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R for Financial Services
The R for finance course provides a practical introduction to the R environment within financial services to enable quantitative analysts to quickly become more productive.
Training materials can be customised for a particular environment including the use of sample client data for the class examples and exercises.
Who Should Attend?
This course is suitable for R novices and improvers who wish to use R for statistical analysis of financial markets. Some basic knowledge of finance, linear models and time series analysis will be assumed.
Course Goals
- To provide an understanding of the technology behind the R package
- To improve programming style and confidence
- To understand R's models related to the finance sector
- To enable users to access a wide range of available functionality
- To enable attendees to program in R within their own environment
Course Outline:
As with all our courses, attendees are provided with comprehensive training manuals complete with detailed examples and laminated tip sheets for future reference.
The cost of this course is £1200 for commercial attendees and £800 for academic attendees.
Should you want to book a place on this course or have any questions please contact us at
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Should your organization have more than 3 possible attendees why not talk to us about hosting a customized and focused course delivered at your own premises?
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Course content:
Day 1
Introduction
- What is R?
- The R community and web resource
- R-related journals and conferences
- How is R used in the finance industry
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The R Environment
- The R command line
- Overview of R objects and object creation
- Search paths, the workspace, working directory and package directories
- R packages
- The R GUI
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Data Objects
- Core data types, missing data
- Vectors
- Matrices
- Arrays
- Lists
- Data frames
- Factors
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R functions
- What is a function?
- Calling functions, arguments, return values
- Flow control
- Debugging
- The help system
Day 2
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Important R functions
- Importing and exporting data
- Probability distributions, summary statistics
- Functions for manipulating character data
- Functions for handling missing data
- The apply family
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Traditional Graphics
- Graphics devices and colours
- High level graphics functions
- Graph types
- Univariate graph functions
- Matrix plotting functions
- Low level graphics functions
- Setting graphics parameters
Day 3
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Lattice Graphics
- The Lattice Philosophy
- Panels and strips
- High level functions
- Controlling lattice
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Basic R Statistical and Mathematical Functions used in the Finance industry
- Matrix operations, linear equations
- Quadratic programming
- Optimization functions
- Splines
- Linear models and regression
- Nonlinear regression
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Time Series
- Creating and manipulating time series objects
- Fitting time series models, diagnostics
- Time series graphics
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Overview of additional R finance packages
- zoo
- Rmetrics
- PerformanceAnalytics
Additional packages as time permits
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