R Programming for Finance ( rforfinance | 28 hours )

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

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.

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 an 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