**Self-Paced **Matlab – An Introduction for Financial Applications with Jörg Kienitz

**Location: Globally online**

##### This course can be taken as part of the Annual Subscription Service

##### Outline:

The course gives an overview of the Matlab system with a view towards financial engineering. Since this is a beginners course we start by giving an introduction to the basic functionality like plotting, handling of matrices, using m-files and running scripts. All examples are based on financial problems. Thus, we aim to implement the Black-Scholes pricing formula, calculate Greeks. Furthermore, we consider writing programs. To this end we develop basic programming skills and show how to transform algorithms to working Matlab code and how to arrange the code. We wish to use the Binomial model as an example. Finally, we cover useful functionality for everyday life such as interpolation, integration or special functions.

The last topic is on Monte Carlo simulation. We wish to outline the development of a Monte Carlo simulation application for option pricing. To this end we cover random number generation, calculating the Monte Carlo estimator as well as the Standard error and presenting the outcome as a convergence table or a convergence plot.

After the course you know the basic functionality of the Matlab system and you have a solid background for tackling financial problems with Matlab. Furthermore, you are able to explore further techniques such as object oriented programming and larger projects with the skills you acquired during this course.

**Lecture 1. Introduction to Matlab **

- The Matlab Workspace
- Working with Matlab (Importing Data, Vectors, Matrices, …)
- The Help Functionality
- Matlab for Financial Engineering – A Perspective

**Lecture 2. Basic Functionality **

- Plotting and Visualizing
- 2D Plots and Subplots
- Interpolation
- 3D Plots
- Further Issues with Plotting

**Lecture 3. Programming in Matlab **

- m-files
- Script m-files
- Introduction to Programming
- Standard techniques
- Special Matlab topics
- Summary of Basic Programming tasks

- Example: Black Scholes Merton Formula, Greeks, Binomial Trees

**Lecture 4. Data Types **

- Logic Arrays, n-dim Arrays, Sparse Arrays, CellArrays, …
- Function Handles
- Example: Optimization

**Lecture 5. Useful Functionality **

- Special Functions
- Integration and Transforms
- Example: Implementing Option Pricing Methods

**Lecture 6. Monte Carlo**

- Random Number Generation
- Path Generation
- Example: MC Application (Path-Dependent Options)

**Final Practical Project week.**

**The final project will be marked with feedback and a pass or fail will given. One retake is allowed if you fail.**

##### About the Presenter:

**Jörg Kienitz: Director, Financial Risk Solutions, FSI Assurance, Deloitte & Touche GmbH. Previously: Head of Quantitative Analytics, Dt. Postbank AG, Senior System Architect, Postbank Systems AG Financial Consultant, Reuters Academic: PhD Math, Diploma Math Books (Wiley): (A) Monte Carlo Frameworks in C++ (B) Financial Modelling - Theory, Implementation and Practice with Matlab Code**

**PRMIA Certification:**

The Professional Risk Managers' International Association (PRMIA) is a non-profit professional association, governed by a Board of Directors directly elected by its global membership, of nearly 90,000 members worldwide. PRMIA is represented globally by over 65 chapters in major cities around the world, led by Regional Directors appointed by PRMIA's Board

**The Programming School will be fully certified by PRMIA**

**CPD Certification:**

You will be able to receive up to **27 CPD points (9 hours of structured CPD and 18 hours of self-directed CPD)** for completing this course.

The CPD Certification Service was established in 1996 as the independent CPD accreditation institution operating across industry sectors to complement the CPD policies of professional and academic bodies. The CPD Certification Service provides recognised independent CPD accreditation compatible with global CPD principles.

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