Course Outline
Part 1
A Brief Introduction to MATLAB
Objectives: Provide an overview of what MATLAB is, its components, and its capabilities.
- Example: C vs. MATLAB
- MATLAB Product Overview
- MATLAB Application Fields
- Benefits of Using MATLAB
- Course Outline
Working with the MATLAB User Interface
Objective: Introduce the main features of the MATLAB integrated development environment and user interfaces, and provide an overview of the course themes.
- MATLAB Interface
- Reading data from files
- Saving and loading variables
- Plotting data
- Customizing plots
- Calculating statistics and best-fit lines
- Exporting graphics for use in other applications
Variables and Expressions
Objective: Enter MATLAB commands, with a focus on creating and accessing data within variables.
- Entering commands
- Creating variables
- Accessing help
- Accessing and modifying values in variables
- Creating character variables
Analysis and Visualization with Vectors
Objective: Perform mathematical and statistical calculations with vectors and create basic visualizations. Discover how MATLAB syntax allows calculations on entire datasets with a single command.
- Calculations with vectors
- Plotting vectors
- Basic plot options
- Annotating plots
Analysis and Visualization with Matrices
Objective: Utilize matrices as mathematical objects or collections of (vector) data. Understand how to use MATLAB syntax appropriately to distinguish between these applications.
- Size and dimensionality
- Calculations with matrices
- Statistics with matrix data
- Plotting multiple columns
- Reshaping and linear indexing
- Multidimensional arrays
Part 2
Automating Commands with Scripts
Objective: Organize MATLAB commands into scripts for ease of reproduction and experimentation. As task complexity grows, entering long sequences of commands in the Command Window becomes inefficient.
- A Modeling Example
- The Command History
- Creating script files
- Running scripts
- Comments and Code Cells
- Publishing scripts
Working with Data Files
Objective: Import data into MATLAB from formatted files. Since imported data can vary widely in type and format, the focus is on working with cell arrays and date formats.
- Importing data
- Mixed data types
- Cell arrays
- Conversions among numerals, strings, and cells
- Exporting data
Multiple Vector Plots
Objective: Create more complex vector plots, such as multiple plots, and use color and string manipulation techniques to produce visually engaging representations of data.
- Graphics structure
- Multiple figures, axes, and plots
- Plotting equations
- Using color
- Customizing plots
Logic and Flow Control
Objective: Use logical operations, variables, and indexing techniques to create flexible code that can make decisions and adapt to different situations. Explore other programming constructs for repeating sections of code and those allowing user interaction.
- Logical operations and variables
- Logical indexing
- Programming constructs
- Flow control
- Loops
Matrix and Image Visualization
Objective: Visualize images and matrix data in two or three dimensions. Explore the differences in displaying images versus visualizing matrix data using images.
- Scattered Interpolation using vector and matrix data
- 3-D matrix visualization
- 2-D matrix visualization
- Indexed images and colormaps
- True color images
Part 3
Data Analysis
Objective: Perform common data analysis tasks in MATLAB, including developing and fitting theoretical models to real-life data. This leads to one of MATLAB's most powerful features: solving linear systems of equations with a single command.
- Handling missing data
- Correlation
- Smoothing
- Spectral analysis and FFTs
- Solving linear systems of equations
Writing Functions
Objective: Increase automation by encapsulating modular tasks as user-defined functions. Understand how MATLAB resolves references to files and variables.
- Why functions?
- Creating functions
- Adding comments
- Calling subfunctions
- Workspaces
- Subfunctions
- Path and precedence
Data Types
Objective: Explore data types, focusing on the syntax for creating variables and accessing array elements, and discuss methods for converting among data types. Data types differ in the kind of data they may contain and how the data is organized.
- MATLAB data types
- Integers
- Structures
- Converting types
File I/O
Objective: Explore low-level data import and export functions in MATLAB that allow precise control over text and binary file I/O. These functions include textscan, which provides precise control when reading text files.
