Formation MATLAB for Financial Applications

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Code formation



21 heures (généralement 3 jours pauses comprises)

Pré requis

A-level maths or economics, or relevant experience in the workplace, is advisable for this material


MATLAB est un environnement informatique numérique et un langage de programmation développé par MathWorks.

Machine Translated

Plan du cours

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:
    1. Dealing with Missing data
    2. Cleaning data, Unusual observations
    3. 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

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