Course Code

rintrofinance

Duration

21 hours (usually 3 days including breaks)

Requirements

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

Overview

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

Audience

Programmers
Finance professionals
IT Professionals

Format of the course

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

Course Outline

Introduction

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

Troubleshooting

Summary and Conclusion

Closing Remarks

Courses Discounts

2021-01-20 2021-01-22

Izmir

Remote

5250 EUR

4725 EUR

Classroom

6050 EUR

N/A

Select

Testimonials

★★★★★

I liked the new insights in deep machine learning.

Josip Arneric

Course:Neural Network in R

We gained some knowledge about NN in general, and what was the most interesting for me were the new types of NN that are popular nowadays.

Tea Poklepovic

Course:Neural Network in R

I mostly enjoyed the graphs in R :))).

Faculty of Economics and Business Zagreb

Course:Neural Network in R

The flexible and friendly style. Learning exactly what was useful and relevant for me.

Jenny Tickner

Course:Advanced R

I enjoyed the Excel sheets provided having the exercises with examples. This meant that if Tamil was held up helping other people, I could crack on with the next parts.

Luke Pontin