Course aim

The aim of this workshop is to provide an introduction to the statistical software R for professionals and academics in Finance. This course gives insights into possibilities of data analysis and statistics with R, import of data sets, generation of graphics and the preparation of reports. The main focus is on applications in Finance. An example of portfolio optimization highlights the options of Rmetrics, which is a collection of several hundred  functions in the area of Financial Engineering and Computational Finance.

Key features

¨ Preparations and installation of R
¨ Data import, data types and variables
¨ Simulations in R
¨ Graphics in R
¨ Exploratory analysis in R with special   focus to time series data
¨ Applications in Finance: Portfolio    optimisation and VaR
¨ R and Excel
¨ Preparing reports

Target Audience

The target audience are professionals and academics, who wish to learn the basics of the statistical software R and its use in Finance.

Benefits of Attending

¨ The workshop provides insight into the statistical models and concepts in R, which are useful for various problems arising in Finance.
¨ The attendees will be able to import datasets into R, analyse them statistically and apply concepts from time series modelling.
¨ An example on how to optimise a portfolio in R will show various concepts in financial mathematics and statistics, which are provided in R. In practical      sessions, the attendees will learn and practice how to use R.

Registration Fee:

2 days £850 + VAT

9:00	Registration and Coffee
9:30	Welcome and Introduction to the Programme
9:35	Preparations and installation of R Some background on R, how to obtain and how to install it Contributed packages R documentation and available help and web resources R Console and R GUI
10:00	Data import, data types and variables Elementary import functions Data types Variable generation, inspection and modification
11:00	Coffee
11:30	Graphics in R Command "plot" and where to plot to Setting the setting: par High-level and low-level plotting functions legends Math in plots
12:30	Hands-on Session—data handling & graphics
13:00	Lunch
14:00	Simulations in R Randomness in R: sample Simulating from given distributions Risk management basics
15.00	Hands-on Session—Simulations in R
15:30	Tea Break
16:00	Data Structures in R             Review of types of objects                 Additional object types
16:30	Hands-on Session---Playing with R
17:00	Basics of the R Language             Conditionals             Loops              Functions
17:30	Close.

Day 2

9:00	Registration and Coffee
9:30	Round-Table: Discussion & Feedback
11:00	Coffee
11:30	Writing R Functions             Basic functions             Object-orientation             Debugging
12:00	Hands-on Session---Writing R functions
13:00	Lunch
14:00	Application in Finance Rmetrics Calculating Value at Risk Packages for Portfolio Optimization
14:45	Tea Break
15:15	Your Future with R             The ups and downs of R in the workplace             Exciting things that can be done in R
17:00	Close.

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Ronald Hochreiter

Assistant Professor at WU Vienna University of Economics and Business. His specialities include  Operations Research, Quantitative Decision Optimization, Optimization under Uncertainty, Financial Risk Management, Asset Liability Management.  He has published a number of articles in these topics and is himself an R Practitioner.

Patrick Burns

Patrick is the Owner of Burns Statistics and is uniquely qualified in modern statistics, computing and finance.  His specialties include Statistical computing especially R and S-PLUS, risk management, portfolio construction, equity modelling, GARCH, optimization via genetic and simulated annealing algorithms, statistical consulting.  Pat is a popular speaker at finance sector events.

Michael Sun

Michael (Xiaochen) Sun, is a senior associate at MSCI, he advises and supports UK/ Benelux asset managers on both quantitative and fundamental equity risk models, portfolio construction/optimisation and extreme risk analysis. He worked at OptiRisk Systems on quant modeling and service marketing from 2004 to 2010. He holds a PhD in Mathematical Science from the Centre for the Analysis of Risk and Optimisation Modeling Application (CARISMA), Brunel University, UK.