Introduction to R for Finance Training Course

Course Code



21 hours (usually 3 days including breaks)


  • A basic understanding of finance concepts
  • A solid grasp of mathematics
  • Basic programming experience


R is a popular programming language in the financial industry. It is used in financial applications ranging from core trading programs to risk management systems.

In this instructor-led, live training, participants will learn the fundamentals of R programming as they walk through coding in R using financial examples.

By the end of this training, participants will be able to:

  • Understand the basics of R programming
  • Use R to manipulate their data to perform basic financial operations


  • Programmers
  • Finance professionals
  • IT Professionals

Format of the course

  • Part lecture, part discussion, exercises and heavy hands-on practice

Course Outline


Getting Started with R

  • Overview of R
  • Why Use R in Finance?
  • Setting up the R Working Environment
    • Installing RStudio
  • Running R

Learning the Basics of R Programming

  • Overview of R Programming Fundamental Concepts
    • Vectors
    • Matrices
    • Arrays
    • Data Frames
    • Factors
    • Lists
  • Implementing Your First R Script: Basic Arithmetic with R
  • Assigning Values to Variables in R
  • Understanding Financial Returns
  • Implementing Financial Returns Calculations on R
  • Listing Objects in R
  • Understanding Object Data Types and Storage Modes in R
  • Understanding Object Classes

Using Vectors

  • Using the c() (Combine) Function to Create Vecors
  • Using Vector names()
  • Visualizing Vectors
  • Vector Operations
  • Indexing Vectors
  • Subsetting Vectors
  • Stock Prices Example: Calculating Weighted Averages Using Vectors

Using Matrices

  • Creating a Matrix
  • Binding Vectors to Form Matrices
  • Visualizing Matrices
  • Using the cor() (Correlation) Function
  • Subsetting Matrices

Using Data Frames

  • Overview of Data Frames
  • Creating Your First data.frame()
  • The Contents of a Data Frame
  • Using the head(), tail(), and str() (Structure) Functions
  • Using Row and Column Names
  • Manipulating Data Frames
  • Accessing Data Frames
  • Subsetting Data Frames
  • Adding New Columns
  • Understanding Present Value in Finance
  • Calculating the Present Value of Projected Cash Flows Using R

Using Factors

  • Overview of Factors
  • Creating a Factor
  • Implementing Factor Levels
  • Using the Factor Summary Function
  • Visualizing Factors
  • Bond Credit Ratings Example: Creating a Factor from a Numeric Vector
  • Ordering Factors
  • Subsetting Factors
  • Using Strings as Factors

Using Lists

  • Overview of Lists
  • Creating a List
  • Implementing Named Lists
  • Accessing List Elements
  • Adding Elements to a List
  • Removing Elements from a List
  • Creating Lists Using Functions
  • Splitting a List
  • Stocks Portfolio Example: Implementing Split-Apply-Combine to Your List
  • Using Attributes


Summary and Conclusion

Closing Remarks



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