Date(s) - 09/08/2021
12:00 pm - 1:00 pm
NoCA Training: Introduction to MATLAB with Credit Risk Applications is being provided by Neil Sheridan, FIA.
Neil has over 25 years of working experience including 12 years in various credit related roles in Basel II, Solvency II and IFRS. He is a keen programmer in VBA and sometimes C++. He has embraced MATLAB over the last six years coming to greatly appreciate its power, versatility and ease of use.
The course will comprise of 5 lessons of 1 hour each. Registration closes 24 hours before the first session starts.
Course Level: Beginner
1. 9th August 2021, 12pm – 1pm
2. 10th August 2021, 12pm – 1pm
3. 11th August 2021, 12pm – 1pm
4. 12th August 2021, 12pm – 1pm and
5. 13th August 2021, 12pm – 1pm.
A NoCA Training Certificate will be provided on the completion of the course.
A MATLAB license will be needed plus the “Statistics and Machine Learning” toolbox and the “Symbolic Math” toolbox.
A MATLAB Home license can be purchased for £105+VAT. Add-ons and toolboxes cost £29+VAT each. https://uk.mathworks.com/products/matlab-home.html
MATLAB Student version can be purchased which is about half price and already includes the essential toolboxes, if eligible. Note that Home and Student versions are exactly the same as MATLAB Professional.
A thirty day FREE trial is available for MATLAB and the toolboxes: https://uk.mathworks.com/products/get-matlab.html?s_tid=gn_getml.
Alternatively, Octave is a free software that has a high degree of compatibility with Matlab, can be used. Presenter does not guarantee all commands covered in the course will be tested on Octave.
- The MATLAB user interface
- Entering commands and creating variables
- Analysing vectors and matrices
- Visualizing vector and matrix data
- Accessing HELP
- Example: Bond portfolio valuation
- Working with files: Read and Write from/to Excel and CSV
- Working with data types: Numeric, Text
- Date & Time, logical, Categorical arrays
- MATLAB data structures: Tables, Cells and Structs
- Example: Credit spread history
- Automating commands with scripts
- Writing programs with branching and loops
- Error Handling
- Improving performance
- Example: Calculating portfolio Cost of Downgrade and Cost of Default
- Creating functions: Standalone functions, Function handles, Inline functions
- Variable length arguments and outputs.
- Introduction to Object Oriented Programming
- Example: Bond Portfolio Object
- Optimisation functions
- Distribution Fitting
- Copula Fitting
- Ranking distributions using goodness-of-fit criteria
- Custom distributions
- Example: Spread distribution fitting and Simulation