Course Outline
Part 1
A Brief Introduction to MATLAB
Objectives: Provide an overview of MATLAB’s purpose, components, and capabilities.
- Example: C vs. MATLAB
- Overview of MATLAB Products
- Applications of MATLAB
- Benefits of using MATLAB
- Course Structure
Working with the MATLAB User Interface
Objective: Introduce the main features of the MATLAB integrated development environment and its interfaces, while outlining the course themes.
- The 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: Learn to enter MATLAB commands, focusing on creating and accessing data within variables.
- Entering commands
- Creating variables
- Accessing help resources
- Accessing and modifying variable values
- Creating character variables
Analysis and Visualization with Vectors
Objective: Execute mathematical and statistical calculations on vectors and create basic visualizations. Observe 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 distinguish between these uses via MATLAB syntax.
- 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 grows, entering long command sequences directly into 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 from formatted files into MATLAB. Given the variety of data types and formats, emphasis is placed 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, using 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 decision-making and adapting to different scenarios. 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 between displaying images and visualizing matrix data through imagery.
- 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 standard data analysis tasks in MATLAB, including developing and fitting theoretical models to real-world data. This introduces 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 the syntax for creating variables and accessing array elements, and discuss methods for converting between data types. Data types vary based on the kind of data they contain and its organization.
- 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 detailed control for reading text files.
- Opening and closing files
- Reading and writing text files
- Reading and writing binary files
Note that the actual delivered content may differ slightly from the outline above without prior notification.
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 has been 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
- Fundamental undergraduate-level mathematical knowledge, including linear algebra, probability theory, statistics, and matrix operations
- Basic computer proficiency
- Familiarity with another high-level programming language (e.g., C, PASCAL, FORTRAN, or BASIC) is preferred but 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
