R Programming for Finance Training Course

Course Code

rforfinance

Duration

28 hours (usually 4 days including breaks)

Requirements

  • An understanding of finance (securities, derivatives, etc.)
  • A solid grasp of mathematics
  • Programming experience in any language is helpful but not required

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 how to use R to develop practical applications for solving a number of specific finance related problems.

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

  • Understand the fundamentals of the R programming language
  • Select and utilize R packages and techniques to organize, visualize, and analyze financial data from various sources (CSV, Excel, databases, web, etc.)
  • Build applications that solve problems related to asset allocation, risk analysis, investment performance and more
  • Troubleshoot, integrate deploy and optimize an R application

Audience

  • Developers
  • Analysts
  • Quants

Format of the course

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

Note

  • This training aims to provide solutions for some of the principle problems faced by finance professionals. However, if you have a particular topic, tool or technique that you wish to append or elaborate further on, please please contact us to arrange.

Course Outline

Introduction

Setting up the IDE (Integrated Development Environment)
    RStudio

R Programming Fundamentals
    R objects: vectors, matrices, arrays, data frames and lists
    Flow control: branching, looping and truth testing

Accessing Data with R
    Reading and writing CSV data
    Accessing data in a SQL database

Visualizing Data with R
    Plotting with R

Analyzing Data with R
    Manipulating data frames
    Descriptive statistics

Inference and Time Series Analysis
    Analyzing time series data in financial markets
    Volatility modeling for high frequency financial data

Simulating Asset Price Trajectories
    Monte Carlo simulation

Asset Allocation and Portfolio Optimization
    Performing capital allocation, asset allocation, and risk assessment
    Regression analysis

Risk Analysis and Investment Performance
    Defining and solving portfolio optimization problems
    VaR and ES

Fixed-Income Analysis and Option Pricing
    Performing fixed-income analysis and option pricing

Taking Your R Application into Production
    Integrating your application with Excel and other web applications

Application Performance
    Optimizing your application
    R multiprocessing

Troubleshooting

Closing Remarks

Bookings, Prices and Enquiries

Guaranteed to run even with a single delegate!

Private Classroom

From £5800

Private Remote

From £5200 (109)

Public Classroom

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