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
- Application Fields for MATLAB
- How MATLAB Can Benefit You
- Course Outline
Working with the MATLAB User Interface
Objective: Get an introduction to the main features of the MATLAB integrated development environment and its user interfaces, along with an overview of 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, emphasizing the creation and access of data within variables.
- Entering commands
- Creating variables
- Getting help
- Accessing and modifying variable values
- 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: Use matrices as mathematical objects or collections of vector data. Understand the appropriate use of MATLAB syntax 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: Group MATLAB commands into scripts for easier reproduction and experimentation. As task complexity increases, entering long command sequences in the Command Window becomes impractical.
- 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, emphasis is placed on working with cell arrays and date formats.
- Importing data
- Mixed data types
- Cell arrays
- Conversions among numbers, 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 appealing data representations.
- 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 capable of making decisions and adapting to different situations. Explore programming constructs for repeating code sections and interacting with users.
- 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 typical data analysis tasks in MATLAB, including developing and fitting theoretical models to real-life data. This naturally 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: Enhance automation by encapsulating modular tasks as user-defined functions. Understand how MATLAB resolves references to files and variables.
- Why use functions?
- Creating functions
- Adding comments
- Calling subfunctions
- Workspaces
- Subfunctions
- Path and precedence
Data Types
Objective: Explore data types, focusing on syntax for creating variables and accessing array elements, and discuss methods for converting between data types. Data types differ in the kind of data they may contain and how that 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 delivered content may be subject to minor discrepancies from the outline above without prior notification.
Part 4
Overview of the MATLAB Financial Toolbox
Objective: Learn to apply various features included in 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 spent on each topic.
Requirements
- Fundamental undergraduate-level mathematical knowledge, including linear algebra, probability theory, and statistics, particularly regarding matrices
- Basic computer proficiency
- Preferably, a foundational understanding of another high-level programming language such as C, PASCAL, FORTRAN, or BASIC (though this is not mandatory)
Testimonials (3)
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
Experience and provide necessary information to the topics
