MATLAB for Financial Applications Treningskurs

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21 timer (vanligvis 3 dag inkludert pauser)


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


MATLAB er et numerisk datamaskinmiljø og programmeringsspråk utviklet av MathWorks.

Machine Translated


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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