Course Outline
Part 1
A Brief Introduction to MATLAB
Objectives: Provide an overview of MATLAB's purpose, components, and capabilities.
- Example: C vs. MATLAB
- MATLAB Product Overview
- MATLAB Application Fields
- How MATLAB Can Benefit You
- Course Outline
Working with the MATLAB User Interface
Objective: Gain familiarity with the main features of the MATLAB integrated design environment and its interfaces. Review course themes.
- MATLAB Interface
- Reading data from files
- Saving and loading variables
- Plotting data
- Customizing plots
- Calculating statistics and fitting best-fit lines
- Exporting graphics for external use
Variables and Expressions
Objective: Master the entry of MATLAB commands, focusing on creating and accessing data within variables.
- Entering commands
- Creating variables
- Accessing help
- Accessing and modifying variable values
- Creating character variables
Analysis and Visualization with Vectors
Objective: Execute mathematical and statistical calculations using vectors and create basic visualizations. Observe how MATLAB syntax allows for set-wide calculations with single commands.
- Vector calculations
- Plotting vectors
- Basic plot options
- Annotating plots
Analysis and Visualization with Matrices
Objective: Utilize matrices as mathematical objects or collections of vector data. Understand MATLAB syntax distinctions between these applications.
- Size and dimensionality
- Matrix calculations
- 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 easy reproduction and testing. As task complexity grows, entering long command sequences in the Command Window becomes inefficient.
- 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 overlaid plots, and use color and string manipulation to produce impactful data visualizations.
- Graphics structure
- Multiple figures, axes, and plots
- Plotting equations
- Using color
- Customizing plots
Logic and Flow Control
Objective: Use logical operations, variables, and indexing to create flexible code that adapts to different scenarios. Explore programming constructs for code repetition and 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 distinctions between displaying images and visualizing matrix data via 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 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 functions?
- Creating functions
- Adding comments
- Calling subfunctions
- Workspaces
- Subfunctions
- Path and precedence
Data Types
Objective: Explore data types, focusing on syntax for variable creation and array element access. Discuss methods for converting among data types, which differ in content organization and data kind.
- MATLAB data types
- Integers
- Structures
- Converting types
File I/O
Objective: Explore low-level data import and export functions in MATLAB for precise control over text and binary file I/O. Includes textscan, which offers precise control over text file reading.
- Opening and closing files
- Reading and writing text files
- Reading and writing binary files
Note: The actual delivered content may have minor discrepancies from the outline above without prior notification.
Part 4
Overview of the MATLAB Financial Toolbox
Objective: Learn to apply features of the MATLAB Financial Toolbox for quantitative analysis in the financial industry. Gain the knowledge and practice needed to efficiently develop real-world financial applications.
- 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 key learnings.
- 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 time spent on each topic.
Requirements
- Fundamental undergraduate-level mathematical knowledge, including linear algebra, probability theory, statistics, and matrix concepts
- Basic computer operation skills
- Although not required, familiarity with a high-level programming language (e.g., C, PASCAL, FORTRAN, or BASIC) is advantageous
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
