QuantMethods-MATLAB - Python
This repository collects short, classroom-ready examples in MATLAB and Python for teaching and exploring computational methods in finance and data science.
Each topic includes: a MATLAB Live Script (.mlx) with interactive controls, and a Jupyter Notebook (.ipynb) Python version for cross-language learning. Static PDF versions of the Live Scripts are also provided for easy reference and offline review.
The instructions inside the Live Script or the Jupyter notebook guide you through the activities and exercises. It is recommended to run each section individually to observe intermediate results. Interactive controls (such as sliders, checkboxes, buttons, etc.) allow you to experiment with different parameters and datasets, encouraging exploration and hands-on learning. Contents The repository is organized into folders corresponding to the following chapters:
- Data Analysis
QMF1_1_Data_Analysis_ImportingData
QMF1_2_Data_Analysis_FetchData
QMF1_3_Data_Analysis_Distributions
QMF1_4_Data_Analysis_Normalization
QMF1_5_Data_Analysis_Detrending
QMF1_6_Data_Analysis_SmoothingData
QMF1_7_Data_Analysis_Overfitting
QMF1_8_Data_Analysis_MissingData
- Modelling
QMF2_1_Modelling_Optimization
QMF2_2_Modelling_MonteCarloSimulations
QMF2_3_Modelling_Regression
QMF2_4_Modelling_RegressionTestingCAPM
- Machine Learning
QMF3_1_MachineLearning_Supervised
QMF3_2_ML_CreditBonds
QMF3_3_ML_FXTrading
This is a work in progress! Additional material will follow.
Suggested Prework
Introduction to MATLAB MATLAB Onramp - Learn the essentials of MATLAB through this free, two-hour introductory tutorial on commonly used features and workflows.