# Quant Finance Training

This repository contains codes that were executed during my training in the CQF (Certificate in Quantitative Finance). The codes are organized by class, facilitating navigation and reference.

## Repository Structure

In the `PythonLabs` folder, you will find the following files:

- **pythonlab01:** *Financial Time-Series Analysis*
- **pythonlab02:** *Statistical Analysis*
- **pythonlab03:** *Option Pricing with Binomial Trees*
- **pythonlab04:** *Portfolio Optimization*
- **pythonlab05:** *Risk Measures*
- **pythonlab06:** *Value at Risk*
- **pythonlab07:** *GARCH Models*
- **pythonlab08:** *Black-Scholes Model*
- **pythonlab09:** *Monte Carlo Simulation*
- **pythonlab10:** *Finite-Difference Method*
- **pythonlab11:** *Implied Volatility*
- **pythonlab12:** *LASSO and Ridge Regression*
- **pythonlab13:** *KNN and Support Vector Machine*
- **pythonlab14:** *Gradient Boosting Machine*
- **pythonlab15:** *K-Means*
- **pythonlab16:** *Self-Organizing Maps*
- **pythonlab17:** *Neural Network*
- **pythonlab18:** *Reinforcement Learning*
- **pythonlab19:** *Yield Curve*
- **pythonlab21:** *Credit Risk Analytics*
- **pythonlab22:** *Credit Default Swap*