Course Outline
Part I – Matlab Fundamentals
Matlab Basics
- Matlab User interface
- Variables and Assignments Statements
- Basic data objects: Vector, Matrix, Table
- Basic data manipulation
- Character and Strings objects
- Relational expressions
- Built-in numerical functions
- Data Import/Export
- Visualizing data, Graphics options, Annotations, customizing graphics
Matlab Programming
- Automating commands with scripts
- Logic and flow control - if, if-else, switch, nested ifs
- Loop statements and vectorized code
- Writing functions
Working with Financial Data
- Data objects – Cell arrays, Structures, Tables, Time series
- Working with dates and times
- Conversion amongst different data types, data operations
- Modifying tables, table operations
- Data filtering, Indexing, Logical indexing, Categories
- Data preparation:
- Dealing with Missing data
- Cleaning data, Unusual observations
- Data Transformations
- Statistical functions
Part II – Financial Applications
Overview of Matlab toolboxes relevant to Financial Analysis
- Financial Toolbox
- Financial Instruments Toolbox
- Trading Toolbox
- Risk Management Toolbox
- Econometrics Toolbox
- Optimization Toolbox
- Statistics Toolbox
Financial modelling basics
- Random variables, probability distributions, random processes
- Distribution fitting
- Linear regression
- Simulation modelling – Monte Carlo Simulation
- Optimization modelling
- Optimization under uncertainty
Regression and volatility
- Linear regression
- Spurious regression
- Nonstationarity
- Cointegration
- Conditional volatility models ARCH, GARCH
Portfolio theory and asset allocation
- Dividend discount model
- Modern portfolio theory
Asset pricing models
- CAPM
Market risk management
- VAR by the historical simulation
- VAR by Monte Carlo simulation
- VAR and PCA
Optimization methods
- Convex optimization
- Linear Programming
- Dynamic Programming
- Non-convex optimization
Requirements
A-level maths or economics, or relevant experience in the workplace, is advisable for this material
Testimonials (8)
The content, as I found it very interesting and think it would help me in my final year at University.
Krishan - NBrown Group
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Very tailored to needs.
Yashan Wang
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The trainer was so knowledgeable and included areas I was interested in.
Mohamed Salama
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I enjoyed the good real world examples, reviews of existing reports.
Ronald Parrish
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Intensity, Training materials and expertise, Clarity, Excellent communication with Alessandra
Marija Hornis Dmitrovic - Marija Hornis
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I learned a lot - not only in theoretical knowledge but I also applied that knowledge during the training and therefore I really understood what process mining is and how it works. Thanks a lot!
Julia Dörre - Techniker Krankenkasse
Course - Process Mining
how the trainor shows his knowledge in the subject he's teachign
john ernesto ii fernandez - Philippine AXA Life Insurance Corporation
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I feel more confident with coding now. I've never done it before but now I understand that it's not rocket science and I can do it when necessary.