- Opening and closing files
- Reading and writing text files
- Reading and writing binary files
Note that the actual content delivered may vary slightly from the outline above without prior notice.
Part 4
Overview of the MATLAB Financial Toolbox
Objective: Learn to apply the various features of the MATLAB Financial Toolbox to perform quantitative analysis for the financial industry. Gain the knowledge and practice needed to efficiently develop real-world applications involving financial data.
- Asset Allocation and Portfolio Optimization
- Risk Analysis and Investment Performance
- Fixed-Income Analysis and Option Pricing
- Financial Time Series Analysis
- Regression and Estimation with Missing Data
- Technical Indicators and Financial Charts
- Monte Carlo Simulation of SDE Models
Asset Allocation and Portfolio Optimization
Objective: Perform capital allocation, asset allocation, and risk assessment.
- Estimating asset return and total return moments from price or return data
- Computing portfolio-level statistics, such as mean, variance, value at risk (VaR), and conditional value at risk (CVaR)
- Performing constrained mean-variance portfolio optimization and analysis
- Examining the time evolution of efficient portfolio allocations
- Performing capital allocation
- Accounting for turnover and transaction costs in portfolio optimization problems
Risk Analysis and Investment Performance
Objective: Define and solve portfolio optimization problems.
- Specifying a portfolio name, the number of assets in an asset universe, and asset identifiers.
- Defining an initial portfolio allocation.
Fixed-Income Analysis and Option Pricing
Objective: Perform fixed-income analysis and option pricing.
- Analyzing cash flow
- Performing SIA-Compliant fixed-income security analysis
- Performing basic Black-Scholes, Black, and binomial option-pricing
Part 5
Financial Time Series Analysis
Objective: Analyze time series data in financial markets.
- Performing data math
- Transforming and analyzing data
- Technical analysis
- Charting and graphics
Regression and Estimation with Missing Data
Objective: Perform multivariate normal regression with or without missing data.
- Performing common regressions
- Estimating log-likelihood function and standard errors for hypothesis testing
- Completing calculations when data is missing
Technical Indicators and Financial Charts
Objective: Practice using performance metrics and specialized plots.
- Moving averages
- Oscillators, stochastics, indexes, and indicators
- Maximum drawdown and expected maximum drawdown
- Charts, including Bollinger bands, candlestick plots, and moving averages
Monte Carlo Simulation of SDE Models
Objective: Create simulations and apply SDE models
- Brownian Motion (BM)
- Geometric Brownian Motion (GBM)
- Constant Elasticity of Variance (CEV)
- Cox-Ingersoll-Ross (CIR)
- Hull-White/Vasicek (HWV)
- Heston
Conclusion
Objectives: Summarize what we have learned
- A summary of the course
- Other upcoming courses on MATLAB
Note: the actual content delivered may differ from the outline due to customer requirements and the time allocated to each topic.
Requirements
- Undergraduate-level mathematical concepts, including linear algebra, probability theory, statistics, and matrix mathematics
- Familiarity with basic computer operations
- Preferably, some familiarity with another high-level programming language (e.g., C, PASCAL, FORTRAN, or BASIC), though this is not mandatory
Testimonials (5)
Good communication, open for discussion, kept it interesting and engaging
Ahmet Keyman - Keytrade AG
Course - Management Accounting and Finance for Non-Finance Professionals
Experience of the trainer and his way of conveying the content
Roggli Marc - Bechtle Schweiz AG
Course - FinOps
The trainer did not leave a single minute unexploited! He was up a storm throughout every lesson and provided much material for whatever he dealt with.
Elpida - Unemployed
Course - Anti-Money Laundering (AML) and Combating Terrorist Financing (CTF)
The pricing strategies. Need to have more real case examples on the strategies and the pricing methods.
Ruziham A Razak - Telekom Malaysia Berhad
Course - A Practical Guide to Successful Pricing Strategies
Personal service and orientated to my needs
