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