How arunp77/montecarlo-simulation works
This repository is an educational Monte Carlo simulation project: its website and notebooks present simulation fundamentals, statistical methods, variance reduction, and finance applications. The principal hands-on workflow is to obtain or generate inputs, simulate outcomes, and inspect estimates or risk measures. The graph also includes the small Flask dice-simulation endpoint. Source evidence is limited to the README and sampled Python excerpts; notebook and website relationships beyond documented capabilities are not inferred.
Main entry points: app.py Dice simulation API · Adani-share.py Adani share analysis · Reference-monte-carlo.py VaR and CVaR · index.html Learning website
Components 20
Simulation learning
- Simulation basics
0.1-Monte-carlo-simulations.ipynb - Covariance analysis
0.2-covariance matrix.ipynb - Dice example
Other-example/Dice-rolling.ipynb - Random walk
Other-example/Random-walk-problem.ipynb
Finance applications
- Risk analysis
Finance-risk/0.1-Risk-analysis.ipynb - Credit risk
Finance-risk/0.2-Credit-risk.ipynb - Market risk
Finance-risk/0.2-Market-risk.ipynb - Portfolio performance
Finance-risk/Portfolioperformance.ipynb - Adani share analysis
Finance-risk/Adani-share.py - VaR and CVaR
Finance-risk/Reference-monte-carlo.py
Website and API
- Learning website
index.html - Home content
home.html - Project listings
projects.html - Finance content
finanical-risk-analysis.html - Market risk page
market-risk.html - Contact page
contact.html - Dice simulation API
app.py
Simulation methods
- Variance reduction
0.3-Variance-reduction-techniques.py
Other components
- Learner
- Market data
Connections 5
- Learner → Learning website: views
README.md - Learner → Dice simulation API: posts simulation
- Dice simulation API → Dice simulation API: returns average
app.py - Adani share analysis → Market data: downloads prices
Finance-risk/Adani-share.py - VaR and CVaR → Market data: downloads prices
Finance-risk/Reference-monte-carlo.py