https://github.com/real-veersandhu/bond-analysis-dashboard
Interactive dashboard that provides key insights into bond valuation, risk metrics, and price simulations using Monte Carlo methods.
https://github.com/real-veersandhu/bond-analysis-dashboard
finance fixed-income python
Last synced: 8 months ago
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Interactive dashboard that provides key insights into bond valuation, risk metrics, and price simulations using Monte Carlo methods.
- Host: GitHub
- URL: https://github.com/real-veersandhu/bond-analysis-dashboard
- Owner: Real-VeerSandhu
- Created: 2025-02-22T00:12:09.000Z (9 months ago)
- Default Branch: main
- Last Pushed: 2025-02-22T00:46:52.000Z (9 months ago)
- Last Synced: 2025-02-22T01:20:44.006Z (9 months ago)
- Topics: finance, fixed-income, python
- Language: Python
- Homepage: https://bond-analysis-dashboard.streamlit.app/
- Size: 265 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Fixed-Income Bond Analysis Dashboard
## Overview
This project is a **Fixed-Income Bond Analysis [Dashboard](https://bond-analysis-dashboard.streamlit.app/)** built using **Python, Streamlit, NumPy, SciPy, and Plotly**. The dashboard provides key insights into bond valuation, risk metrics, and price simulations using Monte Carlo methods.
## Features
- **Yield to Maturity (YTM) Calculation** – Computes the bond's internal rate of return using numerical root-finding methods.
- **Bond Pricing Model** – Calculates bond price based on coupon rate, time to maturity, and YTM.
- **Bond Duration & Convexity** – Measures interest rate sensitivity and curvature risk.
- **Current Yield Calculation** – Determines the annual return based on the bond’s market price.
- **Monte Carlo Simulation** – Generates a distribution of possible bond prices based on simulated YTMs.
- **Interactive Dashboard** – Users can input bond parameters and visualize results dynamically.
## Monte Carlo Simulation Statistics
The Monte Carlo module generates **thousands of bond price simulations**, providing:
- **Mean Price** – Expected bond price.
- **Standard Deviation** – Volatility of simulated prices.
- **5th and 95th Percentiles** – Risk bounds for price movement.
- **Min and Max Prices** – Extreme cases for stress testing.
## Technologies Used
- **Python** – Core programming language.
- **Streamlit** – Interactive web application framework.
- **NumPy & SciPy** – Numerical computing and optimization.
- **Plotly** – Data visualization for histograms and charts.
## Sample Output
## License
This project is licensed under the MIT License – see the LICENSE file for details.