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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