Financial Tools

A comprehensive, interactive web application built with Streamlit for financial concepts demonstration, simulation, and education. This application simplifies complex financial concepts into easy-to-understand interactive modules, covering everything from basic bond pricing to options strategies and credit risk modeling.

Live Demo

You can explore and interact with the fully deployed version of the application here:
Financial Markets Demo

Disclaimer

This application is strictly for educational purposes only. The calculations, models, and data provided do not constitute professional financial advice or a real-world financial tool.

Features

The application is divided into six distinct educational modules:

Module 1: Foundations & Macroeconomics

• Bond Pricing: Determine the market value of a bond based on current interest rates and maturity. Includes duration and convexity metrics to measure interest rate sensitivity.
• Inflation: Calculate the true growth of wealth by adjusting nominal gains for inflation to see actual purchasing power.
• Short Selling: Track the short selling cycle, including financing fees, dividend obligations, and margin call thresholds.
• Central Bank Reserve: Simulate the fractional reserve banking system, the deposit multiplier effect, and bank run stress tests.

Module 2: Performance & Valuation

• Returns: Calculate and compare arithmetic and logarithmic returns, and evaluate the impact of dividend yields.
• Valuation Models: Estimate intrinsic stock value using the Gordon Growth Model (GGM) and the H-Model.
• Sharpe-Ratio: Evaluate risk-adjusted performance by measuring expected returns against a risk-free benchmark.

Module 3: Portfolio Management

• Portfolio Simulator: Design a custom two-asset portfolio to see how correlation drives diversification and creates a "Risk Gap."
• Portfolio Performance: Audit portfolio efficiency using the Sharpe Ratio, Coefficient of Variation (CV), and Value at Risk (VaR).
• ETF Evaluation: Calculate the Net Asset Value (NAV) of an ETF and check for stale pricing arbitrage risks.

Module 4: Derivatives & Advanced Models

• Payoff Visualizer: Visualize the profit and loss profiles (Hockey Stick payoff) of Call and Put options.
• Put Call Parity: Detect market mispricing and arbitrage opportunities by comparing a Fiduciary Call and a Protective Put.
• Merton Model Simulator: Evaluate credit risk and housing debt by treating equity as a call option on underlying property assets, visualizing the "Right to Default."

Module 5: Credit & Lending

• Loan Evaluator: Simulate mortgage underwriting using Loan-to-Value (LTV) and Debt-to-Income (DTI) ratios.
• MBS Simulator: Test how a securitized mortgage pool (Mortgage-Backed Securities) absorbs credit losses from the bottom up across different risk tranches.
• Credit Risk: Calculate Expected Loss on specific loans and determine the Implied Probability of Default from public bond spreads.

Module 6: Real Estate & Equity Markets

• Leverage and Development: Calculate a homeowner's net equity and leverage multiplier, or figure out a real estate developer's absolute break-even sale price based on hard and soft costs.
• Equity Research: Evaluate intrinsic value based on P/E, P/B, and PEG ratios.
• Technical Analysis: Track simple price momentum and use the Relative Strength Index (RSI) to spot overbought or oversold conditions.

Prerequisites

Ensure you have Python 3.12 or newer installed. The project relies on the following core libraries:

• streamlit (>= 1.52.2)
• pandas (>= 2.3.3)
• matplotlib (>= 3.10.8)
• plotly (>= 6.5.2)

Installation

1. Clone the repository:

   git clone https://github.com/drjollof/financial-tools
   cd financial-tools

2. Set up a virtual environment (Recommended):

   python -m venv .venv
   source .venv/bin/activate  # On Windows use: .venv\Scripts\activate

3. Install dependencies: If you are using pip, you can install the dependencies defined in the project:

   pip install streamlit pandas matplotlib plotly

   (Note: This project uses pyproject.toml and uv.lock, so you can also use modern package managers like uv or pip install .)

Usage

To run the application locally, navigate to the root directory of the project and run the following command:

streamlit run app.py