability ratio, return on investment) The toolkit is designed to be modular and extensible, allowing users to incorporate additional functionalities and customize analyses based on specific requirements.

Dependencies

Python 3.x NumPy SciPy (for optimization)

Install the required dependencies using pip:

'''bash Copy code pip install numpy scipy '''

Usage

Clone the Repository ''' bash Copy code git clone https://github.com/your_username/financial-modeling-toolkit.git cd financial-modeling-toolkit '''

Import the FinancialModeling Class

python Copy code from financial_modeling import FinancialModeling Initialize FinancialModeling Object python Copy code initial_investment = -100000 cash_flows = [30000, 40000, 50000, 60000, 70000]

Create an instance of FinancialModeling

financial_model = FinancialModeling(initial_investment, cash_flows) Perform Financial Calculations python Copy code

Calculate Net Present Value (NPV)

discount_rate = 0.1 npv_result = financial_model.calculate_npv(discount_rate)

Calculate Internal Rate of Return (IRR)

irr_result = financial_model.calculate_irr()

Calculate Payback Period

payback_period_result = financial_model.calculate_payback_period()

Other financial analysis

profitability_ratio = financial_model.calculate_profitability_ratio(50000, 200000) Explore Additional Functionalities python Copy code

Example of portfolio optimization

expected_returns = [0.05, 0.08, 0.12] # Expected returns of assets cov_matrix = [[0.1, 0.05, 0.03], [0.05, 0.12, 0.06], [0.03, 0.06, 0.15]] # Covariance matrix optimal_weights = financial_model.calculate_optimal_portfolio_weights(expected_returns, cov_matrix)

Contributors

Kampamba Shula (@kshula)

License This project is licensed under the MIT License - see the LICENSE file for details.

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