R

The registration for R/Finance 2011–which will take place April 29 and 30 in Chicago–is NOW OPEN!

Building on the success of the two previous conferences in 2009 and 2010, we are expecting more than 250 attendees from around the world representing both industry and academia to join a record 30+ presentations covering all areas of finance with R.

This year we are excited to have longer tutorial sessions and an optional full-day workshop on the Thursday before the conference. In addition, we have worked hard to extend the great networking opportunities on both days with longer breaks and more hallway time between sessions.

This first post of the Backtesting in Excel and R series will provide some resources to help smooth the transition from the familiarity and comfort of Excel to the potentially strange and intimidating world of R.

I made my voyage from Excel to R more than 5 years ago and learned mostly by trial and error (and reading the R manuals).  Most people don’t prefer my approach of “keep at it until you figure it out”, so I don’t have a lot of personal advice to share.  My main piece of advice is that the best way to learn R is to use it, so most of the resources below focus on “how-to” do certain things in R.

This post is the introduction to a series that will illustrate how to backtest the same strategy in Excel and R.  The impetus for this series started with this tweet by Jared Woodard at Condor Options.  After Soren Macbeth introduced us, Jared suggested  backtesting a simple DVI strategy in Excel and R.

The three-post series will show you:

1. Resources that make it easier to move from Excel to R
2. How to test DVI in Excel
3. How to test DVI in R

Since I know next to nothing about testing strategies in Excel, I will be writing posts 1 and 3.  Jared was kind enough to create the Excel framework for post 2, but did not have time to devote to a full post.  Thankfully, Damian Roskill has agreed to write post 2 using Jared’s Excel file.

The 2011 R/Finance conference has an updated call for papers.  Dirk Eddelbuettel announced it to the R-SIG-Finance mailing list.  I’ve reproduced his email in its entirety below.  Let me know if you plan on attending.

Subject: R/Finance 2011: Call for Papers: Now with prizes and travel money

Dear R / Finance community,

The preparations for R/Finance 2011 are progressing, and due to favourable responses from the different sponsors we contacted, we are now able to offer

I use R very frequently and take for granted much that it has to offer.  I forget how R is different from similar tools, so I have trouble communicating the benefits of using R.  The goal of this post is to highlight R’s main strengths, but first… my story.

How I got started with R

I was introduced to R while I was working as a Research Analyst at the Federal Reserve Bank of St. Louis.  I wanted to do statistical analysis at home but the tools I used at work (GAUSS and SAS) were expensive, so I started doing my analysis in Excel.

Before you start, note that there is now a Windows binary of RQuantLib is available on CRAN.

Due to a change in how R-2.12.0 is built, CRAN maintainers could no longer provide a Windows binary of RQuantLib with the QuantLib library they had been using. I decided to try and build an updated QuantLib library from source, which would allow me (and them) to build the current RQuantLib.
Instructions for Getting Started with QuantLib and MinGW from Scratch by Terry August (found in QuantLib FAQ 3.2) were incredibly valuable.  Thanks to Dirk Eddelbuettel for helpful guidance and pointers while I was working through this exercise, and for useful comments on this blog post.

Josh had kindly invited me to post on FOSS Trading around the time when he first came up with the idea for the blog. Fast forward a year and I am finally taking him up on his offer.

I’ll start by highlighting that while all the software in this post is indeed free (true to FOSS), an account with Interactive Brokers is needed to make use of it. For those not familiar with IB, they offer a trading platform that excels on numerous fronts but is most appealing to those of us who trade algorithmically. IB makes available a rather comprehensive API that makes data access and trade execution entirely possible programmatically via a handful of “supported” languages. These include Java (the language of the platform), C#, VBA and even Excel. The also have a POSIX compliant C++ version for those who enjoy C++ but dislike Windows.

As posted by Dirk Eddelbuettel on R-SIG-Finance:

R / Finance 2010: Applied Finance with R
April 16 & 17, Chicago, IL, US

The second annual R / Finance conference for applied finance using R, the premier free software system for statistical computation and graphics, will be held this spring in Chicago, IL, USA on Friday April 16 and Saturday April 17.

Building on the success of the inaugural R / Finance 2009 event, this two-day conference will cover topics as diverse as portfolio theory, time-series analysis, as well as advanced risk tools, high-performance computing, and econometrics. All will be discussed within the context of using R as a primary tool for financial risk management and trading.

Posted to the R-SIG-Finance mailing list today:

For those who missed it, the slides for the R/Finance 2009 tutorials
and presentations are now available on RinFinance.com

http://www.RinFinance.com/presentations

We want to thank everyone who traveled to Chicago to make this happen. With nearly 200 attendees, coming from 8 countries and 20+ states in the US, the conference exceeded all of our expectations. A very big thank you to our presenters for taking the time to join us, UIC’s International Center for Futures and Derivatives for hosting the event, and our sponsors REvolution Computing and Microsoft for their support.

The first international R/Finance 2009 conference in Chicago, IL was a huge success! David Smith from REvolution Computing has written a great summary of the entire event. I’ll take the lazy route and point you to his blog post. :)

The first international conference dedicated to the use of R in the finance industry, R/Finance 2009, was a great success. With over 150 attendees (my poor estimation skills notwithstanding), sold-out tutorials, and an outstanding lineup of invited and contributing speakers from around the world, this event really demonstrated the importance of R in the world of financial analysis.