The aim of this workshop is to provide an introduction to the statistical software R for professionals and academics in Finance. This course gives an insight 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 hundreds of 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 optimization and VaR
-R and Excel
-Preparing reports

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.

Day One: Finance with R

09.30 – Welcome and Introduction to the Programme

09.35 Preparations and installation of R
Christina Erlwein, Fraunhofer ITWM

• 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
Peter Ruckdeschel, Fraunhofer ITWM

• Elementary import functions
• Data types
• Variable generation, inspection and modification
• Coding categorical Variables

11.00 Coffee Break

11.30  Data import, data types and variables, Part II
Peter Ruckdeschel, Fraunhofer ITWM

• Indexing
• Date types
• Missing data

12.00 Hands-on session – data import, data types and variables
Peter Ruckdeschel, Fraunhofer ITWM

13.00 Lunch

14.00 Simulations in R
Christina Erlwein, Fraunhofer ITWM

• Random in R: sample
• Simulating from given distributions
• Reproducible numbers: seed
• Simulating outliers

15.00 Hands-on session - simulations in R
Christina Erlwein, Fraunhofer ITWM

15.30 Tea Break

16.00 Graphics in R
Peter Ruckdeschel, Fraunhofer ITWM

• Command "plot" and where to plot to
• Setting the setting: par
• High-level and low-level plotting functions
• legends
• Math in plots

17.00 Hands-on session – graphics in R
Peter Ruckdeschel, Fraunhofer ITWM

17.30 Close

Day Two: Finance with R

09.30 Application in Finance
Christina Erlwein, Fraunhofer ITWM

• R Metrics
• Calculating Value at Risk
• Packages for Portfolio Optimization

10.30 Hands-on session - application in Finance
Christina Erlwein, Fraunhofer ITWM

11.00 Coffee Break

11.30 This session starts off with the simple GARCH model, then looks at how to modify the objective function to include other common models used in volatility modelling.Yohan Chalabi, Institute for Theoretical Physics, ETH Zurich

13.00 Lunch

14.00 In the second session, Yohan shows how to use the code developed in the first session and see how to improve its executions time. That means learning how to profile R code, understand the performance limit of R and learn how to interface R with external code. The session concludes with an overview of simple parallel computing in R.
Yohan Chalabi Institute for Theoretical Physics, ETH Zurich

15.00 Tea Break

15.30 R and Excel
Peter Ruckdeschel, Fraunhofer ITWM

• The classic way: im-/exporting .csv files
• Excel-like: Rcommander (J.Fox)
• Real Excel: RExcel (T. Baier, E. Neuwirth)
• xlsReadWrite

16.00 Hands-on session - R and Excel
Peter Ruckdeschel, Fraunhofer ITWM

16.30 Preparing reports and outlook
Peter Ruckdeschel, Fraunhofer ITWM

• Programming in R
• Writing R Documentation
• Own Packages

17.00 Close

Dr Peter Ruckdeschel is a research associate at the Financial mathematics group at Fraunhofer ITWM, Kaiserslautern and at the University of Kaiserslautern.
He received his PhD in Statistics at University Bayreuth in 2001 with an award-winning dissertation on Robust Kalman Filtering. He is co-/author of 13 R packages available on the comprehensive R archive network, ranging from integration of automatic markup to R documents, over objected-oriented implementations of distributions to optimally robust estimation. Within the collaborative software development platform r-forge, he is developing—with other authors—R package robKalman. Since his affiliation to ITWM, he has been working on several industry projects covering parameter estimation in stochastic correlation models, quantification of operational risk, and pricing of loans in illiquid markets.

 
Dr Christina Erlwein  is a research associate at the Financial mathematics group at Fraunhofer ITWM, Kaiserslautern. She received her PhD in financial ma¬the¬matics on hidden Markov models in Finance from CARISMA, Brunel University in 2008. She was awarded a Marie Curie Fellowship for Early Stage Researchers and worked within international research projects on financial mathematics at CMA, University of Oslo, Norway, Heriott-Watt University, UK and University of Western Ontario, Canada. She published several papers on applications of HMMs in Finance. Since 2008 she is affiliated to ITWM, where she works on various projects with the financial industry ranging from modelling alternative investments to software concepts for statistical models and credit pricing.

Yohan Chalabi is a PhD candidate in the Econophysics group of PD Diethelm Wuertz at the Institute for Theoretical Physics at ETH Zurich. He holds a master in Physics from the Swiss Federal Institute of Technology in Lausanne. He is a co-developer and co-maintainer of the Rmetrics packages covering time series analysis, hypothesis testing, GARCH modeling, extreme value theory and copulae, pricing of derivatives, portfolio optimization, and much more (www.rmetrics.org). Since his affiliation to the Rmetrics Association, he has given R training courses in Zurich, Singapore and Mumbai and has given R related talks in major R conferences : UseR, Rmetrics Meielisalp Summer School and R/Finance.

Industry Rate: 2 days £1025 + VAT

Thanks to our sponsors, there are a limited number of generous bursaries available for academics and research students so they can attend at the reduced rates of:
Academics: 2 days £275 + VAT
Research Students: 2 days £180 + VAT

For more information regarding bursaries, please contact us on + 44 (0) 1895 819 488 or email info@optirisk-systems.com

Discounted rates for group bookings can be also arranged on request